04 --spatial-data

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How to build data model acording INSPIRE

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  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • ISOCARP: We are a global association of experienced, professional planners. Founded in 1965 with a vision of bringing together recognised and highly qualified planners in an international network. We have members from over 70 countries. We are a non-governmental organisation, recognised by the United Nations and the Council of Europe and with a consultative status with UNESCO.
  • FMI : Forest Management Institute (FMI) (ÚHUL, Czech Republic)
  • FMI : Forest Management Institute (FMI) (ÚHUL, Czech Republic)
  • FMI : Forest Management Institute (FMI) (ÚHUL, Czech Republic)
  • FMI : Forest Management Institute (FMI) (ÚHUL, Czech Republic)
  • FMI : Forest Management Institute (FMI) (ÚHUL, Czech Republic)
  • FMI : Forest Management Institute (FMI) (ÚHUL, Czech Republic)
  • 04 --spatial-data

    1. 1. Spatial data Karel Janecka, Karel Charvat Department of Mathematics, Faculty of applied Sciences University of West Bohemia Pilsen, Czech Republic kjanecka @ kma.zcu.cz Help Service Remote Sensing charvat @ccss.cz
    2. 2. Agenda <ul><li>Data models for spatial planning </li></ul><ul><li>- Experience from the PLAN4ALL project </li></ul><ul><li>Spatial data harmonization </li></ul><ul><li>Experience from the HUMBOLDT project </li></ul>
    3. 3. PLAN4ALL project <ul><li>PLAN4ALL ( Towards Harmonisation of Spatial Planning Data ) </li></ul><ul><li>Start: May 2009 </li></ul><ul><li>Duration: 30 months </li></ul><ul><li>The harmonisation of spatial planning data according to the INSPIRE Directive based on the existing best practices in EU regions and municipalities and the results of current research projects. </li></ul>e Content plus project (Best Practice Networks)
    4. 4. Experience from the PLAN4ALL project <ul><li>In the scope of PLAN4ALL project will define data models for the following INSPIRE Themes: </li></ul><ul><ul><li>Land Cover </li></ul></ul><ul><ul><li>Land Use </li></ul></ul><ul><ul><li>Utility and Government Services </li></ul></ul><ul><ul><li>Production and Industrial Facilities </li></ul></ul><ul><ul><li>Agricultural and Aquaculture Facilities </li></ul></ul><ul><ul><li>Area Management/Restriction/Regulation Z ones and Reporting Units </li></ul></ul><ul><ul><li>Natural Risk Zones </li></ul></ul>
    5. 5. Experience from the PLAN4ALL project <ul><li>On the basis of experience from single project countries the work will include: </li></ul><ul><ul><li>The analyse of data models for these Themes used in single countries. </li></ul></ul><ul><ul><li>The definition of conceptual data models for selected Themes ( platform neutral !) </li></ul></ul><ul><li>Data specifications including UML data models for Annexes II and III are not defined yet. Plan4all will contribute to define them . </li></ul><ul><li>Contribution will be ensured by providing reference materials, leading a specific data theme, providing experts, testing, providing comments, … </li></ul>
    6. 6. Data models for spatial planning <ul><li>The process of defining conceptual data models for the selected themes will be based on the INSPIRE document “ D2.6 - Methodology for the development of data specifications ” </li></ul>
    7. 7. Data models for spatial planning
    8. 8. Data models for spatial planning <ul><li>STEP: Identification of user requirements and spatial object types </li></ul><ul><li>RESULTS: </li></ul><ul><ul><li>List of spatial object types as proposals for entries in the INSPIRE Feature Concept Dictionary Register </li></ul></ul><ul><ul><li>“ First cut” data specification </li></ul></ul><ul><ul><li>List of requirements </li></ul></ul><ul><li>REFERENCE MATERIALS: </li></ul><ul><ul><li>D2.6 (section 6.4), D2.3, </li></ul></ul><ul><ul><li>Generic Conceptual Model, ISO 19131, </li></ul></ul><ul><ul><li>INSPIRE Feature Concept Dictionary Register, </li></ul></ul><ul><ul><li>INSPIRE data specification template, </li></ul></ul><ul><ul><li>Consolidated INSPIRE UML Model </li></ul></ul>
