geoinformation technology and data models
Transkrypt
geoinformation technology and data models
PiotrCichociński,AgnieszkaDawidowicz,MonikaMika,MarekOgryzek,Tomasz Salata,MonikaSiejka,MarekŚlusarski,AdaWolny GEOINFORMATIONTECHNOLOGY ANDDATAMODELS Zagreb,Croatia,2015 Reviewers JarosławBydłosz RyszardŹrobek ScientificEditors AgnieszkaDawidowicz AdaWolny Publishedby: CroatianInformationTechnologySociety,GISForum 10000Zagreb,Ilica191e,Croatia Copyright© CroatianInformationTechnologySociety,GISForum,Croatia Allrightsreserved Numberofcopies:100 ISBN978‐953‐6129‐44‐7Nacionalnaknjižnica,Zagreb,Croatia 2 CONTENTS INTRODUCTION...........................................................................................................................4 1. MODELOFDATAQUALITYCOLLECTEDINTHETOPOGRAPHICDATABASE..6 1.1.Databaseoftopographicobjects(BDOT10k)asasourceofspatialinformation.......8 1.2.DataqualitymodelBDOT10k..........................................................................................................11 1.3.EvaluationofthequalityofdatacollectedinBDOT10k–experimentalstudies.....16 1.4.Conclusions.............................................................................................................................................20 2.ANALYSISOFFREESOFTWARECAPABILITIESINENSURINGTOPOLOGICAL CORRECTENESSOFSPATIALDATA....................................................................................22 2.1.Geometryissues....................................................................................................................................23 2.2.Topology...................................................................................................................................................24 2.3.Theprocedure........................................................................................................................................25 2.4.Freesoftware..........................................................................................................................................27 2.4.1.QGIS...................................................................................................................................................27 2.4.2.gvSIGCE...........................................................................................................................................28 2.4.3.OpenJUMP.......................................................................................................................................28 2.5.Implementationoftheprocedureinfeaturedprograms....................................................29 2.5.1.OpenJUMP.......................................................................................................................................29 2.5.2.GvSIGCE..........................................................................................................................................32 2.5.3.QGIS...................................................................................................................................................37 2.6.Conclusions.............................................................................................................................................40 3.UPDATINGOFLOCALDATABASESATTHECOMMUNELEVELUSINGGPSTOOLS .........................................................................................................................................................42 3.1.Observationsandmethods...............................................................................................................45 3.2.Resultsanddiscussion........................................................................................................................54 3.3.Conclusions.............................................................................................................................................56 4.ANALYSISOFPOLISHSDIWITHINTHECONTEXTOFNEEDSOFREALESTATE DEVELOPERS...............................................................................................................................59 4.1.Methodology...........................................................................................................................................60 4.2.SDIasanetworkandanenablingplatform..............................................................................62 4.2.1.GEOPORTAL.GOV.PL..................................................................................................................66 4.2.2.AtlasofWarmiaandMazury..................................................................................................69 4.2.3.MSIPMO............................................................................................................................................70 4.2.4.SIPStawiguda................................................................................................................................74 4.3.AssessmentoftheNSDI.....................................................................................................................77 4.4.TheuseofGISsystemsforrealestatemarketinvestors....................................................81 4.4.Conclusions.............................................................................................................................................83 5.SOFTWARE,TOOLSANDINSTRUMENTSUSEDFORTHEPRESENTATION (VISUALIZATION)OFRESULTSOFSPATIALANALYSISINGIS....................................85 5.1.Materialsandmethods.......................................................................................................................86 5.2.Resultsanddiscussion.......................................................................................................................88 5.3.Conclusions.............................................................................................................................................96 REFERENCES...............................................................................................................................98 LISTOFFIGURES.....................................................................................................................105 LISTOFTABLES......................................................................................................................107 NOTESONTHEAUTHORS....................................................................................................109 3 INTRODUCTION As the demand for spatial information grows rapidly there is a need for utilizing, improvinggeoinformationsystemsandadaptingtoolsbasedonIT.Thisbookdiscusses applicationofinformationcollectedinSDIsystemslikespatialdataquality,topicality ofinformationandtopologicalcorrectnessofspatialdata.ItalsopresentsSDIsystems development as well as helpful tools such as GIS software and GPS tools for analysis withintheuseofspatialdata. Spatialinformationisusedindecision‐makingprocessesconcerningthefunctioningof states and quality of life of citizens. The number of institutions recording data and amountofcollectedinformationisincreasing.Topographicobjectsdatabaseisoneof thebasicdatabasescoveringthewholecountryarea.Thatiswhyakeycomponentof anyofficialspatialdatabaseisthemanagementofthequalityofdatacollectedthere. Wherefore the quality of data elements is characterized by varying degrees of significance and by assigning weights to them. The use of weights is particularly importantwhenusingthedatasetscharacterizedbyinternaldiversityofthecriteria forassessingthequalityofdata. Withtheaimofimprovingfulluseofdifferentdataingeographicinformationsystems, thisbookintroducesalsoaprocedureofutilizingtoolsavailableinfreeGISsoftwareto convert CAD drawings into fully‐fledged spatial data sets. This requires finding and testing tools verifying topological correctness of entered data and determining the orderoftheirlaunching.Indicatingwaystotransformtextelementsintoattributesof objects is also necessary. The use of free software enhances possibilities of broad implementation of proposed procedures and thus can speed up the process of convertingdataintousefulformats. Moreover, this study presents the practical aspects concerning the creation and updatingofdatabasesonthecommuneadministrativelevel,thatis,thedevelopmentof thehighestpossibleaccuracyforGISdata.Suchcreateddatabasescanbewidelyused, for example in administrative procedures performed before or during building development and in the coordination of crisis intervention staffs in the area of development. The creation of such an infrastructure within the use of GPS tools enablesaccesstospatialdataandservicesrelatingtoagivenareaaswellasprovides resourcemanagementanduseofgeoinformation. Having regard to diversity of SDI systems this book includes a demonstration of the evaluation of activity in developing local and regional GIS. As local and regional GIS maybeusedfordifferentpurposes,thereisavarietyofparticipantsinvolvedintheir creation and users interested in obtaining information for their needs. That is why another purpose of this elaboration is to show usefulness of geographic information systems within the context of needs of real estate investors ‐ spatial information essentialondifferentstagesofdevelopmentprocess. Finally, this monograph presents the possible application environment GIS software for a variety of spatial analysis, achieved by assigning the target groups of different instruments GIS software. With the aim of modernization of existing records map by 4 definingasetofrequiredfeaturesonnewlayers,theoccurrenceofwhichaffectsthe needsofavarietyofspatialanalysis.AnalysisarecarriedoutsuchtoolsasinArcGIS, MapInfo,EWMAPA,AutoCAD,whichbelongstoagroupofsoftwareGIS.AvailableWeb‐ basedversionsofGISsoftwareallowperforminganalysisandpresentationtheresults ofspatialanalysis. Enjoythereading. ScientificEditors AgnieszkaDawidowicz AdaWolny 5 1. MODEL OF DATA QUALITY COLLECTED IN THE TOPOGRAPHICDATABASE Computer revolution in the second half of the twentieth century initiated the era of information, in which the collected data resources are held by computer systems. These systems allow easy sharing of data, and perform complex analyzes in order to provide processed data. After a brief period of unconsciousness, that computer databasesstorereliableinformation,theresearchonthecomputerdataqualityinthe broadsensebegan. AccordingtoREDMAN(2001)thedataareofhighqualityiftheycanbeusedin operationalprocesses,decision‐makingandplanning.Thefeaturesofgoodqualitydata are: accessibility, comprehensiveness, consistency and accuracy, completeness and usefulness.Thedatashouldhavetheappropriatemetrics.Dataqualitymetricsmustbe characterized by readability, measurability, ease of obtaining and comparability of results.Metricsofdatasetsarecommonlycalledmetadata. A compendium of spatial data infrastructure ‐ The SDI Cookbook (NEBERT, 2015) ‐ distinguishes metadata of recognition, which allow the assessment of the qualityofdatasetanddeterminationofthesetdataintermsofuserrequirements.The main elements of the standard CSDGM (US Federal Geographic Data Committee’s ContentStandardforDigitalGeospatialMetadata)includeinasystematicwayinorder of importance inter alia the following elements: basic information about the dataset, informationaboutdataquality(overallassessmentofthequalityofdatainthefile),the wayofthearrangementofthespatialdataintheset,andothers(LONGLEYATALL,2006). Characterizingthequalityofspatialdata,itispossibletouseseveraldifferent properties. The origin of the data, positional accuracy, attribute accuracy, logical consistency, completeness, semantic accuracy, and temporal quality are the key elementsofdataquality(OORT,2005)and(DEVILLERS,2010). According to GAŹDZICKI (2008) the quality of the data is described by the following features: completeness, logical consistency, positional accuracy, temporal accuracy, thematic accuracy, semantic precision and the origin. The completeness is definedasthepresenceofallthedesireddatawithoutomissionandcommission.The logicalconsistencyisthelackofalogicalinconsistencyinthedataset.Thepositional accuracyreferstothegeodeticaccuracies–expressedbythecoordinatesoftheobjects position. The temporal accuracy is associated with the data changes over time, and thematic accuracy is the correctness of determining, for example, the qualitative properties. Semantic accuracy, represented as a set of data, recreates space of considerations (universe of discourse). The origin describes the method and time of dataacquisitionandsourcematerials,methodsandtechniques. The European Parliament adopted in 2007 the directive, establishing an Infrastructure for Spatial Information in the European Community (INSPIRE). The Directive determines the mechanisms and processes of interaction,accessand use of spatial data. Infrastructure for spatial information is understood as a spatial data set describedwithmetadataandservicesandprocessesassociatedwiththisundertaking (DIRECTIVE, 2007/2/WE). Metadata should include information on, inter alia, the quality and validityofspatial data sets.The Implementing Regulation of the INSPIRE Directive (REGULATION,1205/2008) specifies the record of the history and spatial resolutionasmetadataelementsdescribingthequalityandreliabilityofspatialdata. The European standards ISO 19100 series contain a wide range of concepts relatingtospatialinformationandarecharacterizedbyrichconceptualapparatus.The 6 comprehensive methodology of the data quality description is included in the standard:ISO19157:Geographicinformation–Dataquality(ISO,2013).Accordingto theessenceofthestandardthequalityis“totalityofcharacteristicsofaproduct,that bear on itsability tosatisfy statedand implied needs”. Complete identificationof the quality information should include the "non‐quantitative" and "quantitative" quality information. Non‐quantitative quality information are: purpose, lineage and usage. Quantitative include: completeness, logical consistency, positional accuracy, temporal accuracyandthematicaccuracy. The completeness is defined by the presence and absence of attributes, their featuresandrelationships.Itconsistsoftwoelementsofdataquality:commissionand omissionsinthesetofdata. The logical consistency is defined as the degree of adherence to logical data structures, attributes, and relationships. The structure of data can be conceptual, logicalorphysical.Thelogicalconsistencyconsistsoffourcomponentsofdataquality: the conceptual consistency ‐ the conformity with the rules of the conceptual framework, thedomainconsistency‐theconsistencyofthevalueswiththeirdomain, the format consistency ‐ the degree of compliance of the data record with the physicalstructureofdataset, the topological consistency ‐ the correctness of explicitly stored topological characteristicsofthedataset. The positional accuracy is defined as the positional accuracy of features in aspatialreferencesystem.Itconsistsofthreeelementsofthequality: the absolute or external accuracy ‐ the proximity of the presented coordinate valuestothevaluesconsideredtrueorbeingtrue, therelativeorinternalaccuracy‐theproximityoftherelativepositionsofobjects inthesetofdatatotheirrespectiverelativepositionsrecognizedastrueorbeing true, girded data positional accuracy ‐ the proximity of the girded data to the values consideredtrueorbeingtrue. Thetemporalaccuracyisdefinedasthevalueoftemporalattributesandtemporal relationshipsandcharacteristics.Itconsistsofthreecomponentsofdataquality: theaccuracyofatimemeasurement–thecorrectnessofthetemporalreferences tovaluesacceptedasthetrue, thetemporalconsistency‐thecorrectnessofarrangementofeventsintime, the temporal validity ‐ the correctness of the data with respect to time (up to date). Thethematicaccuracyisdefinedastheaccuracyofquantitativeattributesand the correctness of non‐quantitative attributes and classification of features and their relationships.Itconsistsofthreeelementsofthequality: classification correctness ‐ comparison of classes assigned to objects or their attributes to the space of considerations (e.g. the actual value or a set of reference), non‐quantitative attributes correctness ‐ comparison of classes assigned to objectsortheirattributeswiththescopeofinterest, quantitativeattributesaccuracy‐theproximityofthequantitativeattributevalue tothetruevalue. 7 1.1. Database of topographic objects (BDOT10k) as a source of spatial information Theprimaryobjectiveofthecreationofdatabasesoftopographicobjects(BDOT10k)is to provide access of official specialist spatial information systems to the up‐to‐date andhighqualitytopographicdata.Inthisway,thedatacollectedinBDOT10kprovidea starting point for the construction of spatial information systems for various government and local government institutions, as well as for the private sector (GUIDELINESTBD,2003;GOVERNMENTREGULATION2011)and(GOTLIB2013). The implementation of the presented objective is possible since the topographic database is the primary sources of information their spatial location, characteristics, cartographic codes and also metadata (GOVERNMENT REGULATION, 2011). This information is obtained from multiple reference data sources. As the primarysource,thepublicrecordsshouldbementionedwhichareNationalGeodetic and Cartographic Resource. In contrast, the complementary sources are the records collectedbyotheragenciesandinstitutionssuchasmunicipaloffices,boardsofroads, watermanagement,etc.AnexampleofBDOT10kinthecartographicformisshownin figure1. Fig.1.AnexampleofaBDOT10kdatabaseinthecartographicform. Source:HeadOfficeofGeodesyandCartography According to (GOVERNMENT REGULATION, 2011), (GOTLIB, 2013); (MARMOL andBUCZEK,2013);(ŁABAJ,2013)and(BIELECKA,2010)BDOT10kconsistsofclassesof objects for which the spatial information was obtained from the following reference databases. As the primary database should be considered cadastre of land and buildings, maintained by the county geodetic and cartographic documentation centres. It is asourceofinformationforobtainingandupdatingthegeometryandattributesofthe followingclassesofobjects: 8 building, symbol: OT_BUD_A; information concerning the identifier of the building,statusofthebuilding,numberoffloors,typeofbuildingaccordingtothe PolishClassificationofTypesofConstruction, another construction, symbol: OT_BUIB_A; information on the geometry and the attribute‐thetypeofconstruction, area of grass vegetation or agricultural crops, symbol: OT_PTTR_A; information regardingthesoilscienceclassificationoflandandthetypeoflanduse, locality, symbol: OT_ADMS; information on the locality borders, based on the bordersofregistrationprecincts. Using these data sources must be preceded by a study in terms of completeness, timelinessandtopologicalconsistency. Thestateregistryofboundariesandareasofthestateterritorydivisionunits (PRG) is a database maintained by the Central Office of Geodesy and Cartography Documentation. This database is used in obtaining and updating the geometry and attribute of topographic object classes in the range of local administrative district referencedwiththesymbol:OT_ADJA_A.Theobtainedinformationincludesthename of the unitandthe code ofterritorial division unit. Butfor cartographic studies, they have additional space infrastructure object identifier and the identifier of the border point. The course of borders is taken automatically from the state registry of boundaries database and is not subject to control of the course with the topological boundaries of other objects (rivers, lakes, roads, railways, etc.). Therefore, if the information will be used for the construction of spatial information systems or the productionofmaps,thetopologicalcontrolshouldbecarriedoutbytheuser. The reference database in the range of geographical names, correctness of their sound and spelling, is a database of state registry of geographical names maintained by the Central Office of Geodesy and Cartography Documentation. This registry has spatial and descriptive data for administrative units and physiographic objects.ThesedataareavailableintheSHP,XLS,XML,GML,TXTformats,sotheycan beusedonotherlayersoftopographicobjectsdatabase. The registry of towns, streets and addresses (EMUiA) is a database kept in electronicformbytheauthoritiesofcitiesandcommunes.Itisareferencebaseforthe layerlocalitymarkedwithsymbolOT_ADMS_A.Thisdatabasecontainsinformationon theidentifieroftheobject,theplacename,thetypeoflocality,thenumberofresidents, TERYT identifier, PRNG identifier, and the street name and street type. The data containedinthedatabaseEMUiAoriginatefromthedatabaseoftheStateRegistryOf GeographicalNames(PRNG)intermsofthenamesandtypesofthelocality,whilethe courseofbordersoriginatesfromthedatabaseofthestateregisterofbordersandthe cadastreoflandandbuildings. Aerialandsatelliteimagingaswellasorthophotoanddigitalterrainmodelare databasesusedtoobtainandverifytheobjectsgeometryandalsotheirclassification and initial interpretation. Objects, which cannot be clearly identified on basis of the available materials are subject to verification in the field. The supplement of data on orthophotomap is a digital terrain model (DTM). It allows accurate verification of objects located in areas difficult to access e.g. it enables digitizing and verification of the geometry of water brook in wooded areas. DTM plays an important role in the construction of the contents of cartographic elaborations. This applies to the terrain reliefobjectssuchas:escarpments,contours,mounds,ravines,elevationpointsetc.In caseofthisreferencebase,toensuretheappropriatequalityofthedatacontainedin BDOT10k,itisimportanttomonitortheupdatesofexistingsourcematerials. 9 ThedatabaseoftopographicobjectsBDTO500concerningthedetailsofmaps atscalesfrom1:500to1:5000,isalarge‐scalenumericalelaborationofthecontentof the base map. These databases are maintained in urban and rural areas, butonly for built‐upareasordesignatedfordevelopment.OnthedayoftheelaborationinPoland therearenodataofthistype. National Official Registry of Territorial Division of the Country (TERYT), is adatabase maintained by the CentralStatistical Office. This database is adatabase of reference in the field of territorial units for all records and systems of public administration. The information there contains identifiers and names of territorial division units, identifiers and names of places, names and symbols of streets. This registry provides unambiguous identification of territorial units at different levels of detail (state, county, municipality, city, street, etc.). Thanks to this, it is possible to integrate data between different systems. In the database BDOT10k the following classesofobjectscanbedistinguished: the unit of administrative division, the symbol: OT_ADJT_A; containing the territorial identifier of the superior unit and the identification of the administrativeunit locality, symbol: OT_ADMS_A; containing an identifier of the commune and localityidentifierintheTERYTregistry list of streets, symbol: OT_Ulica; including the identifier of the street coming fromcentralstreetsdirectorymaintainedbytheCentralStatisticalOffice. Databaseregistryofimmovablemonumentsiscreatedandmaintainedbythe voivods. It is created on the basis of a decision on the entry of the object into the register of monuments. This is the basic formof protection of monuments in Poland. Documentation of the national register of immovable monuments is collected by the NationalHeritageBoard.Objectscanbeenteredintheregisterofmonumentsintwo basicformsofprotection.Oneistorecognizetheobjectasamonumenttohistory.The secondformaretheobjectslistedontheUNESCOWorldHeritageList.Thesearethe objects protected under the Convention on the Protection of the World Cultural and NaturalHeritage. The database of topographic objects BDOT10k, contains the following classes of objects: buildings, symbol: OT_BUBD_A; information on the number of general and specificfunctionsofthebuilding, antiqueandhistoricalcomplex,symbol:OT_KUZA_A, object,symbol:OT_OIOR_A;informationregardingthetypeofobject. Registersofmonumentshaveoftenincompleteaddressinformationduetothelackof updatesofchangesofthenamesoftownsorchangesoftheobjectaddress.Therefore, theinformationcomingfromtheregistershouldbeverifiedwithothersources. Reference register for BDOT in the range of water network is the Map of Hydrographical Division of Poland run by the National Water Management and the Institute of Meteorology and Water Management. This map was based on military topographic maps at the scale of 1: 50 000, therefore it has a low accuracy. In this situation, the geometry of the hydrographical network is derived from the current orthophotomap; a reference to the Map of Hydrographical Division of Poland is achievedbygivingtheidentifiertothecorrectobjects.Examplesofobjectsonlayers: 1. surfacewater,symbol:OT_PTWP_A, 2. riverandstream,symbol:OT_SWRS_L, 3. channel,symbol:OT_SWKN_L, 10 4. drainageditch,symbol:OT_SWRM_L. Descriptive and localization data about roads and bridges are acquired from managersoftheseobjects.Dependingontheclassoftheobjectthemanagementcanbe performed by the central, provincial, county or municipal unit. BDOT10k database containsthefollowingclassesofobjects: 1. road, symbol: OT_SKDR_L; information concerning the category of managementandclassofroadattribute, 2. roadway, symbol: OT_SKJZ_L; information concerning the category of managementandclassofroadattribute, 3. road trail, symbol: OT_SzlakDrogowy; information concerning the road numberattribute, 4. roundabout, road junction, symbol: OT_SKRW_P; information concerning the roadjunctiontypeattribute, 5. communication complex, symbol: OT_KUKO_A; information concerning the communicationcomplextypeattributee.g.MOP‐passengerserviceplace. These data on roads and bridges are run in the form of analogue maps and tables containing descriptive information. The enter these data into the BDOT10k database will require inspection of continuity of attributes and the correctness of the entered data. Thepresenteddatarelatingtoobjectsandtheirattributeswhenenteredinto BDOT10kwillbeabletoprovideasystematicsourceofterraininformationforvarious specializedelaborationsonlythenwhentheyarecharacterizedbythehighquality.The main components of the quality include completeness and timeliness of the data. In thissituationBDOTdatabasesmustbesuccessivelyupdatedatspecifiedtimeintervals and be subject to the technical and substantive control (MARMOL and BUCZEK, 2013). The rules of spatial data quality management must resultfrom theadoptedmodel of data quality. The quality model should be designed and formulated before the actual productionofspatialdatatotakeintoaccountuserrequirementsandexpectedquality objectives.Themodelshouldincludetwobasiccorrelatedparts.Thefirstpartrefersto the definition of objectives and quality requirements resulting from the database specification.Thesecondpartdealswiththeevaluationprocessofspatialdata.Inthe proposedmodelofthedataqualityBDOT10kdataqualityelementshavebeendefined. They are described by measures of data quality, evaluation of data quality and the result of data quality. The model also defines the scope and manner of reporting the resultsofthequalityevaluation. 