The SDI-EDU project: Towards INSPIRE Awareness Raising on Example of Spatial Data Harmonization

Transcription

1 The SDI-EDU project: Towards INSPIRE Awareness Raising on Example of Spatial Data Harmonization Karel Janecka Otakar Cerba, Karel Jedlicka, Jan Jezek Faculty of Applied Sciences, University of West Bohemia Pilsen, Czech Republic

2 The SDI-EDU project The SDI-EDU project aims: to transfer experience from EU research projects dealing with Spatial Data Infrastructure (SDI) and spatial planning like PLAN4ALL, HUMBOLDT or NATURNET REDIME towards spatial planners in European Regions and municipalities the SDI-EDU educational curriculum is based upon this experience and user requirements to build European educational geoportal for spatial planning the content material will be accessible on this geoportal

3 Target groups The targeted end users specialized, but ordinary public active in planning processes have to fully understand the meaning and consequences of INSPIRE. In our focus are both: the national level stakeholders (ministries, planning institutes, leading planning ateliers), and the regional administrations and urban planners.

4 Educational curriculum user requirements

5 Educational curriculum Political consequences of INSPIRE on local and regional level (in relation to spatial planning) INSPIRE requirements from the technological point of view The examples of solutions for SDI building (commercial x open source) INSPIRE, Metadata & spatial planning INSPIRE, Spatial data & spatial planning INSPIRE Networking architecture Intellectual property rights & Spatial data infrastructures Monitoring obligation + Practical examples (how to)

6 State of the art Overall we have 17 lessons English content is almost ready In nowadays the translation is running Content reviewer: Institute for Spatial Development under the Czech Ministry of Regional Development GET INVOLVED write to:

7 SDI-EDU Educational geoportal

8 Example of the lesson about spatial data harmonization

9 Harmonization and its role in spatial planning

10 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. 10

11 Spatial data harmonization 11

12 Spatial data harmonization Components of harmonization: INSPIRE principles Reference model Data translation model Portrayal model Application schemes and feature catalogues Dictionaries Metadata Maintenance Quality Data transfer Derived reporting & multiple representations Consistency between data Data Capturing 12

13 An example of Spatial Data Harmonization using PostgreSQL + PostGIS 13

14 HARMONIZATION Source data model Target data model Zemgale urban planing (specific data model) CORINE land cover Geometry Reclassification HARMONIZATION 14

15 HARMONIZATION STEPS Definition of reclassification rules Data reclassification Union of touching geometries in same class Transformation from multipolygon to polygons 15

16 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 16

17 ZEMGALE DATA MODEL Atribute Field Explanation Type VEIDS Planed land use type (see possible values down) Text 50 INDEKSS Area with speciffic restrictions Text 10 PLATIBA Area(m2) Long Integer TER_VIEN territorial unit Text 50 ADM_TER administrative area Text 50 LAYER Layer number in CAD systems Text 50 PIEZIMES notes Text

18 LAND COVER DATA MODEL CORINE land cover 18

19 RECLASSIFICATION RULES ZEMGALE CLASSIFICATION CORINE NOMENCLATURE 1 DzM Low-rise residential dwellings 11 Urban fabric 2 DzV Multi-residential dwellings 11 Urban fabric 3 P Public Building 11 Urban fabric 4 RR Production facilities and warehouses 121 Industrial or commercial units 5 RD Mining area 131 Mineral extraction sites 6 T Technical Building 12 Industrial, commercial... 7 Ū Waters 5 Water bodies 8 M Forests 31 Forests 9 ZĪ Outstanding foliage sites No corresponding class 10 ZC Other groomed greenery space 141 Green urban areas 11 L Rural Land 2 Agriculture areas 12 No data No corresponding class 19

20 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 20

21 Database schema 21

22 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; 22

23 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 23

24 RECLASSIFIED DATA SET 24

25 Next step union of adjacent features with same class SELECT NEXTVAL('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 foo WHERE foo.the_geom IS NOT NULL; 25

26 Final dataset 26

27 An example of Spatial Data Harmonization using commercial GIS software - ArcGIS 27

28 Using ArcGIS Model Builder for transformations between data models - PLAN4ALL Land Cover example 28

29 Understanding target data Plan4all Land Cover data model 29

30 Understanding target data Plan4all Land Cover data model ERA diagram of database schema in ESRI Geodatabase. 30

31 Understanding target data Plan4all Land Cover data model 31

32 Understanding source data Zemgale (Latvia) data model Atribute Field Explanation Type VEIDS Planed land use type (see possible values down) Text 50 INDEKSS Area with speciffic restrictions Text 10 PLATIBA Area(m2) Long Integer TER_VIEN territorial unit Text 50 ADM_TER administrative area Text 50 LAYER Layer number in CAD systems Text 50 PIEZIMES notes Text

33 Attribute mapping ZEMGALE CLASSIFICATION CORINE NOMENCLATURE 1 DzM Low-rise residential dwellings 11 Urban fabric 2 DzV Multi-residential dwellings 11 Urban fabric 3 P Public Building 11 Urban fabric 4 RR Production facilities and warehouses 121 Industrial or commercial units 5 RD Mining area 131 Mineral extraction sites 6 T Technical Building 12 Industrial, commercial... 7 Ū Waters 5 Water bodies 8 M Forests 31 Forests 9 ZĪ Outstanding foliage sites No corresponding class 10 ZC Other groomed greenery space 141 Green urban areas 11 L Rural Land 2 Agriculture areas 12 No data No corresponding class 33

34 Transformation steps Understanding both source and target data A necessary condition! 1. Transform source data to WGS Transform the source data geometry and attributes to match the target scheme. 3. Apply domain. 34

35 Transformation of coordinate system 1. Transform source data to WGS 84. Explore source coordinate system, Run transformation 35

36 Transformation of geometry and attributes 2. Transform the source data geometry and attributes to match the target scheme. Create classes: LandCoverOriginalArea, LandCoverStandardisedArea. Fill them with data. Create relationship between them. 36

37 Transformation of geometry and attributes 37

38 Applying a domain 3. Apply a StandardClassification domain to LandCoverStandardisedArea. 38

39 Result 39

40 Thank you for your attention! Karel Janecka Faculty of Applied Sciences, University of West Bohemia Pilsen, Czech Republic