What to do with the existing spatial data in planning to be

INSPIRE compliant? Petr Horak, Martin Vlk, Sarka Horakova

Lea Manakova, Miloslav DvorakTomas Mildorf, Ota Cerba, Karel

Charvat

Role of Spatial Planning

Spatial planning acts between all levels of government so planners face important challenges in the development of territorial frameworks and concepts every day. Spatial planning systems, the legal situation and spatial planning data management are completely different and fragmented throughout Europe.Nevertheless, planning is a holistic activity. All tasks and processes must be solved comprehensively withinput from various sources. It is necessary to make inputs interoperable because it allows the user to search data from different sources, view them, download them and use them with help of geoinformation technologies (GIT).

Plan4all Data Model

Plan4all develops conceptual data models for seven selected themes from Annexe II and III of the INSPIRE Directive. The themes are land cover, land use, utility and government services, production and industrial facilities, agriculture and aquaculture facilities, area management/restriction/regulation zones and reporting units, and natural risk zones. The data models refer to the INSPIRE documents „Generic Conceptual Model (GCM)“ and „Methodology for the development of data specifications“ which set basic rules for the development of data models.

Plan4all Data Model

The object-oriented Plan4all data models are flexible enough to be extended easily with further objects. Each object has a unique identity which is immutable and used only once, even if an object is removed its identity is not assigned to other objects. Also code lists and nomenclatures are extendable. To specify the models in diagrams UML is used. The data models are published on the Plan4all website and are open for validation by affiliated partners. Further, the Plan4all data models was an input for the development of the INSPIRE data models by the INSPIRE thematic working groups. Especially, there is strong cooperation concerning the land use theme.

Annex III•Statistical units•Buildings•Soil•Land use•Human health and safety•Utility and Government services•Environmental monitoring facilities•Production and industrial facilities•Agricultural and aquaculture facilities•Population distribution – demography•Area management/restriction/regulation zones and reporting units•Natural risk zones•Atmospheric conditions•Meteorological geographical features•Oceanographic geographical features•Sea regions•Bio-geographical regions•Habitats and biotopes•Species distribution •Energy resources•Mineral resources

Annex I•Coordinate reference system•Geographical grid systems•Geographical names•Administrative units•Addresses•Cadastral parcels •Transport networks •Hydrography•Protected sites

•Annex II•Elevation•Land cover•Orthoimagery•Geology

INSPIRE Spatial Data Themes

Plan4all

Plan4all Outputs

1. Promotion

2. Metadata profiles

3. Data models

4. Networking architecture

5. Validation

6. Geoportal

7. Data and metadata deployment

• Land cover• Land use• Utility and Government services• Production and industrial facilities• Agricultural and aquaculture facilities• Area management/restriction/regulation zones and reporting units• Natural risk zones

• Land cover• Land use• Utility and Government services• Production and industrial facilities• Agricultural and aquaculture facilities• Area management/restriction/regulation zones and reporting units• Natural risk zones

Plan4all Harmonisation Idea

Source Data HF

Source Data MEDDTL

Source Data LAZIO

Source Data ADR

Source Data EPF

Source Data DIPSU

Source Data AVINET

Source Data MAC

Source Data GIJONSource Data

NASURSA

Source Data GEORAMA

Source Data FTZ

Source Data PROVROMA

Source Data ZPR

Source Data LGV

Source Data TDF

Source Data OLOMOUC

Conceptual model

Target Data Structure

Plan4all Harmonisation Idea

Source Data Transformation Harmonised data

Source Data HFNumber

Name_areaNumber_areaLandUse_codeLandUse_descr

……

Source Data Olomouc

LevelLayer

PLFESTGLUF

MACRO……

Plan4all Land Use

model

Target Data StructureInspireID

StatusRegulationNature

IsOverlayAreaGeometryProperty

LUCAs_CodeMacroClassificationOfL

andGeneralLandUseTypeSpecificLandUseType

……

Harmonization steps

1. Description of the source data structure – the exact description of the source data enables better understanding of data and definition of the transformation table. The description includes a scheme of data structure, description of data formats, object types and Code lists or enumerations.

