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TanDEM-X Water Indication Mask: Generation and First Evaluation Results

Figure 1

Figure 1
Workflow of the Water Body Detection mask and of the resulting final Water Indication Mask.

Figure 2

Figure 2
Histogram of coherence for SRTM water pixels. For this statistic, 1700 globally random distributed TanDEM-X scenes are used. The coherence values between 0 and 0.3 represent water, the coherence values between 0.6 and 1 represent land and hence misclassifications due to SWBD.

Figure 3

Figure 3
(a) Amplitude image of the first study area around the river Elbe in the west of Hamburg, Germany, acquired on 27th January 2011, (b) corresponding coherence image, (c) Water body detection mask derived from the amplitude image: first amplitude threshold detections displayed in dark blue, second's in light blue, (d) Water body detection mask derived from the coherence image.

Figure 4

Figure 4
(a) Amplitude image of the second study area around Lake Apopka in the west of Orlando, USA, acquired on 12th February 2011, (b) corresponding coherence image, (c) Water body detection mask derived from the amplitude image: first amplitude threshold detections displayed in dark blue, second's in light blue, (d) Water body detection mask derived from the coherence image.

Figure 5

Figure 5
(a) Water Indication Mask at the German Bight: mosaicked result of 46 input water body detection masks which were acquired between 20th October 2010 and 9th December 2011 covering an area of Formula$2^{\circ}\times 3^{\circ}$ containing the result of the amplitude threshold and the coherence threshold. The darker the blue, the oftener the pixel is classified as water. (b) Subset of the Water Indication Mask of the river Elbe (black rectangle in (a)).

Figure 6

Figure 6
(a) TanDEM-X DEM with unedited water areas of the first study area around the river Elbe in the west of Hamburg, Germany, (b) TanDEM-X DEM with edited water areas of the first study area around the river Elbe in the west of Hamburg, Germany.