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  • Challenge…. The currently sophisticated methods like parametric and geometric active contour models and texture measures are not efficient enough to be applied for near-real-time image processing and cannot be applied fully automatically. The only possibility here to keep up with the amount of daily incoming data during the TanDEM-X mission is to process the data fully automatically and to use a less time-consuming threshold method. In this case we apply the threshold method on….
  • … the amplitude image and on the coherence image as we can see here.
  • As you can see all water bodies are appearing smooth and dark without any disturbances caused by wind effect, snow and ice coverage or others
  • Hamburg, Nord-Ostsee-Kanal WAM erklären, wie WAM editing coherence low/amp dark filtering/Glättung
  • Hamburg, Nord-Ostsee-Kanal WAM erklären, wie WAM editing coherence low/amp dark filtering/Glättung
  • igarss_2011_breunig_DLR_TDM_water_mask.ppt

    1. 1. 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 IGARSS’11, Vancouver
    2. 2. Outline <ul><li>Introduction </li></ul><ul><li>Definition of the TanDEM-X water indication mask </li></ul><ul><li>Challenges for TanDEM-X water body detection </li></ul><ul><li>Concept & methodology of water body detection </li></ul><ul><li>Test site demonstration </li></ul><ul><li>Evaluation of classification results </li></ul><ul><li>Outlook </li></ul>Slide
    3. 3. Definition of the TanDEM-X water indication mask <ul><li>Global mission – global DEM – global water body mask </li></ul><ul><li>Water body mask primarily extracted for post-processing DEM editing </li></ul><ul><ul><li>ongoing work in flattening of outpoking water bodies </li></ul></ul><ul><ul><li>correct orthorectification of remote sensing data </li></ul></ul><ul><li>No production of a complete global water body inventory </li></ul>Slide Kurnool Kadapa Channel / India frozen Lake Taimyr / Russia
    4. 4. Challenges for TanDEM-X water body detection <ul><li>TanDEM-X mission with 2 global acquisition data sets in 2011 & 2012 </li></ul><ul><li>The water body detection runs completely data-driven </li></ul><ul><li>Processing at Raw DEM level (30*50 km ≈ 8.000*10.000 pixels) </li></ul><ul><li>400 up to 800 Raw DEM per day to be processed </li></ul><ul><li>Therefore maximum computing time of 3 minutes per product </li></ul><ul><li>Applicable for different appearances of water bodies worldwide (coastline, inland lake, river, tropical, arctic, arid or humide climates etc.) </li></ul>Slide tropical river & coastline in Indonesia small inland water bodies in Minnesota / USA
    5. 5. Concept & Methodology (I) <ul><li>Input images are amplitude & coherence image </li></ul><ul><li>Exclusion of desert & polar regions </li></ul><ul><ul><li>SRTM WAM </li></ul></ul><ul><ul><li>MODIS/Terra Land Cover Types </li></ul></ul><ul><li>Exclusion of steep terrain </li></ul><ul><ul><li>SRTM DEM </li></ul></ul>Slide
    6. 6. Concept & Methodology (II) Slide <ul><li>Median filter separately applied both to amplitude & coherence image </li></ul><ul><li>Threshold method with fix threshold values </li></ul><ul><ul><li>Two different thresholds to handle complexity of water appearance </li></ul></ul><ul><ul><li>1. threshold: reliable classification </li></ul></ul><ul><ul><li>2. threshold: potential classification </li></ul></ul><ul><li>Calculation of water body areas via Chain Code and elimination of water bodies < 1 hectare </li></ul><ul><li>Fusion of three intermediate water body layers </li></ul>
    7. 7. Test site demonstration <ul><li>River Elbe, Hamburg, Germany </li></ul><ul><li>acquired on January 27, 2011 </li></ul><ul><li>Incidence angle 43.4° to 45.7° </li></ul>Slide
    8. 8. Evaluation of classification results (I) Slide <ul><li>Calculation of completeness and correctness </li></ul><ul><li>reference vector layer data of digital landscape models from the Authoritative Topographic Cartographic Information System (ATKIS) </li></ul>
    9. 9. Evaluation of classification results (II) Slide ATKIS: Authoritative Topographic Cartographic Information System Reference Completeness Correctness Amplitude ATKIS 86.9 % 92.6 % ATKIS water bodies > 1hectare 88.1 % 92.5 % Coherence ATKIS 79.8 % 98.7 % ATKIS water bodies > 1hectare 80.9 % 98.7 %
    10. 10. Evaluation of classification results (III) <ul><li>Water body mask derived of amplitude image </li></ul><ul><ul><li>rich in detail </li></ul></ul><ul><ul><li>susceptible to misclassifications </li></ul></ul><ul><li>Water body mask derived of coherence image </li></ul><ul><ul><li>significant and robust results </li></ul></ul><ul><ul><li>loss of details of small scale water bodies </li></ul></ul><ul><li>Maximum of a correct & complete water mask with combination of both </li></ul>Slide
    11. 11. Outlook <ul><li>Accuracy assessment of the water body detection for different climate zones </li></ul><ul><ul><li>robustness & global transferability of our approach </li></ul></ul><ul><li>Mosaicking of different water bodies (neighboring acquisitions resp. first & second year acquisition) to an intermediate & final TanDEM-X water body mask product </li></ul><ul><li>TanDEM-X DEM editing using TanDEM-X water body mask </li></ul><ul><ul><li>flattening of outpoking water bodies </li></ul></ul>Slide
    12. 12. Slide River Elbe, Hamburg, Germany <ul><li>SAR image </li></ul><ul><li>Water indication mask </li></ul><ul><li>DEM </li></ul><ul><li>edited DEM </li></ul>
    13. 13. Slide
    14. 14. Slide 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
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