geoinformation technology and data models

Transkrypt

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.
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.
Fig.7.JoinAttributesSpatiallytoolinOpenJUMP.
31
Fig.8.SpatialJointoolinOpenJUMP.
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.
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.
Fig.11.TopologicalrulestobeverifiedingvSIGCE.

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.
35
Fig.13.GeoprocessingtoolBuildpolygonsingvSIGCE.
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.
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.
37
Fig.16.ExtractbyattributetoolinQGIS.
Fig.17.TopologyRuleSettingsinTopologyCheckerplugininQGIS.
38
Fig.18.TopologyCheckerplugininQGIS.
Fig.19.PointsinPolygontoolinQGIS.
39
Fig.20.JoinAttributesbyLocationtoolinQGIS.
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.
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.
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.
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.
Fig.27.Thecreationoftheresultinglayerforthebettermentlevyduetothe
constructionoftechnicalinfrastructure.
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.
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.
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.
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.
Fig.41.DescriptionofachosenplotattachedtothecadastralmaponMSIPMOview.
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.
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.
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.
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.
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.
93
AnotherexampleofworkingwithGIStoolsistoperformtheanalysis.OnFig.56was
testedusingbufferzonesinGISsoftware,theimpactofthreefactors:thedistancefrom
the centralsite, area,access roads tothecity. Converted into vectormapsand raster
mapsusingrasteralgebramaps,GIStechnologywasachievedinthefinalversionofthe
mapofpotentialspatialdevelopmentofthemunicipality.
Fig.56.AnalysisofthepotentialofthemunicipalitymadeinArcGISusingmapalgebra.
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
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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
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
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
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
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.
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.
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

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