The challenge of linking or integrating data on Buildings

Transcription

1 The challenge of linking or integrating data on Buildings

2 Expected benefits: user requirements

3 Wide use of data on Buildings Buildings are places where people live, work, spend more of their time => Data of interest for many topics Protection from pollution or risk Quality of habitat, sustainable habitat (energy, ) New public infrastructure Land taxes (valuation) Census.

4 Wide use of data on Buildings The use cases identified by INSPIRE

5 Need for lots of data Many very useful attributes Topographic description: height - number of floors roof type - material (roof, structure,..) Cadastral information official area - official value address Temporal aspects (year of construction) Link to various documents Photos, images Building permits Emergency evacuation plans

6 Need for lots of data The INSPIRE selection

7 The INSPIRE approach

8 Interoperability objective Data producers of Member States have to make their data available according to the common INSPIRE rules Common data model Common Coordinate Reference System. INSPIRE applies only to existing data => no obligation of new production

9 Data model: flexible approach Several application schemas in INSPIRE Basic semantic Rich semantic 2D data 2D Buildings Extended2D Buildings 3D data 3D Buildings Extended3D Buildings Only basic data models are in the Implementing Rules Extended models are optional => step-wise approach with legal obligation only on data considered as most useful and most available

10 Data model: flexible approach Basic semantic (core data models) Lots of voidable attributes Voidable = conditional To be provided if available Different geometric representations allowed Use of Building and BuildingPart concepts (CityGML)

11 Data delivery As-is analysis => several data producers Topographic view (mapping agencies, ) Cadastral view Statistical view Local authorities Ministry of Housing. If no national coordination, each of them has to make its data compliant with INSPIRE

12 The core data approach

13 The UN-GGIM: Europe Core data UN-GGIM: United Nations initiative on Global Geographic Information Management Since 2011 Activities at global and regional levels With UN-GGIM: Europe, a WG on core data Objectives: recommendations of content for production or enhancement of core data

14 Geometric representation Priority 1 : 2D data Priority 2: 3D data Data model Define priorities Semantic content Priority 1: selection from INSPIRE basic semantic Priority 3: selection from INSPIRE basic and extended semantic

15 Data delivery Data may be scattered between various data providers Depends on countries Not user-friendly as gathering all useful information is difficult and time-consuming Recommendation: Data providers of core theme Buildings should coordinate their efforts and offer easy access to core data, e.g. through a unique access point or by national reference data set(s).

16 Why is it a challenge?

17 Challenge presentation Attributes may be scattered between various data producers There may be various geometric representations of buildings 2D/3D/ no geometry Roof edge / footprint/ Various segmentations of buildings

18 Various segmentation of buidings There is no common agreement about what is a building CityGML does not provide guidelines about use of Building and BuildingPart 1 generalized building 2 detailed buildings 2 BuildingPart 1 Building

19 Challenge presentation Data producer X? Data producer Y Geometry A Identifier a Attributes 1, 2, 5, 6 Data producer Z Geometry B Identifier b Attributes 2, 3, 7 User requirement: get all attributes (1, 2, 3, 4, 5, 6, 7) on a common geometric representation Geometry C Identifier c Attributes 1, 3, 4, 6

20 Challenge presentation Data producer X Geometry A Identifier a Attributes 1, 2, 5, 6 Data producer Y Geometry B Identifier b Attributes 2, 3, 7 No common segmentation => no common identifiers => no semantic jointure Data producer Z Geometry C Identifier c Attributes 1, 3, 4, 6 No common geometric segmentation and representation => no reliable spatial jointure

21 Challenge examples (1) Example 1: unification of topographic data with cadastral plan Source data Topographic data (BD TOPO) Captured as 2,5 D data Few semantic attributes But generalised representation Cadastral map Captured as 2D data (almost) no semantic attribute Detailed representation Objective: get detailed geometry (cadastre) and Z value (IGN)

22 Challenge examples (1) The generalised representation of building as 2,5D data (IGN) The detailed representation of building as 2D data (cadastre) The detailed representation of building as 2,5D data (BD UNI)

23 Challenge examples (1) Method Data matching Automatic Interactive Post-processing Providing Z value Migrating semantic attributes Checking consistency with other layers Huge work Development : 2-3 years Production : 4-5 years Many difficulties (data not available every where, different reference dates, inconsistencies, ) Most done around 2010 Still on-going

24 Challenge examples (2) Example 2: integration of cadastral information within topographic data base Source data Topographic data (BD TOPO) Unified geometric representation with cadastral map Cadastral registry Contains very interesting semantic» Use» Year of construction» Number of floors» Material». No geometric representation No link with building in the cadastral map Only reference to the cadastral parcel

25 Challenge examples (2) State-of-play Some testing has been done => solve (some) technical issues Agreement with relevant stakeholders Cadastre CNIL (privacy issues) Core Cadastral attributes integrated in new topographic data model

26 Challenge examples (2) Testing results Favourable cases industrial industrial industrial Only 1 building in the cadastral parcel => All attributes may be migrated Several buildings in the cadastral parcel but all having same attribute value

27 Challenge examples (2) Testing results Lots of remaining issues: all other cases What to do? Keep attributes empty Try to make reasonable guess e.g. according size or aspect of building e.g. using Address information

28 Challenge examples (3) Example 3: common identification of buildings WG launched in France By Ministry of Sustainable Development (Housing) Several meetings in 2018 There are user requirements Common identification system Life-cycle rules Various practices from various data producers Some initial proposals Nice in theory» Definition of building from building permit point of view» Rules for life-cycle of identifiers Look difficult to apply them in practice (IGN)

29 Potential solution: topics for innovation or research

30 Topics for research Investigation of segmentation practices What is considered as a building? Modelling practices (e.g. use of BuildingPart?) Representation practices State-of-play, assessment of current linkage mechanisms Address/ identifier(s) /

31 Topics for research Proposals for improvements Guidelines for segmentation /identification E.g. Where to put common identifier? Maximum segmentation: Building Part Meaningful segmentation: Building Tools, methodologies Data matching Data integration Data linking Building cut by (old) cadastral limits => Meaningless segmentation [France] Better data => new applications

32 Topics for research Solutions have to be found mainly at national level Different contexts But sharing knowledge and experiences may help