1.2.DataqualitymodelBDOT10k National Management System of Topographic Objects Database (KSZBDOT) which is beingbuiltnowistheprojectaimedatthepurposesofobtaining,control,storageand sharing of topographic information. This will be the information and communication systemmanagingtopographicandgeneralgeographicdatabases,fromwhichstandard cartographic elaborations can be created (ŁABAJ, 2013). The concept is to build a system of several components comprising KSZBDOT. One of the main areas of KSZBDOT functioning will be the module of topographic information data quality management. The module of system data quality management BDOT10k will control the errors detected during data validation and manage the quality model and the set of metadata.CheckingtheaccuracyoftheBDOT10kdatabasedatasetswillbeperformed automatically using templates of data control. The elements of the control templates 11 are following: controlled database definition and specification of the rules of the control parameters. Database definition defines, what class of objects, and additional files should be in the set. Specification of the rules of the control parameters is aregisterofcontrolrulesstoredinastandardformthatfacilitatestheinterpretationof acontroltemplatebytheapplicationexecutingdatacontrol. Inthecontrolprocesstheinternalconsistencyofasetofdatainthetemporary buffer and consistency with the data in the BDOT10k store will be verified. The next stepofdatacorrectnesscheckingwillbeofficecontrol.Thischeckwillbeperformed on a randomselected datasets samplesand will allow the estimation ofdata quality indicators.ThebasisfortheBDPT10kstorageupdatewillbethesituationwhenquality indicatorsdonotexceedthelimitvaluesspecifiedinthemodeldataquality(GUIDELINES (WYTYCZNE),2012). On the basis of the assumptions of the National Management System of Topographic Objects Database project and implemented in 2012‐2013 undertakings concerningthecreationofBDOT10k,theschemeofqualitycontroloftopographicdata canbeformulated.Fragmentofthediagramofdataqualitycontrolprocessisshownin figure 2. The data sets are subject to the quantitative and qualitative control. Quantitative control verifies the correctness of files saving and their structure, completeness and nomenclature. Quality control is carried out by means of three components: automatic, office and field control. Automatic data control of BDOT10k consists of five basic components: data BDOT10k validation with the GML scheme attribute control in GML files, geometry control, topology control and additional checking. The second step of the quality control is the office control. Its purpose is to examine the detail substantive compliance of reported data with source materials. Area under the control is selected by the selection of the data sample consisting of representative areas and objects. The data are verified due to the: completeness and accuracyofobtainingdatafromotherregisters,thecorrectnessofthepositionofthe introduced objects, the correctness of entering of the values of attributes and the correctnessoftheidentificationofBDOT10kobjects. The third step of the quality control is the field control. The purpose of this controlistoexaminethesubstantivecompatibilityofthetransferreddatawiththereal situationontheground.SubjecttothecontrolareallobjectsenteredtotheBDOT10k in the area of sample data selected for control. Quantitative and qualitative controls canbeperformedinseveraliterationsuntilapositiveresultisobtained(ZAPALSKA and STUGLIK,2013). Currently, the only legal act regulating the rules of creating and updating BDOT10kistheRegulationofNovember17,2011onthetopographicobjectsdatabase and general geographical objects database, and also standard cartographic elaborations(GOVERNMENTREGULATION,2011).TheprovisionsoftheRegulationdo notexplicitlydefinetheprinciplesofdataqualitymanagement.In§19iswrittenonly thatsystemsupportingBDOT10kshouldprovide,interalia,dataqualitycontrol.Data quality elements are contained in the Annexes to the Regulation. Annexes provide, inter alia, a catalogue of objects with their attributes, relationships and constraints, classification of objects at three levels of detail, UML and GML application diagrams andguidanceconcerningtherulesofenteringtheobjectstoBDOT10k.TheRegulation doesnotdeterminethescopeofthedatacontrol,officeandfieldcontrolrulestaking intoaccountthesizeofthedatasamplesandtheacceptableleveloferrorforthedata set. 12 Control of data sets should include validation of database creation and technological and substantial aspects of content. Technological control is mainly analysisofthemethodofdatarecording,thetopologyandconformitytothestandards of data exchange. Substantive correctness is the data completeness, the fulfilment of the required accuracy and compatibility of data with real terrain situation (BIELECKA, 2010). Quantitycontrol Kontrola ilościowa +completenessoffiles + kompletności +correctnessofrecord plików +filesavingstructure + poprawności +... zapisu yes Data Dane correct? poprawne Supplement ofdata no ? Correctionofthe elaboration Automaticquality Kontrola control jakościowa automatyczna + validation of BDOT10k data with + walidacji danych GMLscheme BDOT10k ze +attribute schematem +geometric GML + atrybutowa +... + Officequality control +Substantial conformitywithsource data Fieldcontrol + Substantial conformity with the fieldsituation t AcceptanceofBDOT10k Przyjęcie BDOT10k toNationalGeodeticand do Państwowego CartographicResource Zasobu Geodezyjnego yes Data correct? no Fig.2.Thediagramofdataqualitycontrolprocess(part). Source:SIEJKAandŚLUSARSKIownstudybasedon(GUIDELINES,2012) The principles of BDOT10k data quality management must result from the adoptedmodelofdataquality.Thequalitymodelshouldbedesignedandformulated 13 beforetheactualproductionofspatialdatatotakeintoaccountuserrequirementsand expectedqualityobjectives.Themodelshouldincludetwobasicinterdependentparts. Thefirstpartreferstothedefinitionofobjectivesandqualityrequirementsresulting fromthedatabasespecification.Thesecondpartdealswiththeevaluationprocessof spatialdata. Theconstructionofdataqualitymodelincludesdefiningitscomponents.The maincomponentsofthemodelare: dataqualityelements, measuresofdataquality, methodsofevaluationofdataquality, resultofdataquality, metaquality, scopeofdataquality, metadata. For BDOT10k elements of data quality concern the five major components. Investigation of completeness is called quantitative and qualitative control. Quantitative control verifies the correctness of files saving and their structure, completeness and nomenclature. Quality control of completeness is mainly based on examining the occurrence of excess or deficiency of objects and their attributes and relationships. Logical consistency is the degree of compliance with the logical rules applicable to data structures, attributes and relationships. Here the co linearity and continuity of objects conditions are checked, preserving of the spatial rules and correctness of linear objects segmentation. Positional accuracy is assessed by geometricaccuracyofobjects.Thisfeaturefocusesontheproximityofthecoordinate values to values accepted as true and proximity to the relative position of objects to their correct relative position. The temporal accuracy will be implemented using informationontimelinessandthedateofthedatasetcreation.Thethematicaccuracy is examined in terms of correctness of classification, non‐quantitative attributes correctnessandtheaccuracyofquantitativeattributes. Examination of the quality of BDOT10k data should be based on several measureseasytounderstandbytheuserofthedatabase.Themainmeasuresofdata quality are: number of incorrect objects, attributes, and relationships, and the error coefficient,thatis,theratiooffalseobjects,attributes,andrelationshipstotheirtotal number. In the assessment of the geometric accuracy of database objects understandable to interpret measures are: mean square error, circular error (CE95) andlinearerror(LE95).CE95erroristheradiuscircumscribingthecircle,inwhichthe realpointislocatedwiththeprobabilityof95%.Linearaccuracyofmapwitha95% levelofsignificance(LE95)ishalfthelengthoftheintervaldefinedbytheupperand lowerlimit,inwhichthetruevalueislocatedwiththeprobabilityof95%.CE95error is applicable to the study of one‐dimensional properties, such as the corners of buildings or network nodes. Linear error (LE) determines the likelihood of misplacementoftwo‐dimensionalfeatures,suchasborderlinesorcentreline(ESDIN, 2010). Theresultofdataqualityassessmentshouldbepresentedseparatelyforeach itemofdataquality.Theevaluationresultswillbegivenindifferentunits,depending onthenatureofuseddataqualitymeasures.Geometricalaccuracywillbeexpressedin the unit of distance, and temporal accuracy (timeliness of data) in unit of time. Databaseuserinterpretingtheresultsmusthaveknowledgeofthesevaluesandunits. The results of the data quality will be easier to understand, if all the results are 14 presentedbyasinglescaleorunits.Itcanbedonebycreatingalevelofcompliancefor each data quality measure. Then it is necessary to specify for each result of data quality,inwhichconformationclassislocatedtheresult.Determinationandgradation of conformation classes for BDOT10k can be based on the classification of objects contained in Regulation on the database of topographic objects (GOVERNMENT REGULATION, 2011). First class (I ‐ the highest) includes communication networks, infrastructure networks and buildings, structures and equipment. Next class (II) includesland‐usecomplexesandterritorialdivisionunits.Thethirdclass(III)includes anetworkofwaters,landcoverandprotectedareas. In addition, the characteristics of data quality can be described by ametaquality. Metaquality elements include a set of quantitative and qualitative measures of quality assessment and its result. Metaquality can be described in three meanings: as a confidence, representativity and homogeneity. The confidence means thecredibilityoftheresultsofdataquality.Representativityisthelevelatwhichthe useddatasamplesreachedtheresult,whichisrepresentativeforthedataintermsof data quality. Homogeneity is expected or tested uniformity of the results obtained during the evaluation of data quality (ISO, 2013). For BDOT10K Metaquality should informtheuserofdataaboutthelevelofreliabilityoftheobtainedevaluationresults. Statistical measures such as standard deviation and coefficient of variation may be usefulhere.Descriptionofthemethodofsamplingshowsdegreeofrepresentationof thedataset.Homogeneityassessmentwillbeneededmainlyinthecaseofenteringto one database, information from various sources. It is necessary then to carry out comparisonoftheresultsofthequalityassessmentfordatafromdifferentsegmentsof agivenset. The scope of data quality determines spatial and temporal characteristics, identifyingthedataonwhichthequalityofdataistobeassessed.Thischaracteristics include:thegeographicalcoverage,thetimescope,thedatasetordataseries.Inthe modelofBDOT10kdataquality,thescopeofqualityisdefinedbydefiningasetofdata, classofobjects,attributes,relationships,andsamplesizes. Spatialdatausershavenowwidespreadaccesstounlimitedresourcesofthese data. The valuable data are those that have the appropriate metrics describing data setscalledmetadata.Metadataasquantifiersdescribingspatialdatasetsshouldamong others include information on location and type of objects, their attributes, origin, accuracy,detailsandtimelinessofthedataset(BIELAWSKI,2013).Qualityinformation ofBDOT10kdatabasemaybegivenintheformofstandardqualityreportsorbeapart ofthecollectionofmetadata.Presentationoftheinformationaboutthedataqualityin the form of metadata simplifies their analysis and will facilitate access to them for producersandusersofdata,becausethemetadatahaveastrictlyformalizedstructure. ConceptualproposalofBDOT10kdataqualitymodelisshowninfigure3. 15 Dataquality scope +thesetofdata + classes of objects +attributes +relations + sizes of l defined by Dataquality BDOT10k isreported is expressed Metadata +.... +informationof dataquality +.... Dataquality element +completeness +logicalconsistency +positionalaccuracy +temporalaccuracy +thematicaccuracy is described Dataquality measure + number of incorrect objects, attributes and relationships +errorindex + geometrical accuracy Dataquality evaluation + direct and internal + external (full control and sampling) +.... Dataquality result + the expected level of compliance +.... Metaquality +confidence +representativity +homogeneity Fig.3TheconceptualmodelofdataqualityBDOT10k. Source:SIEJKAandŚLUSARSKIownstudybasedon(ISO,2013). 1.3. Evaluation of the quality of data collected in BDOT10k – experimental studies Experimental studies of spatial data quality were performed by analyzing the information contained in the BDOT10k database for the Zielonki community in the Malopolskie Voivodeship. Zielonki is a rapidly growing community,which is adjacent to Krakow. It covers an area of 48.4 square km, and the number of its inhabitants in 2013 exceeded 18 thousands of people. Built‐up and urban areas account for about 15%ofthecommunearea.InTheDistrictGeodeticandCartographicResourceforthe community there are available the digital land and buildings cadastre map and the digitalbasemap.Experimentalstudiesofspatialdataqualitywereperformed,paying particularattentiontotheneedsoftheuserofthedataset. Examination of the completeness is mainly quality control investigating the occurrenceinthedatabaseofexcessordeficiencyofobjectsandtheirattributesand relationships.ForBDOT10kofZielonkicommunethefieldinspectionswereperformed and additional verification tests based on digital base map and orthophotomap. As aresultofthecarriedoutstudiessignificantdeficienciesinthedatabaseobjectswere 16 found,mainlyinthecategoriesofbuildings,structuresandequipment,infrastructure and utility networks. The deficiencies are estimated at 40%. The reasons for this situationmaybetwo.Thefirstisthelackofbasemapinthedigitalgeodeticresource duringcreatingthedatabase.Thesecondoneistheuseofanoutdatedorthophotomap. Additionally, a control of attribute values of objects was performed. Considerable deficiencies in attribute values were found, for example the height and number of floorsofthebuilding. WithregardtothelogicalconsistencyofBDOT10kisthedegreeofcompliance with the logical rules of data structures, attributes and relationships. For the test database co linearity and continuity conditions of objects were checked and the accuracy of the segmentation of linear objects. The study was performed using the QGIStools.Practicallytherewerenoweaknessesinthelogicalconsistency,analyzing thecriteriarelevanttotheuserofspatialdatabases. Positional accuracy is assessed by geometric accuracy of objects. An error of positionsofobjectsinBDOT10kshouldnotexceed1.5m.Theaccuracyofthedatabase objectsisaffectedbythequalityofthesourcematerials,correctnessofinterpretation andaccuracyofdigitizing.ForBDOT10kofZielonkicommunechecksoftheaccuracy based on the reference material, which is the digital base map, were performed. As aresult of this analysis it was found, that more than half of the analyzed object does notfulfiltherequiredparametersofthegeometricaccuracy. The temporal accuracy is defined as the value of temporal attributes and temporal relationships and characteristics. For the user of BDOT10k, the most important is the temporal importance, or timeliness of the data set. BDO10k is currently not subject of present updates, and changes in the land use in urbanized areas affect the progressive obsolescence of the database. Analysis of temporal accuracyofthedatacollectionofthestudyareashoweditstimelinessat80%level. Thematic accuracy is the precision of the objects classification correctness, non‐quantitative attributes correctness or accuracy of quantitative attributes. The correctness of the classification and the correctness and accuracy of the attributes wereratedasaresultofthecomparisonwithsourcematerials.Practicallytherewere notfoundanyweaknessesinthethematicaccuracy,analyzingthecriteriarelevantto theusersofspatialdatabase. TheresultsoftheassessmentoftheBDOTdatabasequalitycarriedoutforthe Zielonkicommunityareshownintable1.Theresultsareshownusingpointvaluesin therangefrom1to100. Table1.Theresultsofthedataqualityevaluation. No Elementofdataquality 1 2 3 4 5 Completeness Logicalconsistency Positionaccuracy Temporalaccuracy Thematicaccuracy Theevaluationpoint values 60 99 40 80 95 Source:SIEJKAandŚLUSARSKIownstudy. Data quality elements are characterized by varying degrees of significance, therefore during the BDOT10k database qualitative assessment it is necessary to assign to them appropriate weights of validity. The sizes of the weights were determinedbytheAnalyticHierarchyProcess(AHP).TheAHPisoneofthemethods 17 usedtosolvecomplexmultivariatetasksthroughthecreationofahierarchystructure. At every level of the hierarchy a matrix is created, resulting from the pairwise comparisons of individual elements of the hierarchical structure. (PIASEK and SIEJKA, 2003). Inthisway,elementsofmatrixA’meetthefollowingconditions: ‐ allelements aij>0 ‐ diagonalelements aii=1 ‐ symmetricalelements aij=aji‐1 MatrixA’hasalwaysrealandpositiveeigenvalueλ,whichhasthefollowingproperties (SAATY1977),(SAATY1980): 1. itissimplerootofthecharacteristicequationofthematrix, 2. it is the largest (as regards the module) eigenvalue of the matrix, and corresponding to this eigenvalue eigenvector w has always all the componentspositive(wi>0). Therefore,inordertoobtainasolutionitisnecessarytodetermineforeachmatrix,the maximum eigenvalue λmax and associated with this value eigenvector w, which is avectorofpriorities. Aftersettingpartialprioritiesforalllevelsthesolutionofthetaskisavector: k C[1, k ]T Bi Bk Bk 1 B2 i 2 where: C[1,k] ‐ the vector of results of priorities attached to the elements of the hierarchicallevelkwithrespecttothethesis, Bi‐thematrixofresultsfortheleveli,whichcolumnsarethevectorsof prioritiesofelementsofthislevelrelativetoelementsoftheleveli–1. Inordertoverifythecorrectnessoftheresultstwoindicatorswereintroduced(SAATY, 1980): 1. consistencyindex–CI CI 2. max n n 1 0,10 where: n–thedimensionofthematrix λmax–themaximumeigenvalueofthematrix consistencyratio–CR CR CI 0,10 RI where:RI(randomindex)dependsonthesizeofthematrixn,thetable2. Table2.ThevalueofRIdependingonthedimensionofthematrix n 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 RI 0 0 0,58 0,90 1,12 1,24 1,32 1,44 1,45 1,49 1,51 1,53 1,56 1,57 1,59 Source:SAATY,1980. 18 WhentheconsistencyratioCR>0,1orconsistencyindexCI>0,1,theassessmentofthe dependenceoftheelementsofthematrixmustberepeated. ThefirststepofdeterminingthevalidityweightsinthestudyofBDOT10kistocreate matrix of pairwise comparisons for the five elements of data quality (completeness, logical consistency, positional accuracy, temporal precision and thematic accuracy). Preferences are expressed using a scale from 1 to 9, where 1 is the equivalence of comparable elements, and 9 ‐ extreme preference of one component relative to another. Considering the quality of the BDOT10k data from the level of the user's needs,Aweightmatrixofvaliditywilllooklikethis: 1 9/1 5/13/13/3 1/9 1 1/71/71/2 A= 1/5 7/1 12/13/3 1/37/11/213/1 1/32/11/31/31 Thenextstepistocalculatetheeigenvectorofthematrixofpreferences.SAATY(1980) provedthatthisapproachisoptimalinordertofindthefinalrankingoftheconsidered criterion.Asaresultofthecalculationstheweightvectorwasobtained.Vectorwisa vector of weights in relating to the five elements of the quality of data representing userpreferences. w=[0.49,0.04,0.21,0.18,0.08] In order to verify the results of pairwise comparisons of matrix A elements, consistency index and consistency ratio were calculated. The calculated values of the coefficientswererespectively0,068and0,061. Table 3 indicates the point values of data quality assessment for the five featuresdescribedbythepointvaluesonascalefrom1to100,onthebasisoftable1. Theweightsofindividualdataqualitycriteriacomefromthematrixw. Table 3. The point values of data quality evaluation and the values of calculated estimators No 1 2 3 4 5 Calculated estimates Criteriaofdata quality Theevaluation pointvalues Weights Completeness Logical consistency Positionaccuracy Temporal accuracy Thematic accuracy 60 0.49 Pointvaluesfor assessment‐ weighted 29 99 0.04 4 40 0.21 8 80 0.18 14 95 0.08 8 Theaveragevalue 75 Thecoefficientof variation 0.33 Theaverage weightedvalue Thecoefficient ofvariation 63 0.16 Source:SIEJKAandŚLUSARSKIownstudy. Overall evaluation of the quality of the BDOT10k data was performed by calculatingtwoestimators:theaveragevalueandthecoefficientofaveragevariation. 19 Theaveragevalueofalldataqualitycriteriashows,howbigpartofthedatameetsthe established criteria of 100 points. The difference of 12‐points between the values of averageandweightedaverageshowsthemeritsoftheapplicationofvalidityweights inthestudyofspatialdataquality.Inaddition,thevaluesofcoefficientsofvariationfor the average and the weighted average are 0.33 and 0.16 respectively. They showthe consistency of the result of the data quality evaluation calculated using weights. Aconceptualmodelisoneinwhichthecoefficientofaveragesvariationiszero. 1.4.Conclusions In recent years, demand for spatial information is growing rapidly. They are used in decision making processes concerning the functioning of state and quality of life of citizens. Increases also the number of institutions collecting the data, as well as the amount of information collected. In Poland, are created and maintained the official databases collecting spatial information. BDOT10k is one of the basic databases covering the whole country. A key component of the official spatial the database is qualitymanagementofthecollecteddata. BDOT10k due to its complexity of structures and a wide range of topics of collected data requires the use of advanced techniques for data quality control. Currently there is no official solution for quality management purposes in BDOT10k. There are no official control templates and software applications for data control. Controltemplatesshallbeessentiallyconsistentwithcurrentlegislationandassumed as independent from the particular commercial development. The proposed in the work concept of data quality model forBDOT10k will be useful for creating National ManagementSystemofTopographicObjectsDatabase. ExperimentalstudyofthequalityofthedataofBDOT10kdatabasewascarried out in Zielonki commune, Malopolskie Voivodeship. Performing a qualitative assessment,particularattentionwaspaidtotheneedsoftheuserthedataset.Criteria forassessingthequalityofdatasetwerebasedonfivecriteria:completeness,logical consistency,positionalaccuracy,temporalaccuracyandthematicaccuracy.Asaresult ofthisanalysisitwasstatedthat,morethanhalfoftheanalyzedobjectdoesnotmeet the required geometric accuracy parameters. Studies of completeness have shown deficienciesofthedataatthelevelof40%.Researchofthetemporalaccuracyofthe data set for the study area showed its timeliness at 80%. Practically there were no weaknesses found in the thematic accuracy and logical consistency, analyzing the criteriarelevanttotheuserofspatialdatabases.Forthematicaccuracy95%metthis criterion and 99% for logical consistency. Based on these results an average data qualityassessmentfortheBDOT10kdatabaseis75%. Doing the research of data quality from the point of view of the user it is necessary to remember, that data quality elements are characterized by varying degrees of significance. For this reason, during the qualitative assessment the appropriate weights should be assigned to them. The sizes of the weights were calculatedusingAHPmethodintherangeofdataqualityelementsrepresentinguser preferences.Themostimportantqualitycriterionisthecompletenessofthedataset‐ 49points(atascalefrom1to100),furthergeometricalaccuracy‐21pointsandthe temporalaccuracy‐18points.Thematicaccuracy‐8pointsandlogicalconsistency‐4 points,areofminorimportanceforthequalitativeassessmentofthespatialdatabase from the point of view of the user's needs. The weighted average assessment of BDOT10kdatabasedataqualityis63%. 20 Result of data quality assessment of the BDOT10k database calculated using weightsislowerby12percentagepointscomparedtotheresultobtainedwithoutthe use of weights. This fact points to the validity of the use of weights in the study of spatialdataquality.Inparticular,theuseofvalidityweightsisimportantwhenusing thedatasetscharacterizedbyinternaldiversityofthecriteriavaluesforassessingthe qualityofdata. 21 2. ANALYSIS OF FREE SOFTWARE CAPABILITIES IN ENSURING TOPOLOGICAL CORRECTENESS OFSPATIALDATA The increasing demand for the data and information of a spatial nature in the past threedecadesaswellasthedevelopmentsintheareaofinformationtechnologiesand informatics, has led to the development of automated tools for efficient storage, analysis and presentation of geographic data. This rapidly evolving technology has become to be known as Geographic Information Systems (GIS). Geographically referenceddataseparatesGISfromotherinformationsystems. SimplevectormodelsinGISbuilduponpointsandlines.Areas(polygons)are modelled by closed loops of lines – there may be inner loops to exclude “islands” (INTERNATIONALORGANIZATIONFORSTANDARDIZATION,2004).Simplegeometric elements: point, line and polygon are furnished with semantic attributes, thereby creatingfeatures.Thismustbedoneexplicitly.Therefore,avectormodelisalsocalled geo‐relational. Geographical feature, representing ground element, is made up of two components (GOMARASCA,2009): positional, which graphically and geometrically defines the position and the shapeof theobjectsrepresented bygeometricprimitives like points, lines and polygons(e.g.poles,roads,parcels); descriptive, expressed by alpha‐numerical declarations, aimed at qualifying somenon‐spatialpropertiesofthegeometricalfeaturesbymeansofattributes (numbers, strings, date); i.e. pole height, road surface, parcel number, etc. Attributesarearrangedintablesandeachfeaturehasadatabasetablerecord. Geographic features are organized into thematic layers, allowing segregating differentkindsoffeatures.AdditionallyeachGISlayerhasahomogeneousgeometric type(allpoints,lines,orpolygons). IntheerawhenGISsoftwarewasnotyetsopopularandwidelyusedComputerAided Design (CAD) software and other vector graphics programs were used for map creation. CAD software has powerful functions of graphics drawing and graphics editing. It can draw many different geometric shapes, such as points, lines, polygons, circles, arcs, ellipses etc. Therefore it is well suited to draw digital maps. Nowadays CADfilessuchasAutoCADdrawingfiles(DWG),MicroStationdesignfiles(DGN),and Autodesk'sdrawingexchangeformat(DXF)canserveasgoodsourcesofGISdatasets (ESRI,2001). CADfilescontainsometextualandmainlyvectordatathatcanbeusedtopopulateGIS data sets. In general terms CAD files contain a collection of autonomous geometric objects(alsocalledentitiesorelements)thataredefinedbystaticgraphicproperties, suchascolour,linestyle,andlineweight,andarelooselyorganizedbylevelorlayer. Layering is the most widely used technique for managing the complex information contained in larger drawings and CAD models (INTERNATIONAL ORGANIZATIONFORSTANDARDIZATION,1998a).Thisconsistsofassigninggraphical drawingelementsofthesametypetoinvisiblelayers,whichcanbeturnedonandoff, bothonthescreenandinpaperprintouts,tohelptheusertofocusononlythatwhich isessentialtoherwork,hidingtherestoftheinformation. Since Layering is a widely used method for structuring data in CAD models, during the last few years national standardization organizations, professional associations, user groups for particular CAD systems, individual companies etc. have 22 issued numerous standards and guidelines for the naming and structuring of layers, especially in building design. In order to increase the integration of CAD data in the industryasawholeISOdecidedtodefineaninternationalstandardforlayerusage– ISO13567(INTERNATIONALORGANIZATIONFORSTANDARDIZATION,1998b). Although CAD layer is often used to organize and define default symbols for acategory of objects in aCAD file, in practice CAD layer can be used to hold objects from many different categories, or CAD objects in a category can be spread out over many CAD layers. In some sense CAD layers are nothing more than other entity properties, such as colour or line type. This causes that there is a great deal of flexibilitywithinCADtoorganizedata. InaCADfile,enforcementofdataorganizationisthesoleresponsibilityofthe CADstandardsimplementedbytheorganizationandsubsequentlyadheredtobythe CADoperator.CADstandardsdonotalwaysseparateobjectsystemsbylayer–objects couldbedifferentiatedjustaswellbycolourorlinestyle.Sometimesdataorganization is dictated by an application that creates the data. The use of well‐defined data standardsisessentialinavoidingambiguityandpoordataqualityinaCADfile(ESRI, 2003). In addition to the purely geometric data CAD drawings can also contain descriptions of objects. There are a variety of methods used within AutoCAD and MicroStationtomaintaindescriptiveattributesonCADobjects.Fortunatelyincaseof mapdatausuallysimplelabellingisusedbymeansoftextslocatedonmaps. 2.1.Geometryissues Because of presented above different data models and the different intended uses of theCADdrawings,theprocessofusingCADdatainaGISorconvertingCADdataintoa GIS data set requires conversion form CAD data to GIS data. The conversion process includes two parts: one is graphical data conversion, and the other is attribute data conversion. Data migration is often the most challenging and expensive step in the GIS implementation. Importing data from external sources requires some necessary treatment and management such as separating and classifying features, editing geometric elements and modifying the attributes. Recent advances in GIS software havemadeitsimplertomoveCADdataintoGISdatabases,however,manyquirksstill existinfiletransferduetotheintrinsicdifferencesinthefileformatsandstructure. It is common in CAD or general‐purpose vector drawing software to have anetwork of line segments that are used to define the visual boundaries of polygons and to use separate point objects, such as text entities, to identify the “would‐be” polygons. This particularly happens when boundaries of parcels have been drawn usinglinesandnumbershavebeenpresentedusingtexts. It is much easier to draft polygons as a collection of line segments than it is to draw closed polygons (ESRI, 2004). But, unfortunately, they do not include necessary information for executing even the most elementary operations and calculations on givengeometricdata(ŽALIK,1999).Forinstance: itisnotpossibletofillindividualparcels, it is not possible to determine which parcels are neighbours to a specified parcel, itisnotpossibletocalculatetheareaofadesiredparcel. 23 Obviously, such representation of geometric data is not sufficient to automate aforementionedoperations.So,itisnecessarytocreatepolygonsfromacollectionof CADlinesthatarenotdrawnasclosedpolygons. Whenthereisahighdegreeofconfidenceinthedata,theycanbeused“asis” to generate polygons from lines and points. But this can be done only under the assumptionthateachparcelissurroundedbyboundarylinesandexactlyonenumber is located inside that identifies it.To be able to builda polygonallborder linesmust touch each other only at their ends and form closed rings. Moreover, it should be possibletoconverttextsrepresentingparcelnumbersintoparcelattributes,storedin attributetable. But it may happen, that maps drawn in CAD software look perfectly correct and complete only when displayed by a computer. This way, dangerous illusion of “acorrect” computer‐based maps is achieved whereas in fact there are so‐called topologicalinconsistencies. 2.2.Topology Originally and in the wider sense the term topology referred to the branch of mathematics dealing with the properties of geometric figures that are not subject to changeundergeometrictransformations(MAGNUSZEWSKI,1999).However,inthefield ofGeographicInformationSystems(GIS)topologyisunderstoodasadescriptionofthe spatial relationships between adjacent or located near each other objects (THEOBALD, 2001). Topological consistency describes the trustworthiness of relationships between the datasetsegments(JOKSIĆandBAJAT,2004).Theserelationstypicallyinvolvespatialdata inconsistencies such as incorrect line intersections, polygons not properly closed, duplicatelinesorboundaries,orgapsinlines.Itdealswiththestructuralintegrityofa given data set based on formal framework for modelling of spatial data and relationships among objects. These types of errors must be corrected to avoid incompletefeaturesandtoensuredataintegrity. Unites States Census Bureau was a pioneer in the field of application of topologyto reduce the number of errors made inthe process ofcollecting largedata sets at the turn of sixties and seventies of the last century. Environmental Systems Research Institute (ESRI) has also made major achievements in the field of topology applications. In the early eighties they developed Coverage format allowing for the storage of large data sets and efficient spatial analyses taking into account limited capacitiesofdatastoragemediaandrelativelylowprocessingcapabilityofcomputers in those days (ESRI, 2005). The operation principle of this format was to store only information about the components of objects and their relationships (topology) and constructionoftheseobjects“on‐demand”forthepurposeofpresentationoranalysis. Thus,storingdatainthisformatwassynonymouswiththeverificationoftopological correctness.Itassumesthattheobjectsarelocatedontheaplaneandarerepresented by nodes (zero‐dimensional), edges, also called arcs (one‐dimensional) and polygons (two‐dimensional). Because edges are located on aplane they are not allowed to intersect,buttheyhavetotoucheachotherattheirends,representedbynodes,finally forming non‐overlapping and filling the entire area of polygons (ZADRAVEC and ŽALIK, 2009). The development of computer hardware in terms of processing power and datastoragecapacityintheninetiesofthetwentiethcenturyresultedinthechangeof aviewonhowtostorethevectordata.Itturnedoutthatitwaseasiertostoreobjects 24 in the “ready” form of so‐called simple features (OPEN GEOSPATIAL CONSORTIUM, 2011). This is particularly important in the case of polygons, because it resulted in redundant double storage of the same boundary points. Shapefile format was then created(ESRI,1998).Thisapproachtostorageofsimpleobjectswasalsousedatthe end of this decade, when the first attempts to store geographic data (both geometry andattribute) in relationaldatabase structures were undertaken (ZEILER, 1999). This way storage of topology together with the data was abandoned. It turned out easier and more efficient to generate or check the topology “on‐demand” than to create objectsbythatmeans. 2.3.Theprocedure Theaboveconsiderationsallowtoproposeastep‐by‐stepprocedurefordatatransfer fromCADtoGISandsubsequentconstructionofpolygonsfromasetoflinesegments or polylines. Particular emphasis is placed on the possibility to use free software for this purpose (MICHALAK, 2007). Issues described here were previously described in variouspublications,forexample(ALRAWASHDEHBALQIESSADOUNandALFUKARA,2012), (ŽALIK,1999),butsofarnoonehasproposedacomprehensiveanddetailedsolution tothisproblem. Interestedreaderwillfindheresomekindofguide,butitdoesnotcoverevery technicalissueandlikelysituationinCADtoGIStransfer.Theproposedprocedureis comprisedofthefollowingsteps: Step1.CADdataimport WhenconvertingCADdrawings,itisnecessarytobeabletoisolateobjectsthatcanbe candidates for GIS features. If building of polygons is anticipated, it is necessary to obtaintheinformationabouttheirboundariesandidentifiers.CADdataiscommonly groupedbyCADlayernameorCADgraphicpropertiessuchascolourorlinestyle.GIS software has several methods for categorizing and isolating data contained in CAD files.ThekeytosuccessfuluseofCADdataasGISfeaturesistheabilitytouniquelyand consistentlycategorizedifferentobjectswithintheCADfilethatcanbeusedwithinGIS layers. Althoughthereareseveralstandardsonhowthelayersshouldbeorganized, mostlyinarchitecturaldesign(DAVIES,2011),(INTERNATIONALORGANIZATIONFOR STANDARDIZATION, 1998b) and (NATIONAL INSTITUTE OF BUILDING SCIENCES, 2014),CADapplicationsdonotforceuserstofollowanyofthesestandards.Therefore it is possible to find CAD drawings where the information regarding polygon boundariesandtheiridentifiersismixedwithotherdataordividedintoseverallayers. Thesecondsituationiseasilysolvedbymixingthecontentsofthelayersthatkeepthe desired information, whereas the first situation is still an open problem, because typicallythereisnoadditionaldata(apartfromlineattributeslikecolourorthickness) to support automatic extraction of primitives from the layers without involving the user. OncethecorrectfeatureshavebeensuccessfullyidentifiedinCADfileGIScan directly use the geometry of CAD objects as the GIS feature geometry. GIS uses the geometric entity type as the primary organization tool. When a CAD drawing is imported into GIS, it interprets all elements into the three primitive geometric GIS features:points,linesandpolygons.Theircharacteristicssuchaslayername,colour,or line style are stored in individual columns of attribute table created specifically for 25 them.Onthisbasis,anattributequeryutilizinganyoftheCADgraphicpropertiescan beusedtofurtherisolateessentialobjectswithinaCADfile. Step2.Detectionoflineinconsistencies Beforerunningthepolygonconstructiontool,allinconsistenciesattheinputdatahave to be eliminated. Because the user of the CAD software does not need to follow any otherlimitsthanacorrectvisualeffect,coordinateandtopologyerrorsmayoccur. Topological errors exist due to violation of predefined topology rules. The mostcommontopologyerrorsinmapdatainclude(SEHRAetal.,2014): Intersections: twolinesegmentsintersectatexactlyonepoint–thissituationisthemost common onelineonlytouchestheother,notactuallyintersectingit self‐intersection,whichisaspecialcase Danglingnodes(lineends)orlines: undershoots(linesbeingtooshort) overshoots(linesbeingtoolong),whichinspecificcasescanalsoresultin creationofintersectionerrors Duplicatelines: twolinesegmentscompletelyoverlap twolinesegmentsoverlappartially Lines,whichdonotcreateaborderbetweentwopolygons(thesamepolygonis ontheirbothsides). Step3.Correctionofdetectedinconsistencies Automaticcorrectionofdetectederrorsaregenerallynotrecommended(ESRI,2004). Instead, a more controlled method of fixing any errors should be established rather thanrelyingontheautomatedsnappingthatoccurswhenfeaturesaresnappedusing theclustertolerance.Usingtheclustertolerancetomodifyormitigategeometryerrors does not provide adequate control that one might want in the creation of polygons from lines. Manual editing tools should be considered to fix errors when accuracy is aconcern.Therearecasesinwhichtheautomaticactionmaycauseworseningofthe situationratherthanitsimprovement.ŽALIK(1999)presentssomesuchexamples.In hisopinion,problemsmayalsoresultfromthewrongorderofcorrectionofindividual topologicalerrors. Beforetheediting,itisnecessaryfirsttospecifywhichlayerwillbeedited,i.e. to start so called “Editing session”. It is important to mention that usually editing is possibleonlyononelayer. Theaforementionedtypesoferrorsshouldbecorrectedasfollows: Twointersectinglinesshouldbereplacedwiththreeorfourlinestouchingeach otherattheirends. Undershoots (lines being too short) should be extended, whereas overshoots (linesbeingtoolong)shouldbeshortened,withoutforgettingaboutcorrection ofthepossibleintersectionerrors. One of the two overlapping (identical) lines must be removed. If the lines overlap only partially, the common fragments should be separated from both linesandoneofthemremoved. Lines,whichdonotcreateaborderbetweentwopolygons(thesamepolygonis ontheirbothsides)havetoberemoved. 26 Step4.Creationoftemporarypolygonsonlyonthebasisoflines Afterobtainingcorrectlines,polygonsshouldbecreatedusingtoolavailableinchosen GISsoftware. Step5.Determinationofthenumberofpointsinpolygons GIS software is usually equipped with Spatial join tool which purpose is to transfer attributesfromonefeaturetoanotherbasedonthespatialrelationship.Inadditionto the conventional use this tool often has an additional option, which allows to determinestatisticalparameterssuchastotal,averageandstandarddeviationforthe selected attribute in case of multiple Join Features inside Target Features. Kind of aside effect of this action is to create an additional column in the attribute table indicatinghowmanyjoinfeaturesmatcheachtargetfeature. Step6.Correctionofpointerrors Inthecaseofmorethanonepointinthepolygonuserneedstodeterminewhichoneis correct.Ifthepointismissingthenuserhastoobtaininformationfromanadditional sourcewhatattributesitshouldhave.Onlyahumancanperformsuchactivities.They cannot be automated inany way. At mostthematic (choropleth)mapcan be created, where polygons are shaded or patterned in proportion to the number of internal points. Step7.Creationoffinalpolygons Afterobtainingcorrectpolygonsandpointsitisnecessarytoincludetheattributesof thepointfeaturesasattributesonthenewpolygons.DescribedaboveSpatialjoincan beusedforthispurpose 2.4.Freesoftware The development offreeandopensource softwarehas experienced a boost over the lastfewyears.ThevarietyofFree/LibreandOpenSourceSoftware(FLOSS)thatcanbe foundondesktopcomputersrangesfromwordprocessors(e.g.LibreOffice),through web browsers (e.g. Mozilla Firefox) to vector drawing (e.g. Inkscape). In the GIS domain,thewidespreaduseofFLOSSisapparentaswell(STEINIGERandBOCHER,2009). ThreeFLOSSGIShavebeenselected,testedandanalyzedregardingtheircapabilitiesto be used as tools for spatial data conversion from CAD drawings. Vector editing functionstocreatepolygons,topologyvalidationandsupportforcommonvectorand CADdataformatsareconsideredessentialcharacteristicsofGISdesktopsoftwareused for this task. These and other characteristics are compared for QGIS, gvSIG and OpenJUMP. They have been selected out of six which have been introduced and comparedin(PIEPER ESPADA,2010).Theyareconsideredbytheauthorofthispaperas someofthemostadvancedandsophisticatedFLOSSGIScurrentlyavailable. 2.4.1.QGIS QGISmightbethebestknownFLOSSGISsoftware,whichownsoneofthelargestuser communities. It is a user friendly desktop GIS which can be used to manage, edit, visualize, analyze data and compose printable maps (QGIS DEVELOPMENT TEAM, 2015). The programming language is C++ and GUI functionality is based on the Qt4 library.Itsdevelopmentstartedin2002andtheoriginalaimwastoprovideaneasyto use and fast geographic data viewer for Linux‐based systems. However, as the QGIS 27 project evolved the idea emerged to use QGIS as a simple Graphical User Interface (GUI)forGRASS.TheQGISdevelopmentteamreacheditsinitialobjectivesandstarted workingtoextendthefunctionalitybeyonddataviewing.NowQGISincludespowerful analyticalfunctionalitythroughintegrationwithSAGA,OTB,MMGIS,fToolsandGRASS. ItrunsonLinux,Unix,MacOSX,andWindowsandsupportsnumerousvector,raster anddatabaseformatsaswellasdatadeliveredfromwebservers.Inparticularitcan readCADfiles:DXFandDGN.Anattractivefeatureforotherprogrammersistheoption towriteQGISextensions(calledplug‐ins)inPythontoaddcustomfunctionality. 2.4.2.gvSIGCE gvSIG(GeneralitatValencianaSistemasdeInformaciónGeográfica)projecthas beenfoundedbytheRegionalCouncilforInfrastructuresandTransportation(CIT)of Valencia (Spain) to produce software of similar functionality as ESRI’s ArcView for municipalauthorities(ANGUIX,DÍAZ,2008).Thegoalsoftheprojectaretoprovidean open source tool that utilizes open standards and is platform independent. gvSIG wrapsanumberoftheJavalibraries,includingGeoToolsandJTS.Oneofthegoalswas unifyingCADandGISworldsthroughintegrationofCADtoolswithinFLOSSGIStoget ridoftheproprietarysoftwareandlicensecosts.Thegoaltoprovidesoftwarewiththe functionalityofESRI’sArcView(3.x)hasalmostbeenreached,and,insomeaspects,is exceeded. gvSIG is known for its user‐friendly interface and being able to access all commonvectorandrasterformats.gvSIGisaveryusefulGISproductwithextensive vectoreditingfunctions. ThedevelopmentofgvSIGstartedin2003andwasledbythecompanyIVER S.A. (Spain). Currently project is managed by international non‐profit organization gvSIG Association. In 2011 a group of programmers unhappy with direction of program development forked gvSIG creating gvSIG Community Edition (CE). This version is characterized by rich set of topology tools that can be used to validate geometry of vector layers. Advanced analytical functionality is provided by powerful SEXTANTE library (OLAYA, 2010), offering currently more than 300 geoalgorithms. The SEXTANTE project has successfully developed a Java‐based framework for the analysis and processing of vector and raster data. The framework also includes graphical components that enable the creation of workflows similar to the ESRI’s ModelBuilder. 2.4.3.OpenJUMP The JUMP (JAVA Unified Mapping Platform) project was founded in 2002 by a consortium of two Canadian provincial ministries and two companies. The objective was to develop a GIS specifically for data editing and data conflation (CICHOCIŃSKI, 2007).JUMPwasdesignedtobeagenericandpluggableenvironmentintowhichthe complexalgorithmsrequiredforspatialdataconflationcouldbeembedded. Spatialdataconflationusuallyrequires ahumaninputelement,andasaresultJUMP was built with anumber of generic user interface and GIS viewer features. A forerunnerandpartofthatprojectwasalsotheenhancementofthegeometrylibrary JavaTopologySuite(JTS),whichattemptstoimplementtheOpenGISSimpleFeatures Specification(SFS)(OPENGEOSPATIALCONSORTIUM,2011)forgeometricoperations asaccuratelyaspossible.InsomecasestheSFSisunclearoromitsaspecification.In this case JTS attempts to choose a reasonable and consistent alternative. JTS is intended to be used in the development of applications that support validation, cleaning,integrationandqueryingofspatialdatasets(VIVIDSOLUTIONS,2003).When 28 JUMP development activities almost stopped in 2004 due to the loss of financial support, a group of volunteers founded the JUMP‐Pilot Project and continued the software development under the name OpenJUMP. They quickly added multilingual supportandnumeroussmallinterfaceimprovementsaswellassomeanalyticalplug‐ ins. The initial application focus on data conflation and editing is responsible for the fact that the JUMP GIS family has a strong focus on vector data creation and analysis(offeringgoodtopologyvalidationtoolsandvectoreditingfunctions),whileit providesnorasteranalysisfunctionality.OnlyrecentlyOpenJUMPhasbeenintegrated withSEXTANTE(alsousedbygvSIG),whichaddsextensiverasteranalysistoolstothe software. 2.5.Implementationoftheprocedureinfeaturedprograms Thesmallfragmentofcadastralmap,covering31parcels,wasusedasthesampledata. Apart from boundaries and designations of land use forms, ALE.DXF file contained lines representing boundaries of parcels on GPE layer and texts representing parcel numbers on GNE_R layer. This drawing contained examples of all of the aforementioned topological errors that potentially could interfere with the constructionofcorrectpolygons.DXFdrawingformatwasusedduetothefactthatnot alloffeaturedprogramssupportallCADformats,andDXFformatcanbeconsideredas the most versatile and the simplest. It has some restrictions on the possibility of storingmoreadvancedelements,however,inthecaseofmapdataitwouldnotmatter asgenerallyonlylines(polylines)andtextsareused.TheDXFfilehasbecomethede factointermediatefileformatforvectordata.DXFfilesaresupportedbyawidevariety ofvector‐basedgeometriceditingsoftware.TheDXFfileisgenerallyanASCIIfile. 