2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2017
DOI: 10.1109/igarss.2017.8127660
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Performance evaluation of sar texture algorithms for surface water body extraction through an open source python-based engine

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Cited by 4 publications
(3 citation statements)
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“…Extraction of the threshold decibel (dB) ranges that represent surface water was sampled over a consistent area polygon (70 ha in area [28,000 pixels]) at Chestermere Lake, which is a controlled reservoir. The threshold (dB) sampling routine (95th percentile) is presented as a manual process in this study, and the values are scene specific due to weather effects on the backscattering but can be automated based on training data or other surface water inventories (Peiman, Husam, Brisco, & Hopkinson, ). Pixels not selected as surface water after the FAV filter and not in FGAMMA are then not included as open water to again preserve edges (White et al, ).…”
Section: Methodsmentioning
confidence: 99%
“…Extraction of the threshold decibel (dB) ranges that represent surface water was sampled over a consistent area polygon (70 ha in area [28,000 pixels]) at Chestermere Lake, which is a controlled reservoