1. IGARSS’11, Vancouver Water Body Detection from TanDEM-X Data: concept & first evaluation of an accurate water indication mask A. Wendleder 1), M. Breunig 1), K. Martin 2), B. Wessel 1), A. Roth 1) 1) German Aerospace Center DLR | 2) Company for Remote Sensing and Environmental Research SLU IGARSS 2011 / Vancouver / 2011-07-28

2. Slide 2 Outline Introduction Definition of the TanDEM-X water indication mask Challenges for TanDEM-X water body detection Concept & methodology of water body detection Test site demonstration Evaluation of classification results Outlook

3. Slide 3 Definition of the TanDEM-X water indication mask Global mission – global DEM – global water body mask Water body mask primarily extracted for post-processing DEM editing ongoing work in flattening of outpoking water bodies correct orthorectification of remote sensing data No production of a complete global water body inventory Kurnool Kadapa Channel / India frozen Lake Taimyr / Russia

4. Slide 4 Challenges for TanDEM-X water body detection TanDEM-X mission with 2 global acquisition data sets in 2011 & 2012 The water body detection runs completely data-driven Processing at Raw DEM level (30*50 km ≈ 8.000*10.000 pixels) 400 up to 800 Raw DEM per day to be processed Therefore maximum computing time of 3 minutes per product Applicable for different appearances of water bodies worldwide (coastline, inland lake, river, tropical, arctic, arid or humide climates etc.) tropical river & coastline in Indonesia small inland water bodies in Minnesota / USA

5. Slide 5 Concept & Methodology (I) Input images are amplitude & coherence image Exclusion of desert & polar regions SRTM WAM MODIS/Terra Land Cover Types Exclusion of steep terrain SRTM DEM

6. Slide 6 Median filter separately applied both to amplitude & coherence image Threshold method with fix threshold values Two different thresholds to handle complexity of water appearance 1. threshold: reliable classification 2. threshold: potential classification Calculation of water body areas via Chain Code and elimination of water bodies < 1 hectare Fusion of three intermediate water body layers Concept & Methodology (II)

7. Slide 7 Test site demonstration River Elbe, Hamburg, Germany acquired on January 27, 2011 Incidence angle 43.4° to 45.7°

8. Slide 8 Evaluation of classification results (I) Calculation of completeness and correctness reference vector layer data of digital landscape models from the Authoritative Topographic Cartographic Information System (ATKIS)

9. Slide 9 Evaluation of classification results (II) ReferenceCompletenessCorrectness Amplitude ATKIS86.9%92.6% ATKIS water bodies > 1hectare88.1%92.5% Coherence ATKIS79.8%98.7% ATKIS water bodies > 1hectare80.9%98.7% ATKIS: Authoritative Topographic Cartographic Information System

10. Slide 10 Evaluation of classification results (III) Water body mask derived of amplitude image rich in detail susceptible to misclassifications Water body mask derived of coherence image significant and robust results loss of details of small scale water bodies Maximum of a correct & complete water mask with combination of both

11. Slide 11 Outlook Accuracy assessment of the water body detection for different climate zones robustness & global transferability of our approach Mosaicking of different water bodies (neighboring acquisitions resp. first & second year acquisition) to an intermediate & final TanDEM-X water body mask product TanDEM-X DEM editing using TanDEM-X water body mask flattening of outpoking water bodies

12. Slide 12 River Elbe, Hamburg, Germany SAR image Water indication mask DEM edited DEM

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14. Slide 14 Thank you for your attention! Anna Wendleder | Markus Breunig German Remote Sensing Data Center Team SAR Topography Phone: +49 8153 28 3439 Email: Anna.Wendleder@dlr.de | Markus.Breunig@dlr.de