2.5.1.OpenJUMP OpenJUMPisabletoreadonlyDXFfiles.Afterloadingthewholedrawingispresented in its entirety as one layer, in one colour. The attribute table indicates the geometry typeofeachfeature–lineorpoint(convertedfromtext),respectively.Additionallyit contains universal columns FID (feature identifier), LAYER, LTYPE (line type), ELEVATION, THICKNESS, COLOR, TEXT, TEXT_HEIGHT, TEXT_ROTATION, TEXT_STYLE. On the basis of the content of the attribute table, selection of required drawing elements can be made using Attribute query tool (Fig. 4). OpenJUMP allows immediatecreationofanewlayerfortheresults.Itisuserresponsibilitytosavesuch layer,forinstanceinpopularshapefileformat. Topologicalcorrectnessisverifiedintwoconsecutivesteps.Thefirstmaybebutdoes not have to be, Validate Selected Layers (Fig. 5). This allows to check basic topology andthatgeometriesaresimple(donotself‐intersect). 29 Fig.4.AttributequerytoolinOpenJUMP. Source:CICHOCIŃSKIownstudy. Fig.5.ValidateSelectedLayerstoolinOpenJUMP. Source:CICHOCIŃSKIownstudy. However,theultimatetestofthecorrectnessofthebordersisthecreationof polygons using Polygonize tool (Fig. 6). Selecting the option Node input before polygonizing allows to automatically split intersecting lines into parts, touching each other at the ends. The results of this operation are polygons which could be created andtwotypesoflinesthatdonotformtheboundariesofpolygons. 30 Danglinglines(atleastoneoftheirendsarenotincontactwithanotherline) are presented in red (although dangling ends are not indicated), while blue colour represents lines, called Cuts, that although linked to other, do not create a border betweentwopolygons(thesamepolygonisontheirbothsides).Thereforeitiswritten above, that the first step does not have to be conducted because errors such as self‐ intersecting lines and overlapping lines does not interfere with the Polygonize tool (theyareautomaticallycorrected). OpenJUMP has many editing tools collected in Editing Toolbox, which allow manual correction of signalled errors. Their description, however, goes (for each of the presentedprograms)outsidethescopeofthistext. Fig.6.PolygonizetoolinOpenJUMP. Source:CICHOCIŃSKIownstudy. Fig.7.JoinAttributesSpatiallytoolinOpenJUMP. Source:CICHOCIŃSKIownstudy. 31 Fig.8.SpatialJointoolinOpenJUMP. Source:CICHOCIŃSKIownstudy. Afterobtainingcorrectpolygonsitisnecessarytoassignthemattributesofthe points that are inside. Such operation is unambiguous only when there is only one pointinonepolygon.Tocheckifthisisthecase,JoinAttributesSpatiallytoolcanbe usedwithparameterssetaspresentedinFig.7.Therequirementforthismechanism tooperateproperlyisthattheremustbeatleastonecolumnofnumerictype(integer, double)inattributetable(althoughitcanbeempty).InthiscasecolumnCOLOURwas used. The result is new polygon layer, with column named COUNT in attribute table, which provides information about number of points in every polygon. One (1) is the desiredvalue,zero(0)indicatesalackofapoint,whiletwo(2)ormoreistheevidence of excess. At this stage again human intervention is required, who has to verify and correct the excess or lack of points. In order to facilitate this task, the resulting polygonscanbepresentedintheformofthematicmap(choroplethmap),whereareas are shaded or patterned in proportion to the number of internal points. After correctingpointsfinalpolygons(parcels)areobtainedbytransferringattributesfrom points to polygons using Spatial Join command (Fig. 8). It is important to effectively verify the number of points in polygons, because every additional point inside generates additional resulting polygon, and the lack of a point in the polygon is synonymouswithalackoftheresultingpolygon. 2.5.2.GvSIGCE The gvSIG CE recognizes two CAD file formats: DXF and DGN. After loading data the programtriestopresentthemintheformthemostsimilartotheforminwhichthey could be seen in CAD. It uses for this purpose properties of the graphical elements storedinthecolumnsoftheattributetable:ID,FShape(inthiscasecontainingvalues FPolyline2D and FPoint2D), Entity (values Line and Text), Layer, Colour, Elevation, Thickness, Text, HeightText, RotationText. In particular, it uses the content of the Colour column to specify colour of the elements and labels points originating from texts using content of the Text column, utilizing also parameters stored in columns HeightText and RotationText. However, probably because of an error, it does not presenttextsinappropriatecolours,althoughaccordingtolayerpropertiesitshould. 32 Fig.9.SelectionQuerytoolingvSIGCE. Source:CICHOCIŃSKIownstudy. Onthebasisofthecontentoftheattributetable,selectionofneededdrawing elementscanbemade,usingSelectionQuerytool.Itopensthewizard,whichsimplifies the processof query building by indicatingappropriate columnsanddisplayingtheir content (Fig. 9). Launching the query by pressing New Selection button causes highlightingofappropriateelements,whichcanthenbesavedtoanewdataset,using ExportDataAsoption.BecausegvSIGdoesnotanalyzethegeometrytypeofselected elements,itactuallysaves3files,automaticallygivingthemsuffixesindicatingwhether theycontainpoints,linesorpolygons.Incaseofselectionofparcelboundariestheyare saved to file with “line” suffix. Similarly, points representing texts are saved in a file with“point”suffix.BothinquerywizardandinthenextstepitcanbeseenthatgvSIG user interface is inspired by solutions from ESRI, ArcView producer. Checking the correctness of the course and the relationships between individual segments of bordersconsistsincreatingtopology. In the subsequent windows presented by the wizard one need to specify the layersthatwillbeincludedinthetopology(theremaybemorethanone)(Fig.10),and providethetopologicalrulestobeverified.Incaseoflinestheyarerespectively(Fig. 11): 33 Fig.10.LayersthatwillbeincludedinthetopologyingvSIGCE. Source:CICHOCIŃSKIownstudy. Fig.11.TopologicalrulestobeverifiedingvSIGCE. Source:CICHOCIŃSKIownstudy. All geometries of A must pass JTS validation – Geometries must meet Simple FeatureSpecificationrequirements. 34 NogeometryofAmayhaveduplicatecoordinates–Verticesofgeometriesmust nothaveidenticalcoordinates. No line of A may self‐intersect – Lines in the same layer must not cross or overlapthemselves.Theyareallowedtointersectandoverlapotherlines. All line geometries of A must be free of dangling nodes – No dangling lines allowed.Thelastvertexofalinemusttouchasegmentofthesameoranother line. Layer A must not contain any duplicate geometries – No duplicate geometries allowedinlayer. It should be noted that none of the available rules does allow for analysis of the presenceofintersectionsbetweentwodifferentlines. Thenextstepistopologyvalidation,whichresultsindetectingandflaggingup placesinwhichtherulesareviolated.AsexpectedgvSIGhasdetecteddanglingnodes, duplicate geometries and self‐intersections, but unfortunately, just as one could suspectithasnotsignalledintersectionerrors.Therefore,itappearsthattheprocess of building the topology and correcting found errors must be preceded by launching geoprocessing tool Clean (Fig. 12). By using a minimum tolerance value operation of thistoolshouldbelimitedtocorrectionofintersectionerrors. Fig.12.GeoprocessingtoolCleaningvSIGCE. Source:CICHOCIŃSKIownstudy. 35 Fig.13.GeoprocessingtoolBuildpolygonsingvSIGCE. Source:CICHOCIŃSKIownstudy. In most cases, this tool indeed has worked as expected, but has not worked properly in places where one line only touches the other, not actually intersecting it. Therefore, Build polygons tool (Fig. 13) has been eventually used, acting in a similar manner to the previously presented Polygonize tool from OpenJUMP. The only differenceinfavourofgvSIGissignallingnotonlydanglinglines,butalsotheirends– danglingnodes. Fig.14.SpatialjointoolingvSIGCE. Source:CICHOCIŃSKIownstudy. 36 Aftercorrectionofdetectederrorsandre‐constructionofpolygonsvalidation ofpointsrepresentingparcelnumberscanbegin.Spatialjointoolcanbeusedforthis purpose (Fig. 14). This tool usually transfers attribute table field values from an overlay layer to an input layer. But if Transfer from nearest feature option is not selected,thenNUM_RELAcolumnofoutputlayerattributetablereceivesthenumber ofoverlaylayerobjectscontainedinsideeveryinputlayerobject.JustasinOpenJUMP thisinformationcanbeusedtoverifyandmanuallycorrectexcessorlackofpoints. InthelaststepSpatialjointoolisrunagain,butthistimeactuallytotransfers attributetablefieldvaluesfromanoverlaylayertoaninputlayer.Theresultsarefinal polygons(parcels)withattributetableenrichedwithparcelnumbers. 2.5.3.QGIS After opening CAD file (DXF or DGN) in QGIS user can select one or more geometry typesthatshewantstoload.Inthiscasetherearetwoofthem:PointandLineString (Fig.15).TheyareloadedrespectivelyasentitiesPointandentitiesLineStringlayers. Theirattributetablescontainonlytwousablecolumns:LayerandText.Onthisbasis, neededelementscanbeselected.ItcanbedoneusingExtractbyattributetool(Fig.16) accessible in Processing Toolbox. Like OpenJUMP, QGIS is equipped with Polygonize tool, but it has limited functionality: it does not indicate anomalies detected in the courseofbuildingpolygons.Inparticular,onetypeoferrorisrelevant:danglinglines. Other errors: overlapping (duplicate) lines and intersections do not interfere are automaticallycorrected.Tocontrolthecorrectnessofrelationshipsbetweengeometric elementsinQGISthereis,installedbydefault,TopologyCheckerplug‐inanditcanbe usedtodetectdanglinglines.Appropriaterulemustbespecifiedforthatpurpose(Fig. 17) and then validated (Fig. 18). Detected errors can then be indicated on the list, which causes them to automatically highlight on themapand thus simplifies manual correction. After obtaining correct polygons one can proceed to check points correspondingtotextsinCADdrawing.Thenumberofpointsineachpolygoncanbe exploredusingPointsinPolygontool(Fig.19).Afterdeterminingthecorrectnumber of points, point attributes can be transferred to the surrounding polygons using Join AttributesbyLocationtool(Fig.20)therebyobtainingfinalpolygons(parcels). Fig.15.GeometrytypesavailabletoloadinQGIS. Source:CICHOCIŃSKIownstudy. 37 Fig.16.ExtractbyattributetoolinQGIS. Source:CICHOCIŃSKIownstudy. Fig.17.TopologyRuleSettingsinTopologyCheckerplugininQGIS. Source:CICHOCIŃSKIownstudy. 38 Fig.18.TopologyCheckerplugininQGIS. Source:CICHOCIŃSKIownstudy. Fig.19.PointsinPolygontoolinQGIS. Source:CICHOCIŃSKIownstudy. 39 Fig.20.JoinAttributesbyLocationtoolinQGIS. Source:CICHOCIŃSKIownstudy. 2.6.Conclusions Conductedresearchshowsthatthereexistsagroupoffreesoftwaretoolsthatallowto perform the entire procedure of CAD data import, and then convert them into full‐ fledgedGISdata.Somedifficultymayresultinthefactthatcurrentlyfreesoftwaredo notreadDWGfiles,butitisusuallypossibletomakeearlierconversiontoDXFformat. Not all tools worked as expected, but every time they could be replaced by others, which use was not originally planned. In each of the programs only one path leadingtothegoalwasselected,buttherewereotherpossiblesolutions.Particularly noteworthy are extensive capabilities of GRASS GIS in the area of auto‐correction of topological errors. These tools can be launched from all the analyzed programs and, althoughauto‐correctionisgenerallynotrecommended,situationscouldbeimagined in which the efficiency of data correction is more important than the quality of the result. Itwasnotedthatthefinalresultandtheamountofworkdesignedtoachieveit dependsnotonlyonthecapabilitiesofthesoftware,butalsoonthequalityofacquired data. Therefore, obtained research results allow to formulate guidelines for persons creatingCADdrawingsintendedforuseinGISsoftware. 40 ThesimplestsuggestionformakingCADdatamoreusefulasGIScontentisto implement and adhere to aCAD layering standard. Implementing a CAD standard improvesthequalityoftheCADdataanditsusefulnessasGIScontent.ACADstandard is the closest thing in CAD to a GIS database schema. Being able to reliably identify differentobjectcategoriesbylayernamewillensurethatvariousobjectcategoriescan consistentlybeidentifiedinCADfiles.Thisisparticularlyimportantifonewishtouse CADdrawingsinQGIS,becausethissoftwareisabletouseonlythisproperty. ThecloseraCADfile'sdataconstructsaretothoseofGISsoftware'sfeatures, theeasierandmoreusefulthatgeometrywillbeforuseinGIS.Notonlytheschematic, pictorial representation of the data should be considered but also the geometric interpretation of connectivity when the drawing is used as a GIS data source. For example, there should be no lines stopping short of connecting to make, for cartographicreasons,roomforthenodesymbol. Usingmorethanonepieceoftextinsideapolygontodenoteaparcelnumber should also be avoided, at least in situations when these text object are on the same layer, have the same colour and text style, and have no other distinguishing characteristics. 41 3. UPDATING OF LOCAL DATABASES AT THE COMMUNE LEVELUSINGGPSTOOLS Today, the administration and space management processes are carried out using information technology. Previous work tool in this direction were thematic cartographytoolsinthetraditionalattitude.Theworkconsistedlargelyonthemanual drawingofthematicmaps,whichwerelaterusedforotherbranchesstudies.Thescope of the elaborated data and their accuracy has always depended on specifics and the methodofobtainingofthebaselinedata.Alongwiththedevelopmentofinformation technologies using geolocation and spatial attributes also expectations towards their creators and designers increased. They are mainly focused on the effective use of geomatic methods to acquire and develop spatial data in order to obtain reliable information. To meet this requirement it was necessary to create tools ensuring adequate accuracy and speed of action. This solution proved to be computer Geographical Information Systems (GIS), also called spatial information systems. According to (GOTLIB et al., 2007) GIS provides collecting and advanced analysis processesofgeographicdataandtheirattributes.Inthebroadrangeanessentialfactor thatcontributestothedevelopmentofspatialinformationsystemsisagroupofpeople directlycreatingandusingthissystem,aswellastheorganizational,technologicaland legal procedures in force, enabling its operation. The potential of GIS technology is used in many sectors including the planning, administration, monitoring of pollution, locationsystems,healthcare,andmanyothers. The Information Systems discipline is 50 years old, in Australia, in Scandinavia,theU.S.A.,theU.K.andGermany(CLARK,2006).InPoland,thebeginnings of information systems date back to the eighties of the twentieth century, where the firstattemptstocreatethemusingtheinformationtechnologyappeared.Earlierthey were replaced by the cartographic and descriptive presentations in classical forms ‐ mapsandtabulardatasets.Withthepassageofyearstheneedhasincreasedforaccess toaccurateandcompleteinformation,alsoacquiredatarapidpace.Informationplays an important role in every area of modern life. The pace of life in today's society generates the need to create mechanisms for access to information in a quickly way andunlimitedbyplaceandtime.Thevalueofinformationdependsonitscredibility, up to date character, the speed of access, the method of sharing and the form of presentation. GeographicInformationSystem(GIS)isusedasthenameofthefielddealing with spatial information – geoinformation, and the methods and data processing techniqueswhichhavegeometriccharacter,oftenreferredtoasspatial.Thesemethods are referred to in this paper as GIS tools. These relate to the acquisition, collecting, verifying,integration,analysis,transferandsharingofspatialdatainthebroadsenseit includes methods and technical measures. (GAŹDZICKI, 2003) GIS is used to describe, explain and predict the spatial distribution of geographical phenomena. It provides both software as well as science sections, and the developed methodology to solve researchproblems.GISisaprovenmethodofspatialdataprocessing,providingtools such as cartometric measurements and spatial analysis. Scientific basis for GIS are developedbygeoinformatics,whichtakesadvantageofnewopportunitiesassociated with the development of computer networks. This system is strengthened in Poland duetothegrowingimportanceofspatialdataandworkedoutmethodsofanalysis. In the information systems field there is a great need for different theories. Theory Development can be performed in different ways – deductively and/or 42 inductively. Different approaches with their pros and cons for theory development exists.ACombinedapproach,whichbuildsoninductiveaswellasdeductivethinking, has been put forward – a Multi‐Grounded Theory approach. Important is the knowledge of the limitsofinformation systems: “Knowledge created within scientific disciplines are often codified and structured in theories. Information systems (IS) research,therearegrowingeffortsindevelopingtheories.Oneapproachoftentakenis touseanestablishedtheoryfromareferencedisciplineandredevelopandadaptitto theinformationsystemscontext”(LIND,2006). According to (SMYTH and GABLE, 2006) There is a body of knowledge that suggests that many of the characteristics of Information Systems are consistent with those observed across emerging disciplines in the early stages of their development. For example, in the early evolution of Management as a discipline, some of the characteristicsthatmanifestedthemselvesatthattimehavebeenseenmorerecently inthedevelopmentofInformationSystems. GIS tools enable acquisition and collection of data, their processing, analyze and elaboration of results in appropriate formats, useful for the systems of mass presentations (mapservers and geoservers) and convenient for users to interpret in the form of resulting numerical thematic maps. By combining the geometric characteristicsandlocationoftheobjectwiththeirdescriptionincontrasttoanalogue maps,GISmapscontainalargeamountofinformation.Theversatilityandusefulness of GIS tools caused that they are used in many areas. The subject of the paper is to show the usefulness of spatial information systems, created in accordance with the requirements of the GIS in order to develop local databases for thepurposes of local governmentadministrationtasksinneighbouringcommunes.Creationofsuchsetsof informationhaspracticaljustificationthankstotheconsistencyofdecision‐makingby units atthe same level ofadministration. This solution based on the law (Act, 2010), ensurestheimplementationofthemainobjectivesofspatialpolicy.Currently,apartof the decisions taken by local authorities is based on spatial information of GIS databases,whichdefinethelocationofthephenomenonortheobjecttogetherwithits description. Thanks to the content of local spatial data sets some of the communes have complex characteristics of their land and use it in the process of analyzing, monitoring,management,localplanning.Thisisagooddirectionofchanges,whatcan be a sign of the development of social awareness in the time of the necessity of obtaining complete and recent data in a short time. Modern information and communicationmethodscangreatlysimplifytheuseoflargeamountsofinformation. Asanexamplecanservetheprocedurefortheselectionoflandforinvestment,which usingGIStoolscantakejustafewminutes(BAJTEK,2007).Thesesystemscanbeused anywherewhereoneofthecharacteristicsofanobjectisitsgeographicallocation.The creationoflocaldatabasesisapartofthecomplexprocessofintegrationofdatabases atthedistrictandstatelevels.ThankstothecommonuseofInternetnetworksthere are new opportunities for obtaining spatial information. Unfortunately, this fact also carriescertainrisksregardingtheprotectionofsuchinformation. In turn ‐ integration in the network of units and institutions having data results in the determination of the responsibility for the completeness, validity and availability of data by the institutions and persons concerned. The Directive of the European Parliament and of the Council of the European Union ‐INSPIRE (INSPIRE Infrastructure for Spatial Information in Europe) deals with it, establishing the Infrastructure for Spatial Information in the European Community. It aims to build aspatial data infrastructure enabling the sharing of environmental spatial data by 43 public sector organizations and facilitating of public access to spatial information in Europe(DIRECTIVE,2007). InPoland,onadministrativelevelsofcommunes,bindingrulesregardingthe spatialmanagementareTheLocalSpatialDevelopmentPlans.Theydetermine,among others, trends of changes in allocation of land, housing development, and the developmentoftechnicalinfrastructure.Toaccomplishthis,communesaremoreand more often analyzing the social phenomena, which distribution in space is extremely important for sustainable development. Spatial management is therefore one of the areas of local government activity, which requires strong support from GIS tools. Because this opens up the way not only to support the planning process, but also to performingofadvancedspatialanalyses.GIStoolsenableprovidinginformationabout theproposedplanstopotentialinvestorsandlocalcommunities,activelycontributing tobuildingtheinformationsociety. In thispaper, theauthorspresenta practicalaspectofspatial datacollection for the greation of local spatial databases, using the most recent measurement technologyandGISinformatictools. Inthespecialistliterature,accordingto(GOTLIBetal.,2007)wecanreadthat „Geoinformation systems allow to record spatial data in a logical structure, their comprehensiveanalysisandvisualization.Theyarealsousedtodescribe,explainand predict the spatial distribution of geographical phenomena. The GIS system consists mainly ofappropriate software and hardware, collected data,applied algorithms and proceduresforprocessingandsharingofinformation.” Thesubjectoftheworkincludesthefollowingtopics: 1. Description and brief characteristics of detailed data collection methodfortheneedsoflocaldatabasestogetherwithanassessment oftheiraccuracy(basematerials–EGiB(cadastre)maps,GPS/GNSS tools,statisticaldataonthebasisofCentralStatisticalOfficeandother resources); 2. DescriptionofthemethodologyofcreatingoftheSpatialInformation Systems (SIP) elements in the phase of office works of spatial data processingintheprogramQGIS; 3. Presentation of the effect of data processing in selected areas of the elaboration of SIP for selected communes in accordance with their expectationsandlocalneeds; 4. Componentsofdevelopedspatialinformationsystems: mapofeconomicactivityofthecommune;targetdesignationanduse: thedevelopmentoftheservicesector,promotionofthecommuneas aunitoflocalgovernment, mapofthedistributionandintensityofbuilding, identification of fees impact areas due to commune investment activitiesonthevalueofagivenproperty, communication network update (stops, local connections, exits and intersectionsofalowercategoryroads), update of maps of infrastructural networks, including water and fire fittings (fire hydrants, wells) possibilities of using in the local fire services, surveyofthestatusofselectedobjects(buildings)andgivingthemthe appropriate characteristics relating to the degree of their technical wear. 44 3.1.Observationsandmethods The following section presents the methodology of creation and visualization of GIS components created for the selected objects. They are a few communes of the Małopolskie Voivodship in Poland. This methodology has been developed by the Authors of the publication and used partly for BSc and MSc works shown in the references. In addition, most of the elements of GIS has been implemented in the respective communes and can be used at the moment as the basis of planning activities. In the whole elaboration the base materials were used (maps of Land and Buildings Cadastre (EGiB) in the raster and vector form, data of Geodetic Register of Infrastructure Networks (GESUT), Local Spatial Development Plans (MPZP) and others) obtained from local geodetic resources. Using integrated measurement techniques commonly applied in geodesy, these materials have been updated, and in further technical processing were used as a new sources of information for further analysisinthecommunesareas.Alltheworkwasdividedintothesurveyingpartand the office processing of data. In the surveying part both classic and satellite measurement techniques and GPS instruments were used to update the content of selected elements of thematic maps, such as: location selected groups of buildings, busesforpublictransportation,publicutilitiesobjects.Theinformationobtainedinthe form of files in gpx or shapefile formats were properly processed and converted for further technical elaboration and processing on layers with giving them the relevant references. During the realization of the elaboration object a key role played GIS tools, enriching the thematic cartography methods and significantly shortening time of analyzes development of the phenomena and processes in the areas of communes. Theymadeitpossibletocarryoutspatialanalysisandvisualizationofthefinalresult in the form of maps. Analysis