Object based modelling of habitats with EO data: Semantic and technical challenges to achieve interoperability

Transcription

1 Object based modelling of habitats with EO data: Semantic and technical challenges to achieve interoperability Michael Bock, DLR Space Agency Folie 1 Vortrag > Autor > Dokumentname >

2 Outline : How do we interpret the real world based description of habitats to achieve comparability Geometric interoperability of datasets Folie 2

3 How do we interpret the real world? Folie 3

4 Basic elements of a semantic description Classification -> Assignment of a class Characterisation -> Description by features Integration & interoperability: Thematic integration in a semantic data model Geometric integration in a spatial data model Scale: -> Minimum mapping unit & width Folie 4

5 Basic elements of habitat typologies Land Cover Land Use Function Floristic Physiognomy Ecology Evolution, Topography Biogeography Grassland / herbaceous vegegtation Grassland, extensiv, mowed, one cut Flood protection area, bird protection Sociological plant communitiy Life form, e.g. Helophytes nutrient content (e.g. eutrophic) water content & water regime Hangmoor ( slope bog ) Schluchtwald ( forest ) Fen (England) Zwischenmoor (Germany) Folie 5

6 Through which glasses we are looking? Sensor- und object features Folie 6

7 Seasonal variation Wet herb/grass fields and Purple moorgrass degeneration Outline Folie 7

8 NDVI Time series Spot 5 Feb. April June - August Tag im Jahr GFY Day in the year Purple moorgrass Day in the year Wet grasslands Tag im Jahr NSb NSa Tag im Jahr Folie 8

9 Spatial variation Various representations of sedge reeds Outline Folie 9

10 Mapping scales Outline Forest map in different scales and change? IKONOS State Biotopmap Forest Map Spot based Forest Map Ikonos based Both EO based maps Accuracy > 85 % Bock et al 2008: Exemplary Results form the ESA funded GSE Forest Monitoring Folie 10

11 Geobia From image objects to target objects. BOCK M & LESSING R (2000): Remote Sensing, Building of objects and Determination of quality. In: Cremers & Greve (Eds): Umweltinformatik 2000, , Meropolis. Marburg. Folie 11

12 From image obects to.. Folie 12

13 to a semantic habitat data model Folie 13

14 Every object is described by an ontology Folie 14

15 Extraction of habitat characteristics UK Broad Habitats Fen, marsh and swamp This broad habitat type is characterised by a variety of vegetation types that are found on minerotrophic (groundwater-fed), permanently, seasonally or periodically waterlogged peat, peaty soils, or mineral soils. Fens are peatlands which receive water and nutrients from groundwater and surface run-off, as well as from rainfall. Flushes are associated with lateral water movement, and springs with localised upwelling of water. Marsh is a general term usually used to imply waterlogged soil; it is used more specifically here to refer to fen meadows and rush-pasture communities on mineral soils and shallow peats. Swamps are characterised by tall emergent vegetation. Reedbeds (i.e. swamps dominated by stands of common reed Phragmites australis) are also included in this type. Folie 15

16 The UK Broad habitat Fen, marsh and swamp is described very broad. Folie 16

17 Object model of Deciduous forest as defined by the BNTK &implemented in DeCover ontology DELPHI IMM GmbH Folie 17

18 The approach of semantic interoperability every dataset has a definition of every object (catalog of objects) between the definitions of the objects it is possible to find comparable features, e.g. minimum mapping unit or the character of the highest percentage of landcover (e.g. vegetation) the interoperability approach describes every object with a set of basic features and establishes herewith a comparabilty Simple cross-links between nomenclatures can be extented by using the similarity of the attributes DELPHI IMM GmbH From Presentation: Interoperability between different datasets, Rolf Lessing, Delphi-IMM 2010 Folie 18 18

19 Options of geometric and thematic Integration of GSE- Forest Data to update the Federal DLM-DE Forest Layer 1. Pure thematic integration: Keep the borders of the DLM-DE Forest objects and assign the GSE Forest class if the similarty is high 2. Complete geometric integration: of the GSE Forest Data by keeping the existing forest border lines 3. Combined approach: Thematic integration if the percentual share of a forest type is high Geometric Integration in the remaining areas Bock et al 2008: FP7 B4G funded research -> Feasibility study DLM-DE Update Folie 19

20 Flowchart of methodology Area depend threshold Bock et al 2008: FP7 B4G funded research -> Feasibility study DLM-DE Update Folie 20

21 Mostly thematic integration for the BKG Bock et al 2008: Example of Feasibility study DLM-DE Update for the BKG Folie 21

22 Geometric Integration and zonal class assignment Bock et al 2008: Example of Feasibility study DLM-DE Update Folie 22

23 Bock et al 2008: Example of Feasibility study DLM-DE Update for the BKG Folie 23

24 Grassland Monitoring Integration in the BNTK 1:10000 Biotope and land use map 10m object based classification Bock 2007: Contract work at DFD for the LANU- Schleswig- Holstein Folie 24

25 Bock et al : Funded by FP5 project SPIN, FP6 Geoland and LANU-SH Folie 25

26 s I Common LULC and Habitat nomenclatures are likely defined by a large mixture of descriptors (floristic, ecology, physiognomy, evolution, biogeography, topography) but often not suited to be mapped by remote sensing directly. Systematic semantic Modelling of real world objects and use of ontology's for habitat description is essential: to assure that we know what elements reference data and target class are composed of to achieve interoperability to other comparative data sets in space and time to build up transferable rule sets with Geobia Folie 26

27 s II Geometric integration of EO derived data with existing datasets that are already in operational use is essential Monitoring and update of existing LULC and habitat maps requires to keep the existing outlines as far as possible. A combination of zonal attributes and geometric integration is suitable for most Land use and Land Cover type Semantic and geometric interoperability is an important issue if spatial datasets are combined or updated Folie 27

28 Related Actions The EIONET EAGL Group work on a improvement of current LULC Data models for monitoring in Europe A list of pure LC classes was defined at last meeting Dez Current task of EAGL is to develop a whole list of attributes that will define each of the pure land cover classes Minutes of meetings and further information are available at: Folie 28

29 Related Actions a LCCS plugin for ecognition is planned! Folie 29

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