Cerba ppt gi2011-harmonization-of-spatial-planning-data_final
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Cerba ppt gi2011-harmonization-of-spatial-planning-data_final

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GI2011-X-border-SDI/GDI-Symposium, 23..5.2011: Bad Schandau (SAX)

GI2011-X-border-SDI/GDI-Symposium, 23..5.2011: Bad Schandau (SAX)
[ 11. Sächsisches GIS-Forum ]
24.5.2011: Decin (CZE)
[ 1. Bohemian#Saxonian GIS-Forum ]

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Cerba ppt gi2011-harmonization-of-spatial-planning-data_final Cerba ppt gi2011-harmonization-of-spatial-planning-data_final Presentation Transcript

  • Spatial Data HarmonizationOn how to realize it in Spatial Planning Karel JANECKA, Otakar CERBA, Karel JEDLICKA, Jan JEZEK University of West Bohemia http://portal.sdi-edu.zcu.cz 1
  • Harmonization and its role in spatial planning
  • Spatial data harmonization• Providing access to data through network services in a representation that allows for combining it with other INSPIRE data in a coherent way by using within the European Spatial Data Infrastructure (ESDI) a common set of data product specifications.• This includes agreements about coordinate reference systems, classification systems, application schemes, etc. http://portal.sdi-edu.zcu.cz 3 View slide
  • Spatial data harmonization http://portal.sdi-edu.zcu.cz 4 View slide
  • Spatial data harmonizationComponents of harmonization:• INSPIRE principles • Metadata• Reference model • Maintenance• Data translation model • Quality• Portrayal model • Data transfer• Application schemes and • Derived reporting & multiple feature catalogues representations• Dictionaries • Consistency between data • Data Capturing http://portal.sdi-edu.zcu.cz 5
  • An example of Spatial Data Harmonization using PostgreSQL + PostGIS http://portal.sdi-edu.zcu.cz 6
  • HARMONIZATIONSource data model Target data model Zemgale urban CORINE land planing cover(specific data model) Geometry Reclassification HARMONIZATION http://portal.sdi-edu.zcu.cz 7
  • HARMONIZATION STEPS Definition of reclassification rules Data reclassification Union of touching geometries in same class Transformation from multipolygon to polygons http://portal.sdi-edu.zcu.cz 8
  • HARMONIZATION STEPS IN Definition of reclassification rules → Create mapping table Data reclassification → SQL JOIN using mapping table Union of touching geometries in same class → Spatial aggregate function Union Transformation from multipolygon to polygons → Spatial function dump for converting multipolygon to polygon http://portal.sdi-edu.zcu.cz 9
  • ZEMGALE DATA MODELAtribute Field Explanation TypeVEIDS Planed land use type (see possible values down) Text 50INDEKSS Area with speciffic restrictions Text 10PLATIBA Area(m2) Long IntegerTER_VIEN territorial unit Text 50ADM_TER administrative area Text 50LAYER Layer number in CAD systems Text 50PIEZIMES notes Text 100 http://portal.sdi-edu.zcu.cz 10
  • LAND COVER DATA MODEL CORINE land http://portal.sdi-edu.zcu.cz 11 cover
  • RECLASSIFICATION RULES ZEMGALE CLASSIFICATION → CORINE NOMENCLATURE1 DzM Low-rise residential dwellings → 11 Urban fabric2 DzV Multi-residential dwellings → 11 Urban fabric3 P Public Building → 11 Urban fabric4 RR Production facilities and warehouses → 121 Industrial or commercial units5 RD Mining area → 131 Mineral extraction sites6 T Technical Building → 12 Industrial, commercial...7 Ū Waters → 5 Water bodies8 M Forests → 31 Forests9 ZĪ Outstanding foliage sites No corresponding class10 ZC Other groomed greenery space → 141 Green urban areas11 L Rural Land → 2 Agriculture areas12 No data No corresponding class http://portal.sdi-edu.zcu.cz 12
  • Database tables plan_zonejums_part – orginal dataset (imported from shapefile) lc_original - original classification for land cover lc_standardized – standardized classification for land cover standardized_to_original – classification mapping plan_zonejums_part_harm – reclassified data http://portal.sdi-edu.zcu.cz 13
  • Database schema http://portal.sdi-edu.zcu.cz 14
  • Harmonization query We have: plan_zonejums_part, lc_original, lc_standardized, standardized_to_original We need: plan_zonejums_part_harm SQL Query:CREATE TABLE plan_zonejums_part_harm AS SELECT nextval(gid_seq::regclass) AS gid, orig.gid AS original_gid, orig.the_geom, orig.veids, orig.standardized_cl, lc_standardized.lc_class FROM lc_standardized, ( SELECT plan_zonejums_part.gid, plan_zonejums_part.the_geom, plan_zonejums_part.veids, standardized_to_original.standardized_cl FROM plan_zonejums_part RIGHT JOIN standardized_to_original ON plan_zonejums_part.veids = standardized_to_original.original_cl) orig WHERE orig.standardized_cl::text = lc_standardized.classification::text; http://portal.sdi-edu.zcu.cz 15