of the spatial data is the essence of GIS, it helps to discover the rules, trends or anomalies in the areas of research, which could not be identifiedbystatisticalanalysisortheuseofthematiccartographymethods. Inthedeskjobdevelopmentofdata,digitalelevationmodels(DEM)wereused fortheelaborationofthecharacteristicsvolatilitymapsintherangeoftheresearch.In addition,theimageofbasicandcadastralmapwasused,havinggeoreferencegivenin theETRSsystem:Poland2000‐EPSG2178. Input materials, obtained from District Geodetic Documentation Centre in Krakówandlocallyappropriate,withintheareaofdevelopment,TownandCommune Councils were raster layers in the GeoTIF format. They contained information concerningthethematicofpointobjects,linesandsurfaces,concerning: cadastralobjectsfromtheEGiBmaps,administrativebordersofcommunes dividedintocadastreprecincts,bordersofplots,locationofbuildings, GESUTnetworks(courseoflines,fittingsetc.), elementsofMPZPincommunes. Thesemapsrequiredinthefirstplaceupdateofthecontents.Forthispurpose, threetypesofhandheldGPSreceiverswereused:GPSmap76(GARMIN),GPSmap62st (GARMIN) and Nautiz X7. Manual GPS receivers have already been the subject of numerous publications, among others (KWINTA, 2010), (MIKA, 2011), (MIKA, 2014), (SIEJKA, 2006),(PLEWAKO,2010),(SIEJKA,2013).Theydescribedthebasicfeaturesand work modes, comparing and determining the accuracy of subsequent models of the GARMINfamilyanddemonstratingboththeadvantagesanddisadvantagesofworking with their use. In (PLEWAKO, 2010) it was concluded that: „The accuracy of handheld GPS signals receivers can be regarded as the same as the error (of determination with 45 theiruse)ofgeodeticpointpositionfortheIIorIIIclassofthenetwork.Accepting this criterionrepeatedly,indifferentregionsofthesouthernPolishandfordifferentreference systems, a systematic factor of significant size was observed to exist. Removal of such factor from the set of observations allows for a reduction in the value of the position error. This error is at the level of about ± 1.5 m for nearly optimal measurement conditions.Thisaccuracydropstoapproximately±3mfortheareawheretherearefew obstacles in the way of signals from satellites. When access to signals is limited by the highbuildings,denseforest,etc.theerrorincreasesto±10metersandmore.Accessto signals from EGNOS satellite system significantly improves and adds credibility to the measurement results.” In elaborations (MIKA, 2011), (MIKA, 2014) and (SZOSTAK et al. 2014) the ability of use of a wider range of handheld receivers than land or water navigation was also demonstrated. Fig. 21 shows the selected types of handheld GPS receivers,whichfunctionscanbeusedtosomegeodeticworks,althoughtheirprimary functionisnavigation. Fig.21.Nautizx7,GarminGPSmap62st,GarminGPSmap76 Source:http://www.trekkinn.com/outdoor‐gory/garmin‐gpsmap‐76/6633/p Source:http://www.smallgis.pl Fieldworks,usingGPSreceiversshowninFig.21consistedinthelocationof selected objects on the ground and saving their coordinates. Another element of the fieldworkswastogivelocalizedobjectsproperlypreparedcharacteristics(descriptive attributes). On the basis of field measurements of selected elements of map content recordedusingGPSdevices,ontheunderlayofvectorisedlandandbuildingscadastre maps, a thematic base map was created in a shapefile format using the QGIS free software. An important advantage of this software is the ability to use modular construction.Thesoftwarecomponentscanfunctioninitseparately,theycanalsobe combined.Fortheworkwereused,interalia,:modulesofdataimportfromtextfiles, transmissionofroutesandwaypointsfromtheGPSdevices,rasterscalibration,group statistics,geoprocessing,spatialqueriesandmultilayersystemconstruction. By adopting this methodology the system of spatial information for the selected communes of the Małopolskie Voivodship was created. It is currently being 46 used at the level of the tasks of commune as abase material for the decision‐making action. Inthefollowingfigurestheiconographicmaterialconcerningdevelopmentof SIPforselectedlocalgovernmentunits(communes)isshown. Inthefirstplace(Fig.22)thevectormapoftheselectedcommuneisshown.It servesasthecore(georeferencematerial)ofsubsequentlydevelopedthematiclayers. The commune was divided into zones to allow carrying outthe characteristics of the variabilityinafinitenumberofobjects. Fig.22.Municipalitieszonaldivision. Source:MIKAandSALATAownstudy. An example of such a study is shown in the following figure (Fig. 23), illustratingthebuildingintensityindifferentzones,usingthedasymetriccartogram. 47 Fig.23.Dasymetriccartogramofdevelopmentintensityinthemunicipalityarea. Source:MIKAandSALATAownstudy. The next step in the development of information system in the selected municipalitywastoillustratetheintensityandlocationoftheservicesector(MADRZYK, 2013). Spatial information systems within the scope of their activities include visualization of demographic phenomena and the attributes associated with running abusiness. In the services sector it makes possible to perform the analysis of the acquisition of potential customers and development of a strategy relating to competitive threats. Methods of analysis offered by the GIS are very useful in marketing research, because they allow among other things to select the optimal location of given objects, determination of an appropriate assortment for customers and also determination of the priorities for further development (URBAŃSKI, 1997). Economic activity is, therefore, an important element used in spatial planning and in determination of the development strategy of the commune, and also the entire country.InPoland,theNationalCourtRegisterissharingtheinformationonthisarea ofresearchthroughtheCourtandCommercialGazette,whichcollectsinformationon the business activities in the area, then files by codes of Polish Classification of Activities. In the above‐mentioned classification the economic activities are divided into21mainbranches.Eachofthemcontainssuccessivelyclass,thesubclassandthe clustering. In the era of globalization, when the dynamic development of local 48 governments takes place and the economic activity gradually plays an increasingly importantroleinspatialplanning,inthespacemanagementprocessesnecessaryisto draw up a clear elaboration of business activities and its analysis on the basis of mentionedabovePolishClassificationofActivities.Accordingto(Actof2July2004,on freedom of economic activity, Chapter 1, Art. 2) „Economic activity is a profit generation, construction, trade or service activity and prospecting, exploration and extractionofmineralsfromdeposits,aswellastheprofessionalactivitycarriedoutin organized and continuous manner.” The main legal act in this area is Council of MinistersRegulationof24December2007onthePolishClassificationofActivities(PKD). It sets out the rules for the implementation of the Polish Classification of Activities (PKD), hereinafter referred to as PKD 2007 for use in statistics, records and documentation and accounting, as well as in the official registers and information systems. The regulation specifies that from the date of entry into force of the Regulation,i.e.from01January2008PKD2007classificationsystemcoversallentries of entities starting economic activity. It is also highlighted that, until 31 December 2009 economic activities registered before the date of entry into force of this RegulationwillbereclassifiedinaccordancewiththeclassificationofPKD2007.Inthe process of creation of SIP elements for a commune, successive changes of this provision were taken into consideration. The legal basis from Council of Ministers Regulation of 1 April 2009 is making changes in the regulation of the Polish Classification of Activities (PKD). The Regulation emphasizes, that in the case of entitiesofeconomicactivity,thatwillnotbereclassifiedaccordingtothestandardsof PKD2007to30September2009.theywillbesubjecttotheclassificationexofficioby apublicstatisticsofficials.Fig.24showsthemapofeconomicactivityofthesubjects developedinthecommuneaccordingtothedescribedmethodology. Fig.24.MapofeconomicactivityinZielonkicommune. Source:MIKAandSALATAownstudy. 49 Anadditionalelementofthecreatedsystemwasathematiclayerconcerning determinationoftheimpactareasofcommunityinvestmentactivitiesonthevalueof properties(UNIWERSAŁ,2014).InPoland,inaccordancewiththeprovisionsinforce of(TheAct,2003)asaresultofthedevelopmentoflocalplanstheinternalrevenueof the commune can increase. Through a well‐functioning land information system the system of local fees and taxes can be inspected currently. So ‐ the separation of the bettermentlevyimpactareaandtheplanningfeewillhelpinbetterexecutionofthese fees. Each new investment in technology infrastructure can be co‐financed by the inhabitants of the commune. Imposition of multiple charges on a single plot makes, thatitbecomeslessattractivetopotentialbuyers–theownertocompensateforthe chargesraisesthepriceoftheplot.OneoftheobjectivesofthedevelopmentoftheGIS systemfortheselectedcommunewasthereforethecreationofthematiclayersaimed atthetargetforautomaticorsemi‐automaticidentifyingtheareas,inwhichplanning fee and betterment levy have an area of activities. For the realization of the aim the programQGISwasused.Thestartingthematicmap,asintheotherdescribedcasesof created spatial information systems in communes, contains all the updated surface elements in the commune. To identify those elements the following thematic layers were used: precincts, plots, roads, buildings, fixture elements and GESUT networks (upgradedwiththehelpofGPS),MPZP(landuseplans).Eachoftheselayershasother attributes describing the layer. The attributes were chosen to fully identify the item. The main attribute is the ID of the object. As a result, after generating the base map, showninthenextfigures(Fig.25andFig.26).Thebufferzonesofinfluenceimpactsof thefeesforagivenpropertyweredesignated. Fig.25.Determinationoftheparcelswithinthescopeofresidentialareas. Source:MIKAandSALATAownstudy. The following figures present visualizations of the results of studies of areas belonging to the sphere of betterment levy influence and others in the selected commune.SoftwaretoolsQGISwereusedfortheelaboration. 50 Fig.26.Buffersandparcelslocatedintheirinfluenceonplots. Source:MIKAandSALATAownstudy. Fig.27.Thecreationoftheresultinglayerforthebettermentlevyduetothe constructionoftechnicalinfrastructure. Source:MIKAandSALATAownstudy. 51 In technical sense of studies, layer shows plots qualified for the betterment levyduetotheconstructionoftechnicalinfrastructure,itisthedifferenceofthelayer with parcels which are in the influence of buffers and a layer with plots already equippedwithgivennetwork.Forthispurposethespatialqueryequalswasusedand intheattributetableselectionswerechanged(Fig.27). Inthepresentationofselectedapplicationsandelementsoflandinformation systems surveyed and updated itemsoftechnical infrastructure should also be taken intoaccount.ThisissueisillustratedinFig.28(POSIAK,2014). Fig.28.Layersofbuildings,technicalinfrastructure,fittingsandprecincts. Source:MIKAandSALATAownstudy. An interesting element of the created system was the analysis of the rate of development intensity in another municipality. This problem is further illustrated by successivefigures30and29. Permanent monitoring of areas designated for housing in land use plan is importantintheprocessofspatialplanning.Theshareofdevelopedplotsinbuilding areasisthemainaimofthecontrol.Moreover,itslocationandinvestmentrateineach region has been monitored, too. Fig. 29 shows an analysis of the scattering of developedplots.Individualplotswithbuildingsandfinishedinvestmentsaremarked withadarkercolour. 52 Fig.29.ShareofdevelopedplotsinLocalDevelopmentPlan. Source:MIKAandSALATAownstudy. Plots designated for housing and not yet developed are marked with lighter colour. Such analyses help to determine the need to increase building areas in the future. Anotherexampleisthemanagementofroadexitsfrommunicipalroads.The locationandqualityoftheroadexitsaremonitoredandthelocationofobjectssuchas bridges and bus stops are placed on the map. The orthophotomap was used as abackground(Fig.30). 53 Fig.30.ShareofdevelopedplotsinLocalDevelopmentPlan. Source:MIKAandSALATAownstudy. 3.2.Resultsanddiscussion In the discussion of the results it should be noted that the adopted methodology proved to be fully helpful in the creation of local databases of spatial information systems in selected communes. Both the costs and the quality of the elaboration provedtobesatisfactoryfromthepointofviewoftherecipientsofthesystem.Forthe purposes of update of the contents of available maps handheld GPS receivers were applied. Their cost ranges 1000‐5000zł. Personnel costs were reduced by commissioning this task to the University of Agriculture students as a part of production traineeships in following subjects “Practical usage of GIS” and “Advanced techniques of GIS” carriedout at the University of Agriculture in Krakow, in turn the officeworkswerebasedmainlyontheQGISprogramunderopensourcelicense. Intheworldsoftwareiscommonlyusedunderopensourcelicense.Thepaper (STARKetal.,2008)presentstheconclusionsofthesurveyon„Theuseofopensource softwareinthegeospatialenvironmentinSwitzerland".Opinionsandconclusionsset forth on this basis seem interesting. A great knowledge of the subject in the associations and organizations operating in the geo‐information environment was demonstrated. Studies have shown that the OSS (OpenSource Software) is used in at least20%oftheworksinthefieldofwidelyunderstoodgeoinformation.Onthisbasis, canbeconcludedthatthisalsoappliestothecreationoftheSIP(SpatialInformation Systems).40%oftherespondentsreportedthewidespreaduseofOSS.Dependingon the studied branch and the software requirements (mapping, development and generalization of internet databases etc.) percentage results of the OSS application differ. They are located between 14% and 36% of responses in relation to the study population.InthegroupofrespondentsdominatedtheviewthatinordertouseOSSin 54 practice detailed knowledge about it is not required. This software is designed intuitivelyandpracticallyeveryonewhoearliercarriedoutworkingraphicprograms isabletoquicklylearnhowtouseOSS.Correlationshavebeenshownatthelevelof 36‐38% between knowledge and its practical use and the involvement of the respondentsintheworkintheOSSenvironment.Inaddition,itwasstatedthatOSSis being promoted mainly in sectors such as training and administrative sector. In the privatesectorOSSseemstobemuchlesspresent.ThereasonsfortheuseofOSSare satisfactory results in terms of functionality and quality of the obtained results. The lack of a license fee is also a strong argument. Disadvantages in the range of OSS applicationsinvolvecaseswhenitisnecessarytochangethesystematsomestageand carryoutassociateddatamigrations. Onthuspreparedthematicmapsanalyzesofthetechnicalbackgroundinthe housingandinvestmentareasinthecommunewerealsocarriedout.Thematiclayers containingLocalSpatialDevelopmentPlanortechnicalinfrastructurenetworksinthe commune were used. The following figures 31 and 32 show the results of selected analyzes, determining the level of the land investment and the accessibility to particular GESUT (polish abb.: geodesic evidence underground utility, author’s annotation)networkelements(KULESA,2013). Fig.31.TheratiooftheinvestedareasurfacetothoselabeledMNintheLocalSpatial DevelopmentPlanindifferentvillages. Source:KULESA,2013. 55 Fig.32.Percentagechartofeasyaccessofresidentialbuildingstotheinfrastructureby villages. Source:KULESA,2013. Onthebasisofdevelopeddetailedspatialinformationsystemsinselectedcommunes, the indicators of quality of life and its spatial differentiation were determined. They were presented on a high level of detail, because the relationship of each residential building with individual service points was examined. It should be noted here, that usingtraditionalmethodsofstatisticalanalysisitisonlypossibletoexaminethetotal qualityoflifefortheentirecommune.Themethodologyusedtodevelopcomplexand detailed land information systems in the communes, allowed to perform analysis in this area, using GIS tools. Thanks to them, it was possible to verify areas requiring investments improving commercial facilities, educational, communication, and health service. Furthermore, this analysis indicates the recipient sites that are attractive in terms of future investments, or the possibility of inhabitancy. Analysis of differentiation in quality of life, proved to be an extremely valuable source of information for commune. Thanks to the conclusions flowing from similar analyzes local governments can significantly improve the living conditions of their citizens, takingintoaccountintheiractivitiesthenecessityofproperspatialdevelopment. 3.3.Conclusions In the publication (DALE and MCLAREN, 1999) was shown that effective and efficient management of the land and its resources depends on the availability of good information about the area. Many countries already have or are in the process of creating a computerized national database of cadastral data. Data collected in computer systems thanks to information technology are integrated, analyzed and disseminatedinawaythatuntilrecentlywasnotpossible.Thearticlediscussesamong others, the issues related to the operation of such datasets. In addition, it mentions examples of well‐functioning land information systems. The authors emphasize the institutional,organizationalandbusinessissues,thatneedtoberesolved,tocreatefull valuespatialinformationsystemsonthefoundationofcadastraldata,usingGIStools. 56 Inaddition,theauthorspointoutthespecialroleofthecadastralsysteminthe processoflandmanagement:„Acadastreisadistinguishedformofalandregistration systeminthatthelatterhasbeenexclusivelyconcernedwithownership.Alandregister must operate within a strict legal framework and may not, in practice, cover a whole countrysincenotallcitizensmaychoosetoregistertheirlands.Thecadastre,however, shouldbebasedoncompletecoverageofacountrysinceitmaybeusedforthepurposes oflandtaxation”. Theadvantagesofintroducingspatialdatabasesrefertoallpotentialusersof the system, from the private sector to administration:”The creation of data in digital formisnecessary,butnotsufficient,foreffectivelandadministrationtooccur.Experience to date suggests that it is essential that the legal, political, economic, and social issues alsobeaddressed.Giventhatanyinherentproblemscanbeovercome,significantbenefits shouldensue.Privatecitizensseekingtomovehousewillbeabletolocatepropertiesthat meettheirneedsmoreeasilywhileconveyancewillbecheaperandmoresecure.Planners willfinditeasiertolocatesuitableplacesfordevelopmentanddeterminetheconstraints on their use. There will be clearer protection for sites of special scientific interest. Property developers and investors will be more secure in their analysis of sites while banksandothermortgagelendingorganisationswillhavemoreinformationonlandand propertyvaluesandhencebeabletoreducetheirrisksinlendingmoney.Architectsand builderswillhavemorecertainanddetailedinformationaboutsites.Governmentswillbe abletotaxlandandpropertymoreequitablyandmakemoreinformedjudgmentswhere therearecompetingproposalsfor.”(DALEandMCLAREN,1999). GIS software in recent years has changed to a small extent. Functions used today were known previously. Only the public pressure changes to provide spatial information in a simple way. To accurately hit the needs and provide solutions. This causes that the spatial data must be collected and processed at a high level of detail. Spatial information is valuable and credible when every inhabitant of the region is identifiedseparately.Thenthereisahigherprobability,thathewouldbeinterestedin conclusionsobtainedusingGIS.Therearetwolevelsofgeomaticsworkwithdata:the spatial data model ‐ intricate, complex and unfamiliar to most people (at this level advancedvisualizationtools,specializedsoftware2D,2.5Dareused),andasimpleand easy to interpret set of the results of spatial analyses (3D visualization systems and programsforanimation). Inthestandardrange,GISusuallyprovidetoolsformapeditionfortheneeds ofthepresentationonacomputerscreenorpreparationofmapstoprint(SZCZEPANEK 2013).Itenablesnotonlythecollection,butalsoanalyzingofgeographicdata–data associatedwithgeographicalspaceandassignedtothemdescriptiveattributessuchas estimation of the intensity ratios of inhabitancy, or regional development trends. According to (GOTLIB et al. 2007) ‐ GIS systems enable recording of spatial data in alogicalstructure,andtheircomprehensiveanalysisandvisualization.Theyalsooffer thepossibilityofdescription,explanationandpredictionofthespatialdistributionof geographicalphenomena.Geoinformationsystemsprimarilyconsistoftheappropriate softwareandhardware, collecteddata,the algorithms and procedures forprocessing andsharingofinformation.Thisexampleshows,thatusingthedescribedmethodology it is possible to apply cheaper integrated research and measuring tools and get asatisfactoryresult. ThepresentedmethodologyisconsistentwiththedefinitionofGIStechnology (GOTLIBetal.2007)understoodasasetofmethodsandtechniquesfortheconstruction ofgeographicinformationsystems.GIStechnologycapabilitiesareused,amongothers, 57 in administration, nature conservation, spatial planning, pollution monitoring, health care, geomarketing, localization systems, education, science, crisis management. The rangeofapplicationscontinuestogrow.Currently,itisdifficulttofindasphereoflife, inwhichtheyarenotapplicable. The advantage of created by the described methodology spatial information systems is the possibility of their extension for a further layer, and thus openness to variation in needs and analyzes trends in a given area. In subsequent actions in implementedspatialinformationsystemsitisplannedtoperformnextstepsinorder to allow the determination in areas of individual communes. In the future, the developedsystemcanbeextendedbyfurtherthematiclayerscontaining,interalia: ‐supplementinglocaldatabaseswithinformationpromotingtheregion, ‐interestingplacesandtouristcuriosities, ‐specificationsitesatrisk,e.g.withflood,landslides,etc.. 58 4. ANALYSIS OF POLISH SDI WITHIN THE CONTEXT OF NEEDSOFREALESTATEDEVELOPERS Inthelasttenyearstherehasbeenobservedasignificantactivityincreatingregional andlocalGISinPoland.Theseactivitiesaretheresultoftheglobaltrendformationof the Spatially Enabled Society (FIG, 2012). It is linked with the need to strive for sustainabledevelopment. The concept of Spatially Enabled Society derives from the concept of the information society. It is worth recalling one of its many definitions, where the Information Society is understood as a society that not only has a strong means of information processing and communication, but these measures are the basis of national income and provide livelihoods of the majority of society" (GOBAN‐KLAS and SIENKIEWICZ,1999). STEUDLER and RAJABIFARD (Fig. 33.) modified the concept of information society in the direction of society spatially informedandliterally"Spatially Enabled Society" (SES), (FIG, 2012).TheSESconceptimplies adding to the existing informationtheseonlocationin space, thereby releasing the wealth of existing knowledge about the land and the water, their legal and economic situation, resources,availability and potential applications and hazards. Spatially enabled society uses the concept of place and location to organize information and processes. Currently it is one of the main aim of consistent many government programs developmentstrategies. Fig.33.Coverofelaborationon„SpatiallyEnabledSociety”. Source:FIG,2012. Spatially enabled encourages the development of innovation, transparency and democracy in the country. In connection with the chosen development direction we can talk about the onset of spatial information revolution. Citizens and their governments must be spatially enabled, have the right tools and information within easyreachtomaketherightdecisions. 59 The concept of a spatially enabled society offers new opportunities for the stateanditscitizens.Itsintentionistoleadtotheeffectiveuseanddeliveryofspatial dataandservices. SES benefitsfroma wide rangeofspatial data, information and services asa means to organize activities related to land and water. SES is now part of the global development goals pursued by governments in many countries. This indicates the importanceofincreasingthespatialinformationisalsointhedevelopmentstrategies oflocalandregionalpoliciesandmaketherightdecisionsinthepublicsector. SESincreasinglyactiveinthevirtualworld,buttheseactivitiesmustgohand in hand with the institutional and structural reforms in the real world in the use of spatialinformationandSpatialDataInfrastructuresasanaccessplatforms.Localand regional SDI may be used for different purposes. Created systems include different kind of information especially cadastral data. We also may observe variety of actors involvedintheircreationaswellasusersinterestedinobtaininginformationfortheir needs.Thereisalargegroupofinvestorsinrealestatemarketwhoexpectthatthese developingsystemsmaytakearoleofmainsourcesofinformationonrealestate.For them it is important to develop local and regional GIS with the aim of usefulness in realizationofinvestmentsintherealestatemarket. This elaboration is to show usefulness of geographic information systems within the context of needs of real estate investors. Having regard to diversity of the systems there has been made a research in a form of comparative analysis of information presentedbystate,regionalandlocalsystems,whichareessentialondifferentstages ofinvestmentprocess. 