Potential and Accuracy of Digital Landscape Analysis based on high resolution remote sensing data

Transcription

1 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Potential and Accuracy of Digital Landscape Analysis based on high resolution remote sensing data Dr. Matthias Trapp, Gregor Tintrup genannt Suntrup, Kai Thomas, Tanja Jalke, Djamal Guerniche, RLP AgroScience, Germany, Section Environmental Information Systems Henning Schrader, Infoterra, Germany

2 Rhineland-Palatinate AgroScience GmbH non profit research institute 100 % daughter of Ministry IfA Section Environmental Information Systems Section Angewandte Standortökologie Section Stoffstrommanagement Section Ecochemistry

3 Our main objectives Working with stupid pictures, and converting them to intelligent geodata

4 Our main objectives from raw data to products

5 Contents Remote sensing data with different spatial and temporal resolution are today available (nearly) for the whole world. In Past: Coarse resolution (Land-SAT...) Today: new generation of high resolution remote sensing data useful for realistic landscape classification (arable land or vegetation, structures and forests) Presented today: Optical and multispectral sensors (orthoimages, (IKONOS-2) and Quickbird): land cover classification High resolution radar satellite TerraSAR-X (Infoterra GmbH, Germany): topographical mapping roads, railways, settlements, industrial buildings, etc... First analysis of the TerraSAR-X will be shown as Case studys (Germany and Tunesia)

6 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Case Study (Germany): hr multispectral images and geodata Classification and mapping of arable land and vegetation as basis for the calculation of biogas and biomass potential for an up-to-date biotope cadastre

7 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Source: raw data high resolution aerial photos high resolution satellite images false color presentation: near infrared, blue, green

8 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany knowledge-based semi-automated classification process (with Definiens) Level 2 Level 1 Bild

9 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany knowledge-based semi-automated classification process (with Definiens) photo documentation aerial image classification orchard single tree orchard espalier

10 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Result: landscape classification

11 Digital Terrain Model overlapped with classification results Result: landscape classification... flood areas from DTM

12 Accuracy: hr-classification and cadastrial information (ALK)

13 Accuracy: hr-classification and cadastrial information (ALK)

14 Accuracy: hr-classification and cadastrial information (ALK)

15 Accuracy: hr-classification and cadastrial information (ALK)

16 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Result: landscape classification and analysis: mapping, statistics, analysis 30% 33% forest grassland, meadows arable land afforestation 3% 1% 32% 1% wetlands others Ground truthing showed an accuracy of 95 % - 98 %

17 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Applications: GIS-based Feasibility Study for Biogas Plants 49 30'0"N 8 0'0"E 8 10'0"E 8 20'0"E Contractor A!H Contractor B!H Potential plant location Contractor C!H Legend Logistics!H!H!H!H Radius 20km Administrative District Highway Major Road Contractor A (22,1 km) Contractor B (19,9 km) Contractor C (25,0 km) Plant location Biogas Quantities Forest + Grassland Pomace Crops + Fruitrests Dung ± 49 20'0"N 49 10'0"N Location in Germany Legend Radius 20km Landuse ± Urban area (14557 ha) Forest (57193 ha) Arable land (24721 ha) Grassland (9575 ha) Wine (16673 ha) Orchard (1051 ha) km Summary Visualisation and identification of substrate- and biogaspotentials Location Evaluations to maintain Cost-Effectiveness (e.g. shortest paths)

18 Perspectives: Applications based on LIDAR DTM and DSM LIDAR: Light Detection And Ranging DTM: Digital Terain Model DSM: Digital Surface Model

19 Perspectives: Applications based on LIDAR DTM (3 Points per sqm)

20 Perspectives: Applications based on LIDAR DSM DSM Heigth above surface [m]

21 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Meaningful applications: Mapping of buildings, roads... Calculation of terrain models: slope aspect potential solar radiation... but, available only for small areas expensive...

22 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Especially for countries with a lack of small scaled geodata (this means high resolution) the generating of basic geodata like topographical maps combined with the classification of land cover delivers important georeferenced information for organising, planning and managing ecological and even economical issues

23 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Case Study: TerraSAR-X 1 Combination of multispectral sensor data and Terra-SAR-X data Terra-SAR-X: Advantages weather (clouds...) and daylight independent reflexion of sealing areas like streets, building, surface waters semi-automated mapping and analysing of anthropogenic land cover topographical information settlements, buildings streets... SpotLight: StripMap: ScanSAR: up to 1 m resolution, scene size 10 km (width) x 5 km (length) up to 3 m resolution, scene size 30 km (width) x 50 km (length) up to 18 m resolution, scene size 100 km (width) x 150 km (length) 1 : TerraSAR-X: Infoterra GmbH, Germany

24 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Germany, region Kaiserslautern TerraSAR-X, SpotLight Data Anthropogenic features derived from German ATKIS (vector-based, medium scaled)

25 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany First evaluations of this new sensor showed a high potential especially in combination with multispectral images for a semi-automated classification of land cover and anthropogenic land use. The extraction of sealed objects from Terra-SAR-X was compared with anthropogenic features from the German ATKIS data and we found in a first study a high accuracy in a medium scaled resolution (1: :25.000)... had to be continued... Now first results from InfoTerra GmbH, Germany, Case Study Tunesia: Topographical Mapping

26 Topomap based on StripMap data

27 Topomap based on StripMap data

28 'Spatial Information for Sustainable Management of Urban Areas' Mainz, 2-4 February 2009, Germany Conclusions and Take Home Messages Optical and mulitspectral images in high resolution are available world-wide and can be classified by using object oriented image classifcation software semi-automated Applications: land cover, topographical mapping, assessment of biomass/biogas potential New radar images like TerraSAR-X (and Terra-SAR-X Tandem) are available world-wide in different scale levels: from high to medium resolution: overview mapping to detailed infrustructure analysis Applications: topographical mapping, infrastructure and anthropogenic features (sealed surfaces!) generating DTM (10m resolution) Very high resolution DTM and DSM data can be used for better planning and visualising in small scaled regions

29 Thank you for your kind attention!