  • Database tables plan_zonejums_part – orginal dataset (imported from shapefile) lc_original – original classification for land cover lc_standardized – standardized classification for land cover standardized_to_original – classification mapping plan_zonejums_part_harm – reclassified data http://portal.sdi-edu.zcu.cz 16
  • RECLASSIFIED DATA SET http://portal.sdi-edu.zcu.cz 17
  • Next step – union of adjacent features with same classSELECTNEXTVAL(gid_seq::regclass)::integer AS gid,(ST_Dump(foo.the_geom)).geom AS the_geom, standardized_cl,lc_class FROM ( SELECT ST_union(the_geom) AS the_geom, standardized_cl, lc_class FROM plan_zonejums_part_harm WHERE the_geom IS NOT NULL GROUP BY standardized_cl, lc_class) AS fooWHERE foo.the_geom IS NOT NULL; http://portal.sdi-edu.zcu.cz 18
  • Final dataset http://portal.sdi-edu.zcu.cz 19
  • An example of Spatial DataHarmonization using commercial GIS software - ArcGIS http://portal.sdi-edu.zcu.cz 20
  • Using ArcGIS Model Builderfor transformations between data models P4A Land Cover example http://portal.sdi-edu.zcu.cz 21
  • Understanding target data• Plan4all Land Cover data model http://portal.sdi-edu.zcu.cz 22
  • Understanding target data • Plan4all Land Cover data model – ERA diagram of database schema in ESRI Geodatabase. Geometry Polygon Coded value domain Simple feature class Contains M values No CorineLandCoverCode LandCoverStandardisedArea Contains Z values Yes Description CorineLandCoverCod Allow Prec- Field type e Field name Data type nulls Default value Domain ision Scale Length Split policy String Relationship class Merge policy Default value OBJECTID Object ID StandardisedArea_OriginalArea Default value Code Description SHAPE Geometry Yes Type Simple Forward label OriginalArea 1 Artificial surfaces inspireId String Yes 15 Cardinality One to many Backward label StandardArea 2 Agricultural areas source String Yes 50 Notification None 3 Forest and semi natural areas classification String Yes CorineLandCoverCode 21 Origin feature class Destination feature class 4 WetlandsbeginLifespanVersion Date Yes 0 0 8 Name StandardArea NameOriginalArea 5 Water bodies endLifespanVersion Date Yes 0 0 8 Primary key inspireId 11 Urban fabric SHAPE_Length Double Yes 0 0 Foreign key inspireId Industrial, commercial and 12 SHAPE_Area Double Yes 0 0 No relationship rules defined. transport units Mine, dump and construction 13 sites Artificial, non-agricultural 14 vegetated areas Geometry Polygon 21 Arable land Simple feature class Contains M values No 22 Permanent crops LandCoverOriginalArea Contains Z values Yes 23 Pastures Allow Prec- 24 Heterogeneous agricultural areas Field name Data type nulls Default value Domain ision Scale Length 31 Forests OBJECTID Object ID 32 Scrub and/or herbaceous SHAPE Geometry Yes Open spaces associationsno vegetation with little or 33 inspireId String Yes 15 vegetation 41 Inland wetlands source String Yes 50 42 Maritime wetlands classification String Yes 21 51 Inland waters classificationLink String Yes 50 52 Marine waters SHAPE_Length Double Yes 0 0 111 Continuous urban fabric SHAPE_Area Double Yes 0 0 112 Discontinuous urban fabric 121 Industrial or commercial units Road and rail networks and 122 associated land 123 Port areas 124 Airports 131 Mineral extraction sites 132 Dump sites 133 Construction sites 141 Green urban areas http://portal.sdi-edu.zcu.cz 142 23 Sport and leisure facilities 211 Non-irrigated arable land 212 Permanently irrigated land
  • Understanding target data • Plan4all Land Cover data model Simple feature class Geometry Polygon Contains M values No LandCoverStandardisedArea Contains Z values Yes Allow Prec- Field name Data type nulls Default value Domain ision Scale Length Relationship class OBJECTID Object ID StandardisedArea_OriginalArea SHAPE Geometry Yes Type Simple Forward label OriginalArea inspireId String Yes 15 Cardinality One to many Backward label StandardArea source String Yes 50 Notification None classification String Yes CorineLandCoverCode 21 Origin feature class Destination feature classbeginLifespanVersion Date Yes 0 0 8 Name StandardArea NameOriginalArea endLifespanVersion Date Yes 0 0 8 Primary key inspireId SHAPE_Length Double Yes 0 0 Foreign key inspireId SHAPE_Area Double Yes 0 0 No relationship rules defined. Simple feature class Geometry Polygon Contains M values No LandCoverOriginalArea Contains Z values Yes Allow Prec- Field name Data type nulls Default value Domain ision Scale Length OBJECTID Object ID SHAPE Geometry Yes inspireId String Yes 15 source String Yes 50 classification String Yes 21 classificationLink String Yes 50 SHAPE_Length Double Yes 0 0 SHAPE_Area Double Yes 0 0 http://portal.sdi-edu.zcu.cz 24
  • Understanding source data • Zemgale (Latvia) data model Geometry Polygon Contains M values No Coded value domain CorineLandCoverCode Contains Z values Yes Description CorineLandCoverCod Prec- Field type elue Simple feature class Domain ision Scale Length Geometry Polygon Split policy String Relationship class Contains M values No Merge policy Default value plan_zonejums_JelgavaSurroundings StandardisedArea_OriginalArea Contains Z values No Default value Code Description Allow Type Simple Forward label Prec- OriginalArea 1 Artificial surfaces Field name Data type nulls 15 Default valueOne to many Domain label ision Scale Length Cardinality Backward StandardArea 2 Agricultural areas 50 Notification None OBJECTID Object ID 3 Forest and semi natural areas CorineLandCoverCodeGeometry Shape Yes 21 Origin feature class Destination feature class 4 Wetlands gid 0 Double 0 Yes 8 Name StandardArea 0 0 NameOriginalArea 5 Water bodies veids String 0 Yes 8 0 Primary key inspireId 21 11 Urban fabric Foreign key inspireId indekss String 0 Yes 0 254 12 Industrial, commercial and transport units platiba String 0 Yes 0 Atribute FieldNo relationship rules defined. Explanation 21 13 Type Mine, dump and construction sites Artificial, non-agricultural pasv String Yes 254 14 vegetated areas piezimes String Yes 254 21 Arable land map_leaf Geometry Polygon String Yes VEIDS Planed land use type (see possible 254 values down) Text 50 Contains M values No 22 Permanent crops dept Contains String Z values Yes Yes 254 23 Pastures Shape_Length Prec- Double Yes INDEKSS Area with speciffic0restrictions 0 24 Text 10 Heterogeneous agricultural areaslue Domain Shape_Area ision ScaleYes Double Length 0 0 31 Forests PLATIBA Area(m2) 32 Long Integer and/or herbaceous Scrub vegetation associations Open spaces with little or no 33 15 vegetation 41 Inland wetlands 50 TER_VIEN territorial unit Text 50 42 Maritime wetlands 21 51 Inland waters 50 ADM_TER administrative area 52 Text 50 Marine waters 0 0 111 Continuous urban fabric 0 0 LAYER Layer number in CAD systems 112 Text 50 Discontinuous urban fabric 121 Industrial or commercial units Road and rail networks and 122 PIEZIMES notes 123 Text 100 associated land Port areas 124 Airports http://portal.sdi-edu.zcu.cz 131 25 Mineral extraction sites 132 Dump sites
  • Attribute mapping ZEMGALE CLASSIFICATION → CORINE NOMENCLATURE1 DzM Low-rise residential dwellings → 11 Urban fabric2 DzV Multi-residential dwellings → 11 Urban fabric3 P Public Building → 11 Urban fabric4 RR Production facilities and warehouses → 121 Industrial or commercial units5 RD Mining area → 131 Mineral extraction sites6 T Technical Building → 12 Industrial, commercial...7 Ū Waters → 5 Water bodies8 M Forests → 31 Forests9 ZĪ Outstanding foliage sites No corresponding class10 ZC Other groomed greenery space → 141 Green urban areas11 L Rural Land → 2 Agriculture areas12 No data No http://portal.sdi-edu.zcu.cz corresponding class 26
  • Transformation steps• Understanding both source and target data – A necessary condition!1. Transform source data to WGS 84.2. Transform the source data geometry and attributes to match the target scheme.3. Apply domain. http://portal.sdi-edu.zcu.cz 27
  • Transformation of coordinate system1. Transform source data to WGS 84. – Explore source coordinate system, – Run transformation http://portal.sdi-edu.zcu.cz 28
  • Transformation of geometry and attributes2. Transform the source data geometry and attributes to match the target scheme. – Create classes: • LandCoverOriginalArea, • LandCoverStandardisedArea. – Fill them with data. – Create relationship between them. http://portal.sdi-edu.zcu.cz 29
  • Transformation of geometry and attributes http://portal.sdi-edu.zcu.cz 30
  • Applying a domain3. Apply a StandardClassification domain to LandCoverStandardisedArea. http://portal.sdi-edu.zcu.cz 31
  • Resulthttp://portal.sdi-edu.zcu.cz 32
  • References• JEDLICKA, K.: Using ArcGIS Model Builder for transformations between data models - P4A Land Cover example. In: PLAN4ALL workshop on spatial data harmonization. Riga, 2011.• JEZEK, J.: Technological aspect of spatial data harmonization. [ONLINE] http://prezi.com/ro8cfb114n2d/harmonization/• Project HUMBOLDT http://www.esdi-humboldt.eu/home.html• Project PLAN4ALL http://portal.plan4all.eu• Project SDI-EDU http://portal.sdi-edu.zcu.cz http://portal.sdi-edu.zcu.cz 33