4.1.Methodology One of the main objectives of this study is to assess the functioning of four selected portalswithspatialdataasapartoflocal,regionalandstatelevelofNationalSpatial Data Infrastructures (NSDI) in the context of the recommendations of the Inspire Directive and guidelines of European Interoperability Framework. The analysis coveredtheorganizationalandtechnicalgeoportalsactionarea.Theauthorsanalyzed fourdifferentlevelofSDIgeoportals: Geoportal.gov.pl(statelevel), AtlasofWarmiaandMazury(regiolanlevel), MSIPMO(provincelevel), SIPStawiguda(municipalitylevel). The choice of these geoportals was not accidental. All these geoportals except Geoportal.gov.pl(nationallevel)havedatabasefromthenorth‐eastoftheWarmiaand MazuryRegion(oneofthepoorestregionsinPoland),(Fig.34). 60 Fig.34.WarmiaandMazuryRegion. Source:DAWIDOWICZA.onthebasisofKSNG(2014). InPolandthereare16regions(inPolish:województwa).Eachregioncontains provinces‐districts(inPolish:powiat).Municipality(inPolish:gmina)isthesmallest administrative division of the country. Figure 35 and table 4 presents administrative divisionofRepublicofPoland. Fig.35.AdministrativedivisionofRepublicofPoland–asatJanuary1,2011. Source:CommissiononStandardizationofGeographicalNames,2010 61 Table4.ListofterritorialunitsofPoland‐asat01.01.2015. 1571 602 908 602 18 19 36 17 20 9 18 14 35 3 16 13 25 49 5 16 19 11 78 92 171 41 133 121 229 36 110 78 81 96 71 67 117 50 55 35 22 33 26 47 50 32 34 27 17 22 26 33 90 53 91 52 42 42 44 61 85 35 50 40 42 71 31 49 109 64 55 35 22 33 26 47 50 32 34 27 17 22 26 33 90 53 ‐ ‐ ‐ ‐ ‐ ‐ 18 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 5 ‐ ‐ ‐ 5 4 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 5 ‐ Total Delegations 306 169 144 213 83 177 182 314 71 160 118 123 167 102 116 226 114 Districts 2479 4 4 4 2 3 3 5 1 4 3 4 19 1 2 4 3 UrbanRural 66 26 19 20 12 21 19 37 11 21 14 16 17 13 19 31 18 Rural 314 Urban Inurban‐rural communities Municipalities Auxiliary units Total Dolnośląskie Kujawsko‐pomorskie Lubelskie Lubuskie Łódzkie Małopolskie Mazowieckie Opolskie Podkarpackie Podlaskie Pomorskie Śląskie Świętokrzyskie Warmińsko‐mazurskie Wielkopolskie Zachodniopomorskie Cities Citieswith districtstatus Poland 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 TerritorialunitsofPoland District (province) Specification: countryandregions Source:DAWIDOWICZbasedonthedatafromTERYT(NationalRegisterofCountry TerritorialDivision). Theaimofthestudyistocomparethethematicresources,availableservices, tools and skills to use some of the national SDI portals in every level of country administrativedivision.ExaminationoftheSDIportalstechnicalconditionswasmore complex.ThebasicassumptionintheresearchpartwasanevaluationofNSDIfromthe point of view an ordinary user. Have been taken into account the general range of thematicdataandmetadataprovidedbyportals,availabletools,andservicesrelatedto the use of these data. In view of the variety of solutions offered by SDI portals and increasingly larger needs of citizens in the use of these data, were also examined possibleservicesofferedbytheanalyzedportalsintherangeofpersonalization. Particular attention was paid to the possibility of creating a user account on the site and the ability to customize the tool palette to suit user needs. Due to the constantlyevolvingbranchservicesdesignedformobiledevices,theassessmentalso includedtheabilitytodownloadapplicationsfromtheSDIportalstomobiledevices. 4.2.SDIasanetworkandanenablingplatform ThestartingpointfortheconstructionofSDIinitiativewastoformulatethecreationof economic prosperity, stability (balance), social, environmental protection can be facilitatedthroughthedevelopmentofproductsandservicesbasedonthespatialdata collectedatalllevelsofadministrationandcountryterritorialdivisiontoeasyuseby government bodies, the private sector and individuals. In this context, access to data andspatialinformationintegratedonasingleplatformplayakeyrole.Thefirstworks ofconstructionoftheNationalSpatialDataInfrastructurewaslaunchedin1990inthe United States. The idea of sharing of spatial data spread toother continents. In 2001 62 wasbornaninitiativetoconstructionofEuropeanSpatialInformationInfrastructure. ThenalsoformedthefoundationsoftheINSPIREDirective(InfrastructureforSpatial InformationintheEuropeanCommunity),whichwasadoptedin2007bytheEuropean ParliamentandtheCounciloftheCommissionoftheEuropeanCommunity(INSPIRE, 2007). TheconceptofSDIsofarreceivedanumberofdefinitions.Inoneofthemthe spatial data infrastructure is understood as "a set of legal, organizational, economic and technical conditions: ensure universal access to sustained spatial data from the territory of the country and geospatial services, contribute to the efficient use of geoinformationforincreasingthecompetitivenessoftheeconomy,takingintoaccount the principles of sustainable development of the country, allow the rational managementofgeoinformationmanagedbythegovernmentandself‐government,and contribute to the development of the information society" (http://gisplay.pl/gis/krajowy‐system‐informacji‐przestrzennej.html15). InaccordancewiththedefinitionadoptedintheINSPIREDirective(2007)by SDI is understood described metadata and spatial data sets for their services, technology, processes and procedures that are used and shared by co‐creating infrastructure for spatial information leading authorities, other authorities and third parties. INSPIRE applies to geographical and environmental information that are stored in electronic form by public authorities of the country concerned or on their behalf. Spatial information refer to the areas in which Member State has and/or exercises jurisdictional rights. Spatial information, in accordance with the Directive, shouldbeincludedinthenational'geoportals',arelistedinAnnexesI,IIandIIIofthe Directive2007/2/EC. TheAnnexIsetsoutthebasicspatialdata,suchasadministrativeboundaries, geographic names, cadastral parcels, hydrographs and transport networks. However, in Annexes II and III are specific data on, inter alia, orthoimages, geology, soil use, human health and safety, environmental monitoring facilities, and distribution of public service or industrial facilities. Spatial information listed in the Annexes to Directive INSPIRE informationare mandatory forNSDI in all Member States.NSDI of the Member States can be enhanced with additional thematic sections or modules of spatialinformation. Thearticle11paragraph1oftheINSPIREDirectiveindicatesthatallmember States shall establish and operate a network of the following services for the spatial datasetsandservicesforwhichmetadatahavebeencreatedinaccordancewiththis Directive: a) discovery services making it possible to search for spatial data sets and services on the basis of the content of the corresponding metadata and to displaythecontentofthemetadata; b) view services making it possible, as a minimum, to display, navigate, zoom in/out, pan, or overlay viewable spatial data sets and to display legend informationandanyrelevantcontentofmetadata; c) downloadservices,enablingcopiesofspatialdatasets,orpartsofsuchsets,to bedownloadedand,wherepracticable,accesseddirectly; d) transformation services, enabling spatial data sets to be transformed with aviewtoachievinginteroperability; e) servicesallowingspatialdataservicestobeinvoked. 63 AnnexIII AnnexII AnnexI No Annex The data integrated in the SDI can be flexibly expanded despite initially planned database topics covered in the Annexes of the INSPIRE Directive covering subject matterdescribedinTable5. Table5.Spatialdatathemes. Theme 1 Coordinate systems reference 2 Geographicalgridsystems 3 Geographicalnames 4 Administrativeunits 5 Addresses 6 7 Cadastralparcels Transportnetworks 8 Hydrograph 9 Protectedsites 1 Elevation 2 Landcover 3 Orthoimagery 4 Geology 1 2 3 Statisticalunits Buildings Soil 4 Landuse 5 Humanhealthandsafety Contents Systemsforuniquelyreferencingspatialinformationinspaceasa set of coordinates (x, y, z) and/or latitude and longitude and height,basedonageodetichorizontalandverticaldatum. Harmonisedmulti‐resolutiongridwithacommonpointoforigin andstandardisedlocationandsizeofgridcells Names of areas, regions, localities, cities, suburbs, towns or settlements, or any geographical or topographical feature of publicorhistoricalinterest Units of administration, dividing areas where Member States haveand/orexercisejurisdictionalrights,forlocal, regionaland nationalgovernance,separatedbyadministrativeboundaries Location of properties based on address identifiers, usually by roadname,housenumber,postalcode Areasdefinedbycadastralregistersorequivalent Road, rail, air and water transport networks and related infrastructure. Includes links between different networks. Also includes the trans‐European transport network as defined in DecisionNo1692/96/ECoftheEuropeanParliamentandofthe Council of 23 July 1996 on Community Guidelines for the development of the trans‐European transport network (1) and futurerevisionsofthatDecision Hydrographical elements, including marine areas and all other water bodies and items related to them, including river basins and sub‐basins. Where appropriate, according to the definitions setoutinDirective2000/60/ECoftheEuropeanParliamentand of the Council of 23 October 2000 establishing a framework for Communityactioninthefieldofwaterpolicy(2)andintheform ofnetworks Areadesignatedormanagedwithinaframeworkofinternational, Community and Member States' legislation to achieve specific conservationobjectives Digitalelevationmodelsforland,iceandoceansurface.Includes terrestrialelevation,bathymetryandshoreline Physical and biological cover of the earth's surface including artificial surfaces, agricultural areas, forests, (semi‐)natural areas,wetlands,waterbodies Geo‐referenced image data of the Earth's surface, from either satelliteorairbornesensors Geology characterized according to composition and structure. Includesbedrock,aquifersandgeomorphology Unitsfordisseminationoruseofstatisticalinformation Geographicallocationofbuildings Soils and subsoil characterized according to depth, texture, structureandcontentofparticlesandorganicmaterial,stoniness, erosion, where appropriate mean slope and anticipated water storagecapacity Territory characterized according to its current and future planned functional dimension or socio‐economic purpose (e.g. residential,industrial,commercial,agricultural,forestry) Geographicaldistributionofdominanceofpathologies(allergies, cancers, respiratory diseases, etc.), information indicating the 64 6 Utility and governmental services 7 Environmental monitoring facilities 8 Production and industrial facilities 9 Agricultural and aquaculturefacilities Population distribution — demography 10 11 Area management/ restriction/regulation zonesandreportingunits 12 Naturalriskzones 13 Atmosphericconditions 14 16 Meteorological geographicalfeatures Oceanographic geographicalfeatures Searegions 17 Bio‐geographicalregions 18 Habitatsandbiotopes 19 Speciesdistribution 20 Energyresources 21 Mineralresources 15 effect on health (biomarkers, decline of fertility, epidemics) or well‐being of humans (fatigue, stress, etc.) linked directly (air pollution, chemicals, depletion of the ozone layer, noise, etc.) or indirectly (food, genetically modified organisms, etc.) to the qualityoftheenvironment Includes utility facilities such as sewage, waste management, energy supply and water supply, administrative and social governmental services such as public administrations, civil protectionsites,schoolsandhospitals Location and operation of environmental monitoring facilities includesobservationandmeasurementofemissions,ofthestate of environmental media and of other ecosystem parameters (biodiversity, ecological conditions of vegetation, etc.) by or on behalfofpublicauthorities Industrial production sites, including installations covered by Council Directive 96/61/EC of 24 September 1996 concerning integrated pollution prevention and control (1) and water abstractionfacilities,mining,storagesites Farmingequipmentandproductionfacilities(includingirrigation systems,greenhousesandstables) Geographical distribution of people, including population characteristics and activity levels, aggregated by grid, region, administrativeunitorotheranalyticalunit Areasmanaged,regulatedorused forreportingatinternational, European, national, regional and local levels. Includes dumping sites, restricted areas around drinking water sources, nitrate‐ vulnerable zones, regulated fairways at sea or large inland waters, areas for the dumping of waste, noise restriction zones, prospecting and mining permit areas, river basin districts, relevantreportingunitsandcoastalzonemanagementareas Vulnerable areas characterised according to natural hazards (all atmospheric, hydrologic, seismic, volcanic and wildfire phenomena that, because of their location, severity, and frequency, have the potential to seriously affect society), e.g. floods, landslides and subsidence, avalanches, forest fires, earthquakes,volcaniceruptions Physical conditions in the atmosphere. Includes spatial data basedonmeasurements,onmodelsoronacombinationthereof andincludesmeasurementlocations Weather conditions and their measurements; precipitation, temperature,evapotranspiration,windspeedanddirection Physical conditions of oceans (currents, salinity, wave heights, etc.) Physical conditions of seas and saline water bodies divided into regionsandsub‐regionswithcommoncharacteristics Areas of relatively homogeneous ecological conditions with commoncharacteristics Geographical areas characterized by specific ecological conditions,processes,structure,and(lifesupport)functionsthat physically support the organisms that live there. Includes terrestrial and aquatic areas distinguished by geographical, abioticandbioticfeatures,entirelynaturalorsemi‐natural Geographical distribution of occurrence of animal and plant species aggregated by grid, region, administrative unit or other analyticalunit Energy resources including hydrocarbons, hydropower, bio‐ energy, solar, wind, etc., where relevant including depth/height informationontheextentoftheresource Source: INSPIRE, 2007. 65 AnessenceofSDIcontainsthefivemajorassumptionsINSPIRE(2007)where: a) the data should be collected only once and stored and managed in the most correctandefficientmannerbytherelevantinstitutionsandservices; b) shouldbeensuredthecontinuityofspatialdatasothatitispossibletoacquire a variety of resources, from a variety of sources, and that they can be made availabletomultipleusers,andforavarietyofapplications; c) spatial data should be stored at an appropriate (one) level of public administrationandmadeavailabletothoseatallotherlevels; d) spatial data necessary for the proper management of space at all levels of governmentshouldbepubliclyavailable(i.e.withoutlimitingconditionsand/ orhindertheirfreeuse); e) should be provided access to information about which spatial data are availableandunderwhatconditions,aswellasinformationthatenablesusers toevaluatetheusefulnessofthesedatafortheirownpurposes. OnthebasisoftheINSPIREdirectiveallEUMemberStateshavegiventothe use networking sites that allow searching, viewing and downloading spatial information. All these services are available through the INSPIRE portal, which is connectedwiththenationalgeoportalsofEUcountries. The activity of INSPIRE is coordinated at Community level by the European Commission and at national levels by the appropriate structure designated by the authoritiesofthestates. MemberStatesshouldsharethedatacollectedandallowpublicauthoritiesto access them, their exchange and use for public tasks that affect the environment. Access to data may be payable except in cases where access needs to provide the information in connection with the reporting legislative bodies. Access can also be limited due to the properfunctioningof the justice, national defence or international relations. InPoland,thereisatendencytobuildSDIportalsatvariouslevelsofcountry administrativedivision,adaptedtotheneedsofthepublicadministrationbutalsolocal investors.ComparativeanalysisofSDIportalsondifferentlevelsoftheorganizationis torevealthedesirabilityandqualityofarisingportals. 4.2.1.GEOPORTAL.GOV.PL ThehistoryofPolishSDIcalledGeoportalgoesbackto2005,whentheHeadOfficeof GeodesyandCartographylaunchedtheGEOPORTAL.GOV.PLproject.Theprojecthas been funded under the Sectoral Operational Programme "Improvement of the Competitiveness of Enterprises" 2004‐2006 (http://geoportal.gov.pl/en/o‐ geoportalu/informacje‐o‐projekcie/informacje‐ogolne‐access01.07.2014). The main goal of the GEOPORTAL.GOV.PL project was to improve competitivenessofenterprisesbyprovidingthemonlineaccesstoservicesbasedon spatial data, including cadastral data and metadata. Other important goals of the projectincluded: Developmentofentrepreneurshipaswellasincreasinginnovativenessand competitivenessofenterprises,duetoaccessofspatialdata. Improving decision processes in enterprises, regarding investment decisions. Modernizing the work of public administration (on central, regional and locallevel)withinthescopeoftheproject,bymeansofintroducingnewIT technologies. 66 Increasing the knowledge and importance of spatial data as well as cadastraldataamongentrepreneurs. Savings (in terms of time and costs) for entrepreneurs using the geodesy services. Enrichingtheofferofenterprisesprovidingservicesbasedonpublicspatial data. Participationindevelopingtheinformationsociety. Under the GEOPORTAL.GOV.PL project we have developed the infrastructure of nodes of the National Infrastructure of Spatial Data (in Polish: Krajowa Infrastruktura Informacji Przestrzennej ‐ KIIP), cooperating and providing services ranging from searching and providing data to data analysis. The network of KIIP nodeshasbeenbuiltonthreelevels:central,regionalandlocal. The project did also result in development of an internet portal: www.geoportal.gov.pl – acting as a broker, providing users with spatial data and services.Theprojecthasbeenfinishedin2008,anditresultedindevelopmentofthe followingdatabases: Cadastraldata, Geographicdatabase, DatabaseofTopographicObjects, Orthophotomaps, Topographicmaprasters, Thematicmaprasters, StateRegisterofBorders(PRG), StateRegisterofGeographicalNames(PRNG), NumericTerrainModel, Metadataofsetsandservicesofspatialdata. OncetheGEOPORTAL.GOV.PLhasbeenfinished,in2009wehavelauncheda new project, aimed at continuation and enhancement of previous activities: GEOPORTAL 2 – development of the spatial data infrastructure in the area of georeferentialregistersandrelatedservices. Fullimageofsubjectrequiresthepresentationofgeoportalinterfaces(Fig. 36, Fig. 37). 67 Fig.36.InterfaceofPolishGeoportal. Source:http://geoportal.gov.pl/(access17.07.2014). Fig.37.Cadastraldatainmappingtab. Source:http://mapy.geoportal.gov.pl/imap/? gpmap=gp0&actions=acShowServices_KATASTER&locale=en(freeaccess17.07.2014). 68 4.2.2.AtlasofWarmiaandMazury Atlas of Warmia and Mazury is a spatial information system implemented within the framework of the project "Construction of the Warmia ‐ Mazury GIS platform for enterprises". Atlas of Warmia and Mazury is a web service publicly available on the Internet. The system provides access to information about the region, published on maps.Suchaggregatedinformationcanhelpentrepreneursinfindingareasattractive forinvestments,assistindeterminingtheimpactofthelocationofinvestmentinthe development of urban and rural areas, the impact of population growth on the developmentofurbanandruralareasandalsohelpinthepreliminarydetermination ofthecomplexityoftheconductofinvestment(egroads),duetothestructureofland ownershipinthearea.Thesystemalsoallowsaccesstolocalzoningplanspublishedby themunicipalities,andallowstoordermapintheRegionalDocumentationCentreof GeodesyandCartography(inPolish:WojewódzkiOśrodekDokumentacjiGeodezyjneji KartograficznejWODGiK).AtlasofWarmiaandMazuryisaspatialinformationsystem for decision support in areas such as urban planning, environmental protection, agriculture, health, natural resources management, crisis management, telecommunicationsandtransport. Itcanhighlightthefollowingobjectivestocreateasystem: increasingtheuseoftelecommunicationsandInternettools, improvingthequalityandaccessibilityofe‐services, promoting synergy between the administration and the entrepreneurs, providingcomprehensiveinformationabouttheobjects, helpentrepreneursfindattractiveinvestmentareas, publicationofspatialplans. Atlas of Warmia and Mazury allows you to read the aggregated regional information(foruseinthemanagementofprovince).Italsoallowsauthorizedusersto exchange information in a local area network (data, documents, results of analyzes) needed in the implementation of the current office tasks. Atlas is also unique in the wholecountry,thesystemthatallowstheuseofinfrastructurecreateddirectlybylocal governments to keep their own records. Local Government Units using the Atlas of Warmia and Mazury do not bear the cost of building data structures, ensuring the technicalinspectionofprocessedandpublishedmaterial,theauthorcarecosts,costs to fit the portal for the new law and the costs of infrastructure development and promotion of the portal server. These are great savings in the case of such action by asmallLocalGovernmentUnits. Expectsthefollowingbenefitsofbuildingtheportal: Improvingtheefficiencyofthepublicsectorthroughthecreationof rapidaccesstoknowledgeandinformation, Increasing the number of people interested in geographic informationanduseoftheInternet, Increasing the level of employment in the areas covered by the project, Raiseawarenessofentrepreneurs,forwhomasolutionisdedicated, The possibility of placing an order on the selected map and send orderstoWODGiKforcontractperformance(onlinestore), Improvingthequalityoflifeofcitizensandtheregion Createandpublishownmaps. 69 Built portal consists of two structures. The first is an external portal for businessandindividuals,whoinadditiontoobtainingextractsofmapsandobtaining informationabouttheinvestmentareashavingtheopportunitytocreateownthematic mapsandplacingitonthepageandonthewebsites.Second,theinnerpanelforoffice workers who will supply the system data available to the office. Thanks to local governmentunitsreceiveatoolforanalysistosupporttheirwork.Portalisanopen, i.e.theofficesthatwishtopublishtheirdataonthetheportalshouldcontacttheOffice oftheMarshalofWarmiaandMazuryat:[email protected] inordertoobtain theinformationneededtobeginAtlasofWarmiaandMazury(Fig.38). Atlas of Warmia and Mazury was implemented in Esri technology. System infrastructure is located in the Office of the Marshal of Warmia and Mazury. The system is scalable and its performance monitored by the staff of the office and the contractor‐thecompanySmallGISLtd.fromKrakow.Ifnecessary,decisionsaremade concerning the development and improvement of the parameters characterizing the capacitystorageandspeedofservice. UnfortunatelyportaloperatesonlyinPolishversion. Fig.38.AtlasofWarmiaiMazury. Source:http://atlas.warmia.mazury.pl/mpzp/access3.03.2015. 4.2.3.MSIPMO MSIPMOsystemwasintroducedin2009,butpreparatoryworkstookfewyearsdueto determinants from the Public Procurement Law. Under this circumstances there was prepared a project that includes the design and implementation of organizational‐ technical infrastructure ofMunicipal Spatial Information SystemofOlsztyn, which is apart of the national infrastructure for spatial information. The project provides acommon(public)accesstoupdated,spatialreferencedatabasesofthecityofOlsztyn, in particular, the public data registers connected with spatial planning (Studium 70 wykonalności projektu “Rozbudowa infrastruktury sieci miejskiej obejmującej jednostki publicznenatereniemiastaOlsztyna”2013). MSIPMOwasmadebyconsortiumGISPartnerandGeomatykaKrakówforneeds of the city council specially department of surveying, spatial planning and other departmentsthatrequirespatialinformationaswellasinformationaboutrealestate ownership. This system presents spatial information within borders of the city. MSIPMOoperatesinamulti‐layerclient‐serverarchitecture. MSIPMO consists of several layers and databases. First of all we may find here alayer of orthophotomap – satellite illustration of Olsztyn from 1995, 2005 or 2009. Map coverage from 2009 on the backing of general geographic map is shown on Fig. 39.Besidesthereisapossibilityofshowinginformationfromlandregistry–situation of plots, buildings and precincts (Fig. 40). Moving on to details MSIPMO presents numbersanduniversalidentificationofplots,theirareaandnumberofregistry,where anordinaryuserisabletofindinformationaboutownership(Fig.41). Fig.39.ChosenlayeronaMSIPMOview‐orthophotomapfrom2009. Source:msipmo.olsztyn.eu. 71 Fig.40.ChosenlayeronaMSIPMOview–precinctKortowo‐situationofplotsand buildings. Source:msipmo.olsztyn.eu. Fig.41.DescriptionofachosenplotattachedtothecadastralmaponMSIPMOview. Source:msipmo.olsztyn.eu. Thissystemhasmoreexpandedsearchtool,thathelpsfind: chosenprecinct, chosenplotwithitsarea, chosenbuildingwithitsageandowner, chosenpublicutilities. 