| Titre | Performance evaluation of sar texture algorithms for surface water body extraction through an open source python-based engine |
| Auteur | 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 |
| Année | 2017 |
| Séries alt. | Ressources naturelles Canada, Contribution externe 20181518 |
| Éditeur | IEEE |
| Document | publication en série |
| Lang. | anglais |
| DOI | https://doi.org/10.1109/IGARSS.2017.8127660 |
| Media | papier; en ligne; numérique |
| Formats | pdf |
| Sujets | télédétection; géophysique |
| Programme | Géosciences de changements climatiques |
| Diffusé | 2017 12 04 |
| Résumé | (disponible en anglais seulement)
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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