| Title | Performance evaluation of sar texture algorithms for surface water body extraction through an open source python-based engine |
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| Author | Peiman, R; Ali, H; Brisco, B; Hopkinson, C |
| Source | IEEE International Geoscience and Remote Sensing Symposium proceedings vol. 2017-July, 8127660, 2017 p. 3125-3127, https://doi.org/10.1109/IGARSS.2017.8127660 |
| Year | 2017 |
| Alt Series | Natural Resources Canada, Contribution Series 20181518 |
| Publisher | IEEE |
| Document | serial |
| Lang. | English |
| Media | paper; on-line; digital |
| File format | pdf |
| Subjects | geophysics; remote sensing |
| Program | Climate Change
Geoscience |
| Released | 2017 12 04 |
| Abstract | SAR-based image thresholding can be used to detect and map open water body locations and extents. The selection of a reasonable and consistent thresholding approach can be challenging across many
complex landcover types. Besides SAR acquisition characteristics, environmental factors (e.g., emergent vegetation and wind-induced roughening of the water) can cause water locally increased backscatter relative to the characteristic dark appearance
of water in SAR imagery. This is where much attention has been recently devoted to a variety of thresholding methodologies for surface water monitoring with SAR imagery. |
| GEOSCAN ID | 311873 |
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