72 On the next figure (Fig. 42) created on the basis of MSIPMO online view there is an example of searching results for public utilities with a kindergarten – its name and location. Fig.42.DescriptionofachosenpublicutilityonaMSIPMOview. Source:msipmo.olsztyn.eu. MSIPMOalsoprovidestoolsofidentifyingobjectsaswellasmeasuringdistances andareas.Moreoverhasatoolofselectingareabydrawinglinesandpolygons.User maysketchoncurrentviewansaveresultsforhispurposes. Furthermorethereisaseparatedoverlapforchosendetailedmapssuchas: cityplan, locationoflanduseplans, investmentareasandoffersforinvestors, acousticmap, locationofhistoricalmonuments, mapofownershipandpossession. Fig. 43 presents this variety. Wherefore MSIPMO allows its users access the most detailedinformationaswellascarryoutanalyzesonthebasisofinformationavailable indifferentlayersanddatabasesofthissystem. 73 Fig.43.VarietyofdetailedmapsattachedtoMSIPMO. Source:msipmo.olsztyn.eu. 4.2.4.SIPStawiguda PlanninginformationsystemwasintroducedinmunicipalityofStawigudain2013.It was developed by MD Project for needsof municipality. This system presentsspatial information within borders of the commune. It is a source with variety of spatial information. It combines cadastral and topographic information with orthophotomap as well as current master (land use) plans. “SIP Stawiguda” gives a view of different combinedlayerslike: boundariesoflanduseplansandboundariesofplotsfromcadastralmap(Fig. 44), topographicmapandboundariesofplots(Fig.45), orthophotomapandlanduseplans(Fig.46). 74 Fig.44.ChosenlayersonaSIPStawigudaview‐boundariesoflanduseplansand plots. Source:sip.stawiguda.pl. Thissystemhasalsoasearchtool,thathelpsfind: areaofchosenvillage, chosenplot, chosen land use plan (with its whole description attached in a file including symbolsandparameters). “SIP Stawiguda” also provides tools of printing current view, saving links, identifying objectsaswellasmeasuringdistancesandareas. 75 Fig.45.ChosenlayersonaSIPStawigudaview‐topographicmapandboundariesof plots. Source:sip.stawiguda.pl Fig.46.ChosenlayersonaSIPStawigudaview‐orthophotomapandlanduseplans. Source:sip.stawiguda.pl 76 4.3.AssessmentoftheNSDI Annex To assess national SDI portals adopted specific determinants. The intention of the authors was to identify differences without determining the weight of each attribute.Testingtookplaceon15March2015.Thetestresultsarepresentedin Table6and Table7andintheFig.47andFig.48. An "X" indicates that a factor present in the SDI portal, while "-'' means the absence of the desired item. Table 6. Scope of the data made available in SDI portals by the annexes of INSPIRE Directive. No Theme 1 Coordinate reference systems Geographical grid systems Geographicalnames Administrativeunits Addresses Cadastralparcels Transportnetworks Hydrography Protectedsites Elevation Landcover Orthoimagery Geology Statisticalunits Buildings Soil Landuse Human health and safety AnnexIII AnnexII AnnexI 2 3 4 5 6 7 8 9 1 2 3 4 1 2 3 4 5 6 7 8 9 Utility and governmental services Environmental monitoringfacilities Production and industrialfacilities Agricultural and aquaculturefacilities Geoportal.gov.pl (nationallevel) Atlasof Warmiaand Mazury (regionallevel) MSIPMO (provincial level) SIPStawiguda (community level) x x x ‐ x x x ‐ x x x x x x x x ‐ x ‐ x x ‐ ‐ x x x x x x x x x x ‐ ‐ x x x x x x x x ‐ x x x x ‐ ‐ x ‐ x ‐ x ‐ x x ‐ ‐ ‐ ‐ x ‐ ‐ x ‐ x ‐ ‐ ‐ ‐ ‐ x x ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 77 10 Population distribution demography No — Theme ‐ ‐ ‐ ‐ Geoportal.gov.pl (nationallevel) Atlasof Warmiaand Mazury (regionallevel) MSIPMO (provincial level) SIPStawiguda (community level) ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 11 Area management/ restriction/regulatio n zones and reportingunits 12 Naturalriskzones 13 Atmospheric conditions 14 Meteorological geographical features 15 Oceanographic geographical features 16 Searegions 17 Bio‐geographical regions 18 Habitats and biotopes 19 Speciesdistribution 20 Energyresources 21 Mineralresources Source:KRUKOWSKAandDAWIDOWICZownstudy[2015]. Scopeofthedata Annex I 9 Annex II Annex III 9 8 4 3 2 3 3 3 2 2 1 Geoportal.gov.pl Atlas of Warmia and Mazury 78 MSIPMO SIP Stawiguda Fig.47.ThescopeofdataratingoftheSDIportals. Source:DAWIDOWICZA.ownstudy Thescopeofdatainthefirstthreeportalsisquitesimilarwhenitcomestotopicsof Annex I. With regard to all thematic data the best seems portal Atlas of Warmia and Mazury while the weakest local SIP Stawiguda portal. It can be concluded that local portals contain only data for local development. The higher country administrative divisionlevelofportalsincludingawiderrangeofdatafore.g.statisticalanalysis. Table7.FunctionalityofselectedSDIportals. Typeofgeoportal Tools Content Attribute Sectoralmodule INSPIREmodule Statisticalmodule DatafromEuroBoundaryMap State Register of Geographical Names Thecadastraldata Surfacerelief GeneralGeographicDatabase Vectormap The database of topographic objects Thematicmaps Scansoftopographicmaps Orthophotomap Dataonbasiccontrolnetworks Adjust the map to the selected area Adjust the map to the selected selection The form of data presentation [2D/3D] Thumbnail/Imagepreview Paneloflayers Legend Back/Backtothestartpage Retry Zoom/Zoomtoselectedarea Zoomtoselectedobject Insertingaclassranges Reduction Movingthemapcursor Moving the map by clicking on theframe Centering Removalofselection Selection Geoportal.gov.pl (nationallevel) Atlasof Warmiaand MSIPMO Mazury (provincial (regional level) level) SIPStawiguda (community level) X X X X ‐ ‐ ‐ ‐ X ‐ ‐ ‐ ‐ ‐ ‐ ‐ X X X X X X X X X X X X X X X X X X X ‐ X X ‐ ‐ X X X X X ‐ X X X ‐ X ‐ X X X ‐ X X X X ‐ ‐ X ‐ 2D 2D 2D 2D X X X X X X X X X X X X X X X X X ‐ X X X X X X X X X X X X X X ‐ X X ‐ ‐ ‐ X X X ‐ ‐ ‐ X X X X X X X X X X X X 79 Typeofgeoportal Personalization Services Attribute Ruler ‐ measure the distance Addingtextcharacters Measurementofsurface Showing the coordinates of thecursor Showing the coordinates of mapcoverage Cleanthemeasurements Information about specially selectedobject Thechoiceofscale Searchbyname Searchbykeyword Searchbyparcelnumber Search by a number of real estate Searchbyaddress Search by administrative unit Selectadifferentcoordinate system Metadatabrowser Entermetadata Editmetadata Savetheimage Printsetting Print ExportData CreateaLink Sendbymail Buyingamap Selecting a different language The ability to log on to the website Customizing the Tool Palette Colouring Availability of applications onmobiledevices Geoportal.gov.pl (nationallevel) Atlasof Warmiaand MSIPMO SIPStawiguda Mazury (provincial (communitylevel) (regional level) level) X X X X ‐ X ‐ X X X ‐ X X X X ‐ X X X ‐ X X X X X X X X X X ‐ X X X ‐ X X X ‐ X X ‐ ‐ X X X X ‐ X X X ‐ X X X X X X X ‐ X X X X ‐ ‐ ‐ X ‐ X X X X X X X X ‐ ‐ ‐ ‐ X X X X X X ‐ ‐ ‐ ‐ ‐ X ‐ X ‐ ‐ X ‐ ‐ X ‐ ‐ ‐ X X X ‐ X ‐ ‐ ‐ X ‐ ‐ ‐ X ‐ ‐ ‐ Source:KRUKOWSKAandDAWIDOWICZ[2015] 80 FunctionalityofselectedSDIportals Content Tools Services Personalization 22 14 16 20 18 16 14 11 9 8 7 5 1 Geoportal.gov.pl 1 AtlasofWarmia andMazury MSIPMO 9 0 SIPStawiguda Fig.48.ThefunctionalityratingoftheSDIportals. Source:DAWIDOWICZA.ownstudy. In terms of functionality, the first three analyzed portals similarly present themselves, the most different is SIP Stawiguda portal, which is probably the lowest fundingforhisconduct.Itisfunctionallyadaptedtothelocalusers.Itcanbeassumed thatisusedbylocalpublicentities,investorsandpropertyowners. An important element of the functionality of portals are services that allow spatial analysis. Most of them have an Atlas of Warmia and Mazury Portal, and a little less MSIPMO and Geoportal.gov.pl. This is due to the fact that regional portals serve not only to provide spatial information to realize the vision of spatially enabled society, but also to the basic spatial analysis, that excel in the regional and provincial development. This phenomenon is beneficial and important for sustainable development. 4.4.TheuseofGISsystemsforrealestatemarketinvestors According to research made by BEHRENS and HAWRANEK (1993) in the investment processonrealestatemarketwemayidentifythreephases: 1) pre–investmentphase, 2) investmentphase, 3) operationalphase. Each of them may be divided into main activities, studies and analysis which are necessary before, during or after the investment process. While preparing detailed analysis,studies,plansandprojectsweusevarietyofsourcesofinformation.Someof the traditional sources bound to be replaced by modern GIS systems that combine different sources and make information accessible to an ordinary user. Table 8 presentspossibilitiesofGISsystemsimplementationondifferentstagesofinvestment process.Therearealsonotedneedsforimprovementanddevelopment. 81 Phase Table8.TheuseofGISsystemsondifferentstagesofinvestmentprocess. Mainstudies, analysisand activities Detailed analysis initial investment vision Pre‐investmentphase location analysis feasibility study, additional studies, assessment report market analysis competition analysis Investmentphase designing and planning negotiations, signing agreements, engineering, construction, receptionand commissioning organization of construction works market exposure Necessary information Traditional sourcesof information Implementation ofGISsystemsasa sourceof information usage,area, size,numberof storeys architectural concepts impossible landuse,main roads, neighbourhood, ownership, publicutilities landuse plans, general geographical map,land registry, basicmap possible GEOPORTAL, AtlasofWarmia andMazury SIPStawiguda, MSIPMO supplyand demand, numberof transactions, averageprice, typesofreal estate registryof realestate pricesand values,real estate agents needfor development differentiation, numberof similarobjects, distanceto similarobjects, ageofobjects official registers, basicmap, statistical registers, internet searchers possible GEOPORTAL, SIPStawiguda, MSIPMO(only onewithage) surface, topography, boundariesof plots, infrastructure, ownership, basicmap, cadastral map,land registry, landuse plans possible GEOPORTAL, AtlasofWarmia andMazury SIPStawiguda, MSIPMO geology, topography, watersupply, localizationof infrastructure networks, criteriaforreal estatedivisions basicmap, geological studies, geodetic recordsof public utilities,land useplans, local decisions needfor development supplyand demand, typesofreal estate registryof realestate pricesand values, agencies needfor development 82 Phase Mainstudies, analysisand activities Necessary information Traditional sourcesof information Implementation ofGISsystemsasa sourceof information landuse, neighbourhood, ownership landuse plans, geographical map,land registry, basicmap possible GEOPORTAL, AtlasofWarmia andMazury SIPStawiguda, MSIPMO designing and planning boundariesof plots, infrastructure, ownership, basicmap, cadastral map,land registry possible GEOPORTAL, SIPStawiguda, MSIPMO analysesof impacton other objects ownership, landuse, building conditions land registry, landuse plans possible GEOPORTAL, SIPStawiguda, MSIPMO Detailed analysis Operationalphase location analysis reconstruction, restructuring, expansion, innovation Source:WOLNYA.ownstudy. As we may notice from Table 8 most of the compared systems are able to replacesomeofthetraditionalsourcesofinformationondifferentstagesofinvestment process.Yetnoneofthemcontainsinformationthatwouldhelpinvestorcompleteall stepsofthisprocess.Insomecaseslikemarketanalysisandexposureororganization of construction works integrating information from different traditional and modern sources might be really helpful. It occurs that the younger GIS system the more adapteditistoinvestorsneeds.MSIPMOwhichwasintroducedrecentlyhasthewidest scaleofnecessaryinformation. 4.4.Conclusions Thecarriedoutcomparativeanalyzesallowthefollowingconclusions: 1) The local SDI portals are functionally adapted to the local users, are used by local public entities, investors and property owners. They contain data for localdevelopment. 2) The higher country administrative division level of portals including a wider rangeofdatafore.g.statisticalanalysis. 3) The regional SDI serve not only to provide spatial information to realize the vision of spatially enabled society, but also to the basic spatial analysis, that excel in the regional and provincial development. This phenomenon is beneficialandimportantforsustainabledevelopment. 4) Theuseofvarioussourcesofinformationondifferentstagesoftheinvestment process can significantly decrease the time of: obtaining the necessary information,analysisanddecision‐makingbyinvestors. 5) The SDI portals especially on provincial and community level should be adaptedtotheneedsofawiderrangeofusers,particularlyrealestatemarket investorsandwemaynoticethisdirectionaccordingtoconductedstudies. 6) According to analysis MSIPMO seems to be the SDI portal which meets the needsofrealestatemarketinvestors. 83 As the global society becomes more information relying, the concept of Spatially EnabledSocietybecomesmorepopular.Thatiswhythereisanecessityfordeveloping SDIportalsandadaptingthemforneedsofthesociety.Conductedresearchconfirms this argument as well as important role of SDI portals in creating sustainable development. 84 5.SOFTWARE,TOOLSANDINSTRUMENTSUSEDFORTHE PRESENTATION (VISUALIZATION) OF RESULTS OF SPATIALANALYSISINGIS Spatial information called the location, the geometric properties and spatial relationshipsbetweentheelements,whichcanbeappliedtothesurfaceoftheearth. Informationisobtainedbyinterpretationofspatialdata,geospatial,geographic(about geographical objects). Information achieved by interpretation of geospatial data (relatingtospatialobjectsrelatedtothe Earth'ssurface) is called Geoinformation. In contrast, harvesting, collecting, verifying , integrating , analyzing , and sharing the transformationofspatialdata,andmethods,technicalresources,includinghardware and software, spatial databases, organization and financial resources and the people involved in Geographical Information System . Technical and scientific discipline dedicated to the practical application of Geoinformation (Geoinformation systems) is geomatics(LEKSYKONGEOMATYCZNY,2002). The sudden development of information management occurred in the eighteenth century, but the first thematic maps were developed (automated productionofmaps)usingcomputersinthe50'softhepreviouscentury.Visualization ofthespatialinformationdataprocessingismadepossiblebythedevelopmentofthe Harvard Computer Graphics Laboratory and Analysis of spatial raster first model underthenameSYMAP.Inthe70'sabiginfluenceonthedevelopmentoftheSIPhad interest in environmental issues and ecology. ESRI was founded institute, where he developed the " ARC / INFO" is used to this day. The breakthrough was the introduction of space technology ‐ LANDSAT satellites. Satellite navigation system (GPS)graduallybecameasourceofspatialdatausedingeodesyandcartography.The next step was the emergence in the late 80's colour graphics. Then sought to obtain even better image quality, for this purpose developed software that uses the vector model. GISisacoordinatedsystemforobtainingandprovidinginformationaboutthe location,characteristics,andrelationshipsofobjectsthatcanbeidentifiedwithrespect to the ground. Object definition is understood very broadly and includes both permanent natural and artificial objects, as well as natural phenomena, social and economic.Thespaceinwhichobjectsareidentifiedcanbetwo‐dimensionalorthree‐ dimensional,dependingontheneedsofthesystem.Anotherdistinguishingfeatureof spatialinformationsystemsistheabilitytoanalyzeallowingtoobtainanswersabout therealworldmodelledbythesystemanditscartographicpresentation.Examplesof suchanalysismaybesearchingforobjectsthatmeetcertainconditions,measurements or determination of neighbourhood facilities. One of the basic elements of spatial information system is a database of spatial and descriptive information about the objects of the real world represented in the system. To be able to create it and to effectivelycarryoutallthetaskssetforthespatialinformationsystemisneededyet another of its components, which include the right software and hardware and humans.Speakingofhardware,wemeannotonlythehardware,butalsoperipheral devices used for data acquisition (surveying instruments, digitizers, scanners, autographs),andapparatusforgeneratingtabularandcartographicstudies(printers, plotters,imagesetter).Thefunctioningoftheinformationsystemistogatherrelevant data about real‐world objects that are of concern. These data describe the characteristics of individual objects, and are called attributes. The primary data collectionmethodsinclude(IZDEBSKI,2008): 85 Fieldmeasurements, Digitizationofmaps, Three‐dimensionaldigitizationofphotogrammetric Scanningandvectorizationofmaps. Methodsofphotogrammetryandremotesensing, Applicabilityofthesemethodsdependsonmanyfactors,includingthequality requirementsandthetechnicalandeconomicconditions.Othermethodswillbeused to acquire vector data, and other raster data acquisition. On the basis of information whichresultsfromtheexistenceofthePolishGUGiK,atleastseveralsystemstokeep thedataresource.WithallofthesesystemsarethemostpopularsoftwareGISArsGIS, EWMAPA,GeoInfoandGEO‐MAP(IZDEBSKI,2009). 5.1.Materialsandmethods GISsoftwarecanincludeanyprogramcontainingfunctionsentering,storing,analyzing andvisualizingdatageospatial.CurrentcommercialsystemsusingawiderangeofGIS softwarehavebeenappliedinmanyareasoflife,includinginindustry,science,urban planning, agriculture, etc. The data features or methods consist of or should the content of the thematic overlay, digital maps of the area, creating acomprehensive Geographical Information System. The rules for creating, qualifications adequate spatial characteristics, which are something that in modern thematic cartography is called geoinformation, andtodevelop amethodologyofoperationof such systems is one of the fundamental tasks of modern geodesy and cartography thematic. Use of cartographic materials and spatial information systems currently on the needs of a variety of spatial analysis, has always constituted, one of the fundamental tasks of geodesyandcartography,asascientificdisciplineandpracticalskills. Map presented in the form of a digital map of the area called the computer adigitalpresentationofreality.Vectormodelrepresentsobjectsusingpoints,linesor polygons (coordinates define the shape and location of the object), while the raster model represents reality, as the area is divisible into cells. The cell stores a numeric valueorthematicdata.GISApplicationsenableyoutoworkwithmapsbydisplaying data,symbolization,createandprint.Inaddition,youcanedit,analyzedataandcreate charts and reports. The main feature of GIS is to view, create, edit collection, data analysisandtransformation,andmapping. GISsoftwarecanbedividedasfollows: DesktopGIS‐programsusedtocreate,edit,manage,analyzeanddisplaygeospatial data. DBMS‐Spatialdatabasemanagementsystemsareusedtostoredata,butoftenalso theanalysisanddatamanagement. Servers mapping (WebMap) ‐ software for viewing and distribution maps on the internet. ServerGIS‐thesamefunctionsasadesktopGIS,justthatonline. WebGIS‐aprogramdesignedtodisplaydata,andincludinganalysisfunctionsand queries through Web browsers such as Google Maps ‐ display functions and queries, andthecreationandeditingofdata(buildyourownmaps) MobileGIS‐softwareformobilephonesandportablecomputers The result is the transformation of the spatial analysis of geo‐information in thematic maps, which should feed into existing informationsystems. Development of new layers is possible using software that can be divided according to the general schemeofFig. 49. 86 website commercial software map layer On‐Line Open Source Software Software Fig.49.SchematicGISsoftwaredivisiontocreatethematiclayers. Source:OGRYZEKownstudy. TosupportGissoftwareskillsarerequired: editthedatabases(knowledgeoftheStatisticasoftware,database,Access) Operatingoriginalprograms,interfaces,toolsandscripts Mapping(knowledgeofMapInfosoftware,EWMAPA,ArcGIS,etc.) OperatingInformationSystems serviceportals workinginthecloud,theuseofavirtualdisk BIELECKA(2006)notedthatinGISvisualizationprocessisseenasaprocessof spatial data from the database to graphically visible on the screen. Visualization is thereforeaperiodoftransitionandthecentreofeachGISsoftwareisthedatabaseand the quality of the data depend on the results obtained. Input modules databases supportaverydifferentprojectplanning,andmodernizationoftheexistingprovisions ofthemapsisdonebyselectingthenecessarygeo‐informationpresentedinathematic layer.Presentationoftheinformationcontainedinthedatabasemaybebyselectionof thelayerdatabyattributessuchas:thenameorpositionoftheobjectsthatisselected fromoneormorethematiclayersbasedontheirspatialrelationshipwithobjectsother layer.Theuseofthedatabasecanbeby: firstmethod‐thedevelopmentofaninterfaceindependentspecialist secondmethod‐youcansavetheresultsintheformofscanneddocuments thirdmethod‐tosupplementthedatabase(tablesbemerged) However,youshouldpayattentiontohowmanyobjectsarerelatedtoother objectsinthedatabase.Joinsandrelationshipsarebasedonthekeyfield,sothefield names do not have to have identical names, but the same attribute values in both tables.ItisnotrecommendedtouseObjectIDandcodevaluesTERYT.Therefore,the attributevaluesmustbeidenticalandtheprimarykeydatatypesmustbecompatible. Fig. 50 shows an example where incompatible database version was transposed possibletojointables.ThedatabasecamefromARMAanddataitusedtovisualizethe softwareArcGISabsorptionanalysisforEUprogramsinPoland. 87 Fig.50.TransformationintoacompatibledatabasesoftwareGIS. Source:OGRYZEKonthebasisofdataARiMR2012. Thenextimportantelementofvisualizationissymbolization,i.e.information about the objects expressed by the graphics (colour, shape, size, pattern, direction, etc.),possibletointerpretthelegend.Symbolsaredividedonthesignatureline,fill‐ youcanuseapresetorcreateyourown.Itappliestobothqualitativeandquantitative. Therearesymbolizationcolourscale,signaturegradingandproportionate,mapcrotch andgraphs.Dependingontheclassificationmethodscanbespecifiedintervalssuchas: natural,equal,etc. 5.2.Resultsanddiscussion Forseveralyears,steadilyincreasingpopularityofspatialinformationsystems,which we call the systems acquisition, processing and sharing of data containing spatial informationandtheaccompanyingdescriptiveinformationabouttheobjectsfeatured intheportionofthespacecoveredbytheoperationofthesystem.(GAŹDZICKI,1990). AvailableInformationSystemscitiesandcounties,andportals,asWeb‐basedversions of GIS software allow you to perform analysis and presentation (visualization) the results of spatial analysis. Using Geographic Information Systems for the needs of a variety of spatial analysis and modernization of existing records in the free software maps on‐line is via a web browser. Fig. 51 Changed practical application of Web GIS softwareforvisualizingtheresultsofdifferentstudies: visualization of "a" Survey of economic activity employed on farms. Kart diagram shows the dependence of the size of farms andthe amountof work performed in theGeostatisticPortal. visualizationof"b"‐MapoftheLocalPlanobtainedfromtheMunicipalInformation System Olsztyn City used in the preparation of the spatial impacts of financial, environmentalchangepartsoftheLocalDevelopmentPlanOlsztyn. 88 visualization“a”visualization“b” Fig.51.VisualizationoftheresultsofresearchinsoftwareWebGIS. Source:OGRYZEKownstudy. AsimilartoolisasoftwareenvironmentGISOn‐Line,whichisusuallypaidfor availabledataforanalysisandanalysistoolsavailableinthecloudarefree.However, there are geographic information systems offering free access to the software GIS, whereregistereduserscanperformavarietyofspatialanalysisintheenvironmentGIS andtheresultsintheformofmapsstoredonyourowncomputerprovidedyouhave Internetaccess.AnexamplemightbeaportalE‐government,whichdevelopedrapidly sincearound2003,andsince2007thedataassociatedwithurbanspacebecameapart of it . In time he became one of the world's best public services offered to residents. City of Warsaw has a similar service mapa.um.warszawa.pl where you can find local spatial development plans, plots, offices locations precincts and a few other things. However,thereisnocurrentabilitytoperformspatialanalysisanddatacollectionin theformofanExcelfiletoitsownanalysisinothersoftware.OnFig.52providedan exampleoftheanalysisperformedfordemographicsSeoulportalE‐government. 