    9. 9. Data models for spatial planning <ul><li>STEP: Gap analysis </li></ul><ul><li>RESULTS: </li></ul><ul><ul><li>Description of dat a interoperability issues derived from the identified user requirements and taking the as-is analysis into account (in principle, for every source data set) </li></ul></ul><ul><ul><li>Choice of harmonisation approach </li></ul></ul><ul><ul><li>Updated as-is analyses (additional data sources that have been identified) or updated/reduced user requirements to reduce the i dentified gaps </li></ul></ul><ul><li>REFERENCE MATERIALS: </li></ul><ul><ul><li>D2.6 (section 6.6), </li></ul></ul><ul><ul><li>D2.6 Annex A, </li></ul></ul><ul><ul><li>D2.6 Annex F </li></ul></ul>
    10. 10. Data models for spatial planning <ul><li>STEP: Data specification development </li></ul><ul><li>RESULTS: </li></ul><ul><li>- Data specification (per spatial data theme) with clauses specified in </li></ul><ul><li> ISO 19131 (including application schema in UML as well as the </li></ul><ul><li> corresponding feature catalogue and GML application schema) </li></ul><ul><li>- Updated Consolidated INSPIRE UML model </li></ul><ul><li>- Updated INSPIRE Feature Concept Dictionary Register </li></ul><ul><li>- Updated glossary </li></ul><ul><li>REFERENCE MATERIALS: </li></ul><ul><ul><li>D2.6 (section 6.7), D2.6 Annex A, Generic Conceptual Model, </li></ul></ul><ul><ul><li>ISO/TS 19103, ISO 19109, ISO 19110, ISO 19126, ISO 19131, INSPIRE data specification template, Consolidated INSPIRE UML Model, INSPIRE Feature Concept Dictionary Register, INSPIRE Glossary, ISO 19136 </li></ul></ul>
    11. 11. PLAN4ALL – profit for data holders <ul><li>Regions and municipalities will have their data and systems in compliance with INSPIRE after the end of the project </li></ul><ul><li>Regions and municipalities will be able to promote investment possibilities of their region trough European Plan4all portal, which will be managed in close cooperation with ISOCARP </li></ul>
    12. 12. PLAN4ALL – profit for technological partners <ul><li>Solutions of technological partners will become INSPIRE compliant through modification, testing and validating. </li></ul>
    13. 13. PLAN4ALL – European Portal for Spatial Planning data <ul><li>This portal will be European gate for investors, planners, real estate business, … </li></ul><ul><li>It will allow municipalities and regions to publish their i nformation in central place </li></ul>
    14. 14. Spatial data harmonization <ul><li>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. </li></ul><ul><li>This includes agreements about coordinate reference systems, classification systems, application schemes, etc. </li></ul>
    15. 15. Spatial data harmonization
    16. 16. Spatial data harmonization <ul><li>Components of harmonization: </li></ul><ul><li>INSPIRE principles </li></ul><ul><li>Reference model </li></ul><ul><li>Data translation model </li></ul><ul><li>Portrayal model </li></ul><ul><li>Application schemes and feature catalogues </li></ul><ul><li>Dictionaries </li></ul><ul><li>Metadata </li></ul><ul><li>Maintenance </li></ul><ul><li>Quality </li></ul><ul><li>Data transfer </li></ul><ul><li>Derived reporting & multiple representations </li></ul><ul><li>Consistency between data </li></ul><ul><li>Data Capturing </li></ul>
    17. 17. HUMBOLDT project <ul><li>Project HUMBOLDT will contribute to the implementation of an European Spatial Data Infrastructure that integrates all the diversity of spatial data available from the multitude of European organizations . </li></ul><ul><li>I t is the aim of this project to manage and advance the implementation process of this ESDI </li></ul><ul><li>Duration: 2006 - 2010 </li></ul>
    18. 19. Experience from the HUMBOLDT project <ul><li>HUMBOLDT Scenario FOREST </li></ul><ul><ul><li>The scenario is focused mainly on land cover and vegetation integration with data for spatial planning, water resources, risk management and security </li></ul></ul><ul><ul><li>It demonstrates the possibilities of updating international data set Corine Land Cover (CLC) with using Regional Plans of Forest Development (RPFD) data. </li></ul></ul>
    19. 20. Experience from the HUMBOLDT project <ul><li>CLC Use Case – source data </li></ul><ul><ul><li>RPFD contain data summaries on the state of the forest and the service needs of the forest as a public interest. </li></ul></ul><ul><ul><li>Geometry types: Data can contain all types of geometry primitives (point, line, polygon) and some texts, too. </li></ul></ul><ul><ul><li>Storage format(s): Database, shapefiles. </li></ul></ul><ul><ul><li>Coordinate reference system: S-JTSK (Czech national system) </li></ul></ul><ul><ul><li>Scale / resolution: from 1:10 000 to 1:50 000 </li></ul></ul><ul><ul><li>Language: Czech </li></ul></ul><ul><ul><li>Metadata: Defined by FMI </li></ul></ul>