2. Data transformation – it is a main harmonisation process where data from the original source structure is transformed into the target structure. The target data structure is created on the basis of conceptual models. The transformation has two levels – at first, the transformation of features has to be specified and then also transformation of code lists or enumerations must be defined for each transformed attribute. The transformation can be done through transformation tools or directly through SQL query.

3. Publication – there are several ways how to publish the harmonised data stored in the target structure. The Plan4all regions test the publication of the harmonised spatial planning data in their own web map applications and also provided the data through OGC web services WMS and WFS.

Source Data Description

Description of the source data- General principle of the data management in regions- Description of structures of the source data (relations,

objects, features, code lists)- Translation of national terms

Data Transformation

Transformation methodes1. Transformation tools2. Direct editing of database - SQL queries (used in Sumperk and Olomouc)

Data transformation process (HF example)• The target structure has been established on the basis of LandUse

conceptual data model defined in WP4. Because this conceptual data model is not fully corresponding to the source data structure, some modifications have been proposed and only some of the fields have been used. The target database is PostGIS.

• The transformation (harmonisation) scheme have been defined in two steps • The scheme for attributes transformation • The scheme for values transformation – comparison of enumerations of

the source and target data • The target PostGIS tables have been filled on the basis of transformation

(harmonisation) schemes

Data Transformation

Transformation schemes1. Features transformation2. Attributes transformation

Data Transformation

An example of the multi-level transformation of attributes

Target Sources

Publication

Publication of Harmonised Data via Geohosting tool

• Web Map Client• OGC Web Services (WMS, WFS)

Agreement on:

• Coordination system and projection: ETSR (EPSG 3035)• Legends for Land Use data presentation

Publication

Map Compositions via Geohosting tool

Publication in Web Map Client

Original data Harmonised General Land Use Harmonised Status of Area

WMS Compositions

Examples of Harmonised Data

Building Percentage in developing areas Height indication

Examples of Harmonised Data

Specific LandUse Type Indirect Executions

Connection to INSPIRE

The Plan4all project has been invited to participate in the testing of the INSPIRE Annex II and III data specifications.

Plan4all joined to the INSPIRE testing team. Within the Plan4all wil be tested the INSPIRE themes:-Land Cover-Land Use-Natural Risk Zones

Plan4all conceptual data models will be replaced by INSPIRE data specifications => the present experience with tests on conceptual models will be re-used in following INSPIRE tests

Message to LandUse Testers

• To better understand source-target relations a precise definition of the source data should be created and described. There does not exist any fixed standard for planning data in many countries and the definition should help to harmonise the different data in the same way.

• Define precise specific code lists and enumerations with explanation of terms. The same values may imply different meaning to people from different countries and consequently harmonised datasets may be technically correct, but are not in reality. This is not problem of the data model, but a consequence of differences in spatial planning in European countries.

• Be aware of the potential multiplicity of Harmonised attributes• Define names of the source and target elements of the association

connectors. Otherwise it is very difficult to identity these associations in schema mapping tools.

Message to LandUse Testers

• If you propose changes of the models try to get the model as simple as possible.

• Specify precise metadata fields and leave them out of the data as much as possible – of course, where it is useful !

• Define symbols and colour presentation for harmonised data.• Include an information sheet explaining the difficulties

experienced in aligning and aggregating the data across the local and regional areas and then up to the national and super-national levels. The different professions, software and methodologies used in the countries are too great to compile into one document, however drafting such a sheet allows policy and decision makers to understand the hurdles yet facing spatial information.

• Be aware of problems with overlaying features.

Integration of data

• Transformed data could be integrate with global Land use models like:

• CLC• Urban Atlas

CLC 2006 of Czech Republic

CLC 2006 of Czech Republic

Overlapping with Urban Atlas

Overlapping with Urban Atlas

General LanUse

Metadata Import

Metadata Import

Discovery

Metadata Import

Visualization

Visualization