89 Fig.52.AdemographicanalysismadeinthesoftwareGisOn‐Line Source:http://gis.seoul.go.kr/ Another way to visualize the results are applications of mobile GIS. These applications are used in mobile phones and are associated with integrated and intuitive navigation systems designed for specific groups, e.g. runners, boaters or motorists. AnotherexampleofawidelyusedGISsoftwarecanbeSailCruiser(Fig.53)is aunique navigation program designed for sailors. His versatility and intuitiveness makes working with him is easy and at the same time professional. Leading the navigation of any boat quickly and accurately, we can manage all the necessary information. 90 Fig.53.TheuseofGIStechnologyinsailing Source:http://www.galeriagps.pl The last group GIS software environment are desktop applications. Can be divided into free and commercial, that is, to which access is possible after buying alicense. Quantum GIS (QGIS) is a user friendly open and free (Open Source) GIS software,whichrunsontheplatformsofGNU/Linux,Unix,MacOSXandMSWindows. QGIS is available for free under the GNU General Public License. QGIS allows you to browse, view, edit and create vector data, raster, and database in different formats, includingESRIshapefileformat,MapInfotab,spatialdataPostgreSQL/PostGIS,vector and raster layers GRASS or GeoTiff. Through integration with QGIS GRASS gives the abilitytoperformadvancedanalysis.ItalsohastheabilitytodisplaylayersOGC:WMS andWFS.QGISfunctionalitycanbeeasilyexpandedbyaddingoreventhecreationof the so‐called. plug‐ins, tailored to individual needs. Plug‐ins are managed by the Manager plug‐in, and written in the language Python or C ++. The program already contains a number of plug‐ins designed, inter alia, to import data from text files, transfer GPS device or calibrating grid (NOWOTARSKA, 2009). ESRI ArcGIS is the most currently used GIS in the world (in 2004 there were 160,000 of his license and have used it more than a million people). ArcGIS consists of three separate programs. ArcMap is used for editing, visualization and analysis of product development. Combined with the ArcToolbox contains tools for data analysis. ArcCatalog acts as aWindows Explorer for geoinformation, and with ArcToolbox tools creates a spatial datamanagementenvironment.Anumberofadditionalenhancementsenablesspecific types of analysis: Spatial Analyst Raster data analysis; Network Analyst analysis of network data; Geostatistical Analyst using geostatistics methods for estimating the continuous fields (values defined at each point in space) of data points, and the 3D Analyst analysis of data in three dimensions. The whole system ArcGIS is offered at three levels. ArcView is the cheapest and poorest version, ArcEditor has full editing capabilitiesofdata,andArcInfofullofopportunitiesforbotheditorialandanalytical. The program allows you to create applications integrated with it as a result, there is anumberofspecializedtoolsthatarecreatedinavarietyofresearchcentersandthe 91 most available free of charge for research purposes (URBAŃSKI, 2008). Pay special attention to the possibility of 3D GIS, which differs from 2D that have primarily coordinates, heights, but also expanded the range of sources, e.g. for satellite photographs.AnotherimportantaspectistheabilitytoautomatetasksintheArcGIS onewaytoachievethiseffectistheuseofscripts.ArcGISscriptinglanguageisPython. Theinterdisciplinarynatureof environmentalGISallowstheuseoftoolsforanalysis and visualization of results of research projects in virtually every area of life. Therefore,thetargetgroupofthesoftwareisnotonlycommercialusersbutalsothe research leading recipient. Regardless of the program, i.e., ArcGIS, MapInfo, EwMapa, AutoCad, etc. They are used, among other things, as a means to visualize the test results. The basic element of the systems are interfaces. These are independent programstographicaldataconnectionwiththedescriptive(IZDEBSKI,2009): 1.Queryinterface‐forinformationaboutthespecifiedobject. 2.Loopbackinterface‐anindicationoftheobjectsthatsatisfysomecondition.Itmay takeplaceindifferentways:ashachure,marker,orbychangingthecolor. 3.Syncinterface‐allowsyoutosynchronizethedatabaseobjectsfromthedescriptive part,whichensurestheconsistencybetweenthe internalsystemobjectsand externaldatabase. 4.InterfaceSpecialist‐tailoredtoasingledatabase,e.g.EWOPIS(thedescriptivepart of the land and buildings) that when you point the plot displays the data contained in this system. Another example would be the interface to the systemCENTRE,allowsobtainingmorecompleteinformationabouttheOpera andKERG‐in. 5.GeneralInterface‐ UniversalODBCinterface,whichallowsyoutoconnecttoanydatabaseforwhichan ODBCdriverexists,suchasORACLE,MSACCESS DESCRIPTION universal interface that allows you to link with any object descriptionandphotos, DOCUMENT universal interface that allows you to link with any object scanned documents(e.g.acombinationofcontrolpointstopographicaldescriptions). Fig.54showsthepracticalapplicationofdesktopsoftwareforvisualizingthe resultsofdifferentstudies: visualization "a" ‐ examine the need for planning works in the municipality of Ghaziabad.Kartdiagramshowsthenumberofzoningandlanddivisiononzoning decisionsanddecisionsdeterminingthelocationofapublicinvestment. visualizationof "b" ‐ study theabsorption offunds for EUaction inareas Warmia and Mazury. This map shows the spatial distribution of the "afforestation of agriculturalland." visualization "c" ‐ test the impact assessment of highway on the environment. On the map filter applied to the visualization of protected areas Nature 2000 as ajustificationforavariantofthemotorway. visualization"d"‐studytheimpactofEUProgrammesonecologicalcharacteristics in Poland. For kart diagram shows the relationship between the amount of the grants received (colour scale) and the coefficients (bar charts) urbanization and agriculturalqualityinPoland. 92 Fig.54.VisualizationoftheresultsofresearchinadesktopsoftwareGIS. Source:OGRYZEKownstudy. 6.Toolbox‐theycanbedividedintothosethatchangegeometryandthatchangeonly those attributes. The second group includes those options that perform a table attributes such as calculate field, summary statistic and select by attributes or selects by Location. Tools and functions of the Tables of the group have been convertedinFig.55whereforthehelpofapplyingtwolayersgetthehelpofatool for Analyses Tools \ Overlay \ erase, a new layer having attributes and geometrylayerscombined. Fig.55.Toolboxapplyforanewlayer. Source:OGRYZEKownstudy. 93 AnotherexampleofworkingwithGIStoolsistoperformtheanalysis.OnFig.56was testedusingbufferzonesinGISsoftware,theimpactofthreefactors:thedistancefrom the centralsite, area,access roads tothecity. Converted into vectormapsand raster mapsusingrasteralgebramaps,GIStechnologywasachievedinthefinalversionofthe mapofpotentialspatialdevelopmentofthemunicipality. Fig.56.AnalysisofthepotentialofthemunicipalitymadeinArcGISusingmapalgebra. Source:OGRYZEKownstudy. 94 7.Ownscripts‐isasetofpossibleprogramminglanguagesforuseinGIStechnology. Therearesolutions: •Languagescompiled‐Fortran,C,C++ •Scriptinglanguages‐Matlab,R,IDL •Python Python has gained the greatest popularity because of the rich set of diverse libraries, natural language, and the submission of many libraries for purposes other thanresearch.ETHERINGTON(2011)whileworkingonthegeneticsofthelandscapefor thefirsttimewassurprisedthattherewasnowaytovisualizethedifferencespairsof genetic kinship. To fix this, wrote the script kinship links, which will take a series of points and a matrix text file, kinship, and will produce a polyline shapefile links betweeneachcombinationofpairsofpoints.AnotherexampleshownintheFig.57is thedevelopmentofwindroseforthepresentationofwinddirection.Theprogramis writteninPythonrunsasatoolinArcGIS. 95 Fig.57.WindPROmeteodatareport. Source:KOPEĆA. 5.3.Conclusions GISisasystemofacquiring,processingandsharingofdataduetosystemusers,which enables youto analyzethechange in time andspace phenomenaofsocio ‐ economic scenario building and forecasting and making decisions based on them. The result of multi‐criteria analysis model solutions space management is the transformation of Geoinformation in thematic maps. The proposed software can be used on a different 96 scale and level of detail on a variety of spatial analysis. Entered into a GIS database modulessupportavarietyofprojectplanningandaretargetedtoaspecificaudience. ThemaintaskofthesoftwareGISvisualizationtestresultsanalysis.Theapplicability ofvariousinstrumentsGISdependingonyourneeds,experience,financialcapacityand performance objectives determine the target group and indicate the need to use a specifictypeofsoftware.However,theinterdisciplinarynatureofGISmakesuscloser andclosertothesituationthattheknowledgeanduseofGISsoftware‐thisisstandard inallareasoflife. 97 REFERENCES ALLARD E., 1993. Having, Loving, Being. An Alternative to the Swedish model of welfare research[in:]M.Nussbaum,A.Sen,TheQualityofLife,Oxford,ClarendonPress. Oxford AL RAWASHDEH BALQIES SADOUNS.,AL FUKARAA.,2012.CADfileconversiontoGISlayers:Issues and solutions. In Computer, Information and Telecommunication Systems (CITS),2012InternationalConferenceon(pp.1‐6).IEEE. ANGUIXA.,DÍAZL.2008.gvSIG:AGISdesktopsolutionforanopenSDI.JournalofGeography andRegionalPlanning,1(3):41‐48. BAJTEKM.,2007.Przegląd zastosowań GIS. 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Webpages: http://gisplay.pl/gis/krajowy‐system‐informacji‐przestrzennej.html15 http://geoportal.gov.pl/accesson17.07.2014 http://mapy.geoportal.gov.pl/imap/?gpmap=gp0&actions=acShowServices_KAT ASTER&locale=enaccesson17.07.2014 http://atlas.warmia.mazury.pl/mpzp/accesson3.03.2015 http://msipmo.olsztyn.euaccesson20.03.2015 http://sip.stawiguda.placcesson5.03.2015 104 LISTOFFIGURES Fig.1.AnexampleofaBDOT10kdatabaseinthecartographicform.....................8 Fig.2.Thediagramofdataqualitycontrolprocess(part).........................................13 Fig.3TheconceptualmodelofdataqualityBDOT10k...............................................16 Fig.4.AttributequerytoolinOpenJUMP..........................................................................30 Fig.5.ValidateSelectedLayerstoolinOpenJUMP........................................................30 Fig.6.PolygonizetoolinOpenJUMP....................................................................................31 Fig.7.JoinAttributesSpatiallytoolinOpenJUMP.........................................................31 Fig.8.SpatialJointoolinOpenJUMP...................................................................................32 Fig.9.SelectionQuerytoolingvSIGCE..............................................................................33 Fig.10.LayersthatwillbeincludedinthetopologyingvSIGCE............................34 Fig.11.TopologicalrulestobeverifiedingvSIGCE.....................................................34 Fig.12.GeoprocessingtoolCleaningvSIGCE.................................................................35 Fig.13.GeoprocessingtoolBuildpolygonsingvSIGCE..............................................36 Fig.14.SpatialjointoolingvSIGCE.....................................................................................36 Fig.15.GeometrytypesavailabletoloadinQGIS..........................................................37 Fig.16.ExtractbyattributetoolinQGIS............................................................................38 Fig.17.TopologyRuleSettingsinTopologyCheckerplugininQGIS....................38 Fig.18.TopologyCheckerplugininQGIS..........................................................................39 Fig.19.PointsinPolygontoolinQGIS................................................................................39 Fig.20.JoinAttributesbyLocationtoolinQGIS.............................................................40 Fig.21.Nautizx7,GarminGPSmap62st,GarminGPSmap76..................................46 Fig.22.Municipalitieszonaldivision..................................................................................47 Fig. 23. Dasymetric cartogram of development intensity in the municipality area....................................................................................................................................................48 Fig.24.MapofeconomicactivityinZielonkicommune..............................................49 Fig.25.Determinationoftheparcelswithinthescopeofresidentialareas.......50 Fig.26.Buffersandparcelslocatedintheirinfluenceonplots................................51 Fig. 27. The creation of the resulting layer for the betterment levy due to the constructionoftechnicalinfrastructure............................................................................51 Fig.28.Layersofbuildings,technicalinfrastructure,fittingsandprecincts......52 Fig.29.ShareofdevelopedplotsinLocalDevelopmentPlan...................................53 Fig.30.ShareofdevelopedplotsinLocalDevelopmentPlan...................................54 Fig.31.TheratiooftheinvestedareasurfacetothoselabeledMNintheLocal SpatialDevelopmentPlanindifferentvillages...............................................................55 Fig. 32. Percentage chart of easy access of residential buildings to the infrastructurebyvillages.........................................................................................................56 Fig.33.Coverofelaborationon„SpatiallyEnabledSociety”.....................................59 Fig.34.WarmiaandMazuryRegion....................................................................................61 Fig.35.AdministrativedivisionofRepublicofPoland–asatJanuary1,2011.61 Fig.36.InterfaceofPolishGeoportal..................................................................................68 Fig.37.Cadastraldatainmappingtab................................................................................68 Fig.38.AtlasofWarmiaiMazury.........................................................................................70 Fig.39.ChosenlayeronaMSIPMOview‐orthophotomapfrom2009................71 105 Fig.40.ChosenlayeronaMSIPMOview–precinctKortowo‐situationofplots andbuildings.................................................................................................................................72 Fig.41.DescriptionofachosenplotattachedtothecadastralmaponMSIPMO view...................................................................................................................................................72 Fig.42.DescriptionofachosenpublicutilityonaMSIPMOview..........................73 Fig.43.VarietyofdetailedmapsattachedtoMSIPMO................................................74 Fig.44.ChosenlayersonaSIPStawigudaview‐boundariesoflanduseplans andplots..........................................................................................................................................75 Fig. 45. Chosen layers on a SIP Stawiguda view ‐ topographic map and boundariesofplots.....................................................................................................................76 Fig.46.ChosenlayersonaSIPStawigudaview‐orthophotomapandlanduse plans..................................................................................................................................................76 Fig.47.ThescopeofdataratingoftheSDIportals.......................................................79 Fig.48.ThefunctionalityratingoftheSDIportals........................................................81 Fig.49.SchematicGISsoftwaredivisiontocreatethematiclayers........................87 Fig.50.TransformationintoacompatibledatabasesoftwareGIS.........................88 Fig.51.VisualizationoftheresultsofresearchinsoftwareWebGIS....................89 Fig.52.AdemographicanalysismadeinthesoftwareGisOn‐Line.......................90 Fig.53.TheuseofGIStechnologyinsailing.....................................................................91 Fig.54.VisualizationoftheresultsofresearchinadesktopsoftwareGIS.........93 Fig.55.Toolboxapplyforanewlayer................................................................................93 Fig.56.AnalysisofthepotentialofthemunicipalitymadeinArcGISusingmap algebra..............................................................................................................................................94 Fig.57.WindPROmeteodatareport...................................................................................96 106 LISTOFTABLES Table1.Theresultsofthedataqualityevaluation........................................................17 Table2.ThevalueofRIdependingonthedimensionofthematrix......................18 Table3.Thepointvaluesofdataqualityevaluationandthevaluesofcalculated estimators.......................................................................................................................................19 Table4.ListofterritorialunitsofPoland‐asat01.01.2015....................................62 Table5.Spatialdatathemes...................................................................................................64 Table 6. Scope of the data made available in SDI portals by the annexes of INSPIREDirective........................................................................................................................77 Table7.FunctionalityofselectedSDIportals.................................................................79 Table8.TheuseofGISsystemsondifferentstagesofinvestmentprocess.......82 107 NOTESONTHEAUTHORS AgnieszkaDawidowicz,Ph.D. DepartmentofRealEstateResources UniversityofWarmiaandMazury Olsztyn,Poland e‐mail:[email protected] SCIENTIFICEDITOR An Assistant Professor working in Department of Real Estate Resources, Faculty of Geodesy, Geospatial and Civil Engineering. She holds a PhD in Real Estate Cadastre from the University of WarmiaandMazury.ShealsoholdsdegreesinEngineering(Land Management)Science(GeodesyandCartography)fromthesame institution.FromtheUniversityofWarmiaandMazuryinOlsztyn sheholdsauniversityteachingqualification.Herresearchfocuses on technological and functional development of cadastres and land administration systems. She is currently working on methodologyfortestingtheflexibilityofthelandadministration systems. She is an expert in GIS and other spatial information systems. She participated in scientific and teaching trainings in Germany (Leibnitz University of Hannover) and in the Netherlands (University of Twente). She is also a scientific secretary of the board and the editorial team of Journal “Acta Scientiarum Polonorum Administratio Locorum” (eng. Real Estate Management).AgnieszkaDawidowiczactsasarevieweronmany journalandconferenceseries. AdaWolny,Ph.D. DepartmentofRealEstateResources UniversityofWarmiaandMazuryinOlsztyn Olsztyn,Poland e‐mail:[email protected] SCIENTIFICEDITOR An Assistant Professor working in Department of Real Estate Resources, Faculty of Geodesy, Geospatial and Civil Engineering. SheholdsaPhDinRealEstateManagementfromtheUniversity of Warmia and Mazury. She also holds degrees in Engineering (LandManagement)Science(GeodesyandCartography)fromthe sameinstitution. Her research focuses on application of GIS for real estate management and regional development. She tests capabilities of SDI systems and variety of GIS tools for improving management ofsuburbanareas.SheisanexpertinGIS.Asalicensedrealestate brokersheidentifiesneedsofdifferentparticipantsofrealestate market. Ada Wolny is an author or co – author of scientific publications.SheisalsoamemberofPolishRealEstateScientific Society and she acts as a reviewer on journal and conference series. 108 PiotrCichociński,Prof.Ph.D DepartmentofGeomatics AGHUniversityofScienceandTechnology Kraków,Poland e‐mail:[email protected] Piotr Cichociński is employed at the Department of Geomatics, Faculty of Mining Surveying and Environmental Engineering, AGH University of Science andTechnologyinKraków. Since2005,themainfieldofhisscientificandresearch activity has been related to the broadly defined use of geographicinformationsystems(GIS)intherealestate economy(andthepropertyvaluation,inparticular).In addition,hisresearchinterestsincludestandardization and normalization in GIS, geoinformation modelling anddesignofspatialdatabases,webmapping,network analysis, volunteered geographic information. He also focusesonpromotionoftheideaofopendataandfree software. MonikaMika,Ph.D. DepartmentofLandSurveying UniversityofAgricultureinKrakow Kraków,Poland e‐mail:[email protected] Monika Mika is employed at Department of Land Surveying, Faculty of Environmental Engineering and Land Surveying, University of Agriculture in Krakow. Deals mainly with research and teaching activities in thefieldofseveralthematic: The cadastre, the cadastre history, genesis of the cadastre in Poland and worldwide, modernization ofthecadastre,thecadastralinformation. TheLandandMortgageRegistersysteminPoland– analysis of existing state in terms of the flow of informationabouttheareaandthecreationofreal estatecadastre. The use of GNSS measurement techniques and GIS tools in the creation of thematic maps and other cartographicelaborations. Author or co‐author of scientific publications in the field of geodesy and cartography and real estate management. 109 MarekOgryzek,Ph.D. DepartmentofPlanningandSpatialEngineering UniversityofWarmiaandMazury Olsztyn,Poland e‐mail:[email protected] Marek Ogryzek is employed at the Department of Planning and Spatial Engineering Faculty of Geodesy and Land Management, University of Warmia and MazuryinOlsztyn,Poland. His research interests concern mostly GIS. Still in his research there are topics like activity of Agricultural Real Estate Agency, optimal development, spatial planning and EU programs. His field of research includesalsotheusestatisticandgeostatisticmethods. TomaszSalata,Ph.D. DepartmentofLandManagementandLandscape ArchitectureUniversityofAgricultureinKrakow Kraków,Poland e‐mail:rmtsalat@cyf‐kr.edu.pl TomaszSalataisacademicemployedatDepartmentof Land Management and Landscape Architecture, Faculty of Environmental Engineering and Land Surveying, University of Agriculture in Krakow. He mainly deals with spatial information systems (construction and operation in the network) used in thefieldsofenvironmentalprotection,registrationof landscape events and phenomena and modelling of spatial and descriptive data in information systems. Heistheauthorofmanyscientificpublicationsinthe field of geodesy and cartography, spatial information systems,GISanddatamodelling.Inhisoutputhealso has many years of experience in the field of informatics implementations in institutions of local government administration in the field of communal space management, municipal property, mailing systemsandothers. 110 MonikaSiejka,Ph.D. DepartmentofLandSurveying UniversityofAgricultureinKrakow Krakow,Poland e‐mail:rmwiech@cyf‐kr.edu.pl MonikaSiejkaisaresearchandteachingworkerinthe DepartmentofGeodesyoftheFacultyofEnvironmental Engineering and Land Surveying at the University of AgricultureinKrakowandrealestateappraiser.Sheis the author and co‐author of numerous publications in journals of national and international range on real estate market, real estate management, real estate cadastre, databases, the concept of real estate informationsystems.Sheistheco‐authorofatextbook foruniversitystudentsandofamonographs.Sheleads the research on the use of multi‐criteria methods for theanalysesoftherealestatemarketandoptimization of the choice of the location for the investment of supralocal character. She is also active in the professionalfieldasarealestateappraiserandmember of Malopolskie Association of Property Valuers and PolishFederationofPropertyValuers. MarekŚlusarski,Ph.D. DepartmentofLandSurveying UniversityofAgricultureinKrakow Krakow,Poland e‐mail:rmslusar@cyf‐kr.edu.pl Graduate of Land Surveying College in Lublin (1987) and the Surveying and Mapping at the University of Agriculture in Krakow (1992). Research andteachingworkerintheDepartmentofGeodesyof the Faculty of Environmental Engineering and Land Surveying at the University of Agriculture in Krakow since1992.Academicdegreeofdoctorofagricultural sciences in shaping the environment (2002) obtained for the work. „Methods of obtaining and selection of data in order to create a uniform system of information on real estate”. Author and co‐author of severaloriginalresearchpaperspublishedinnational and international journals. Scientific interests: informationsystems,inparticular,investigationofthe quality of data in geospatial systems and modern cadastre.Amemberoftheselectioncommitteeforthe professional certificates in the field of geodesy and cartography. 111