    20. 21. Experience from the HUMBOLDT project <ul><li>CLC Use Case – target data </li></ul><ul><ul><li>Geometry types: Data contain polygons. </li></ul></ul><ul><ul><li>Storage format(s): Shapefiles. </li></ul></ul><ul><ul><li>Conceptual model: The CLC data are composed of features with three parameters: </li></ul></ul><ul><ul><ul><li>GEOMETRY: Geometry </li></ul></ul></ul><ul><ul><ul><li>CODE_00: String </li></ul></ul></ul><ul><ul><ul><li>AREA: Double </li></ul></ul></ul><ul><ul><li>Coordinate reference system: ETRS 1989 </li></ul></ul><ul><ul><li>Scale / resolution: from 1:100 000 to 1:250 000 </li></ul></ul><ul><ul><li>Language: English </li></ul></ul>
    21. 22. Experience from the HUMBOLDT project <ul><li>CLC Use Case – harmonization issues </li></ul><ul><ul><li>Data formats conversion (to GML) </li></ul></ul><ul><ul><li>Classification schemes and systems, codelists, terminology and vocabulary (selection of corresponding items) </li></ul></ul><ul><ul><li>Types of geometric primitives (to polygons) </li></ul></ul><ul><ul><li>Metadata profile </li></ul></ul><ul><ul><li>Coordinate system </li></ul></ul><ul><ul><li>Geometry improvement </li></ul></ul><ul><ul><li>Generalisation, multi-linguality… </li></ul></ul>
    22. 23. Experience from the HUMBOLDT project <ul><li>CLC Use Case – main steps of data harmonization </li></ul><ul><ul><li>Harmonisation of classifications schemes and systems, codelists, terminology and vocabulary (selection of corresponding items) must be created before the building of harmonisation tools, because there is necessary to define the rules for mapping language. </li></ul></ul><ul><ul><li>Type of geometric primitives (all types to polygons – this harmonisation step is necessary, but the majority of the selected source data (maybe all data) will be in the form of polygons). </li></ul></ul><ul><ul><li>Harmonisation of metadata profile is necessary in the term of INSPIRE directive. </li></ul></ul>
    23. 24. Experience from the HUMBOLDT project <ul><li>CLC Use Case – main steps of data harmonization </li></ul><ul><ul><li>Data must be converted from Czech national system S-JTSK (RPFD) to system ETRS 1989 (CLC). </li></ul></ul><ul><ul><li>Because the geometry of source and target data is not the same, there will be necessary the transformation and/or improvement of geometry (e.g. elimination of differences between data providers and adaptation to reference data, edge-matching). It relates with next item – generalisation. </li></ul></ul><ul><ul><li>Because the harmonised data layers are in different level of detail and target data sets have mostly the smaller scale than source data, the generalisation methods could be used. </li></ul></ul><ul><ul><li>Source and target data are coded in the same language. But because the CLC data do not contain any description except codes and these codes are translated into many languages including Czech, the multi-linguality is supported. </li></ul></ul>
    24. 25. Experience from the HUMBOLDT project <ul><li>The benefits of proposed solution: </li></ul><ul><li>Conformity with standards and major European initiatives </li></ul><ul><li>Reduction of cost and effort of INSPIRE implementation </li></ul><ul><li>Integration of services and data to facilitate decision-making </li></ul><ul><li>Information accessibility and distribution </li></ul><ul><li>Core technology will be available as Open Source </li></ul><ul><li>Information management technology related user-driven operational services </li></ul>
    25. 26. Experience from the HUMBOLDT project <ul><li>Harmonization – conclusion </li></ul><ul><ul><li>Harmonization in forestry makes possible better: </li></ul></ul><ul><ul><ul><li>Classification schemes and systems, codelists, terminology and vocabulary (selection of corresponding items) </li></ul></ul></ul><ul><ul><ul><li>Combination of internal and external data sets with different parameters </li></ul></ul></ul><ul><ul><ul><li>Using of different IT systems </li></ul></ul></ul><ul><ul><ul><li>Cross-border cooperation </li></ul></ul></ul>
    26. 27. Thank you for your attention! Karel Janecka , Karel Charvat Department of Mathematics, Faculty of applied Sciences University of West Bohemia Pilsen, Czech Republic kjanecka @ kma.zcu.cz Help Service Remote Sensing charvat @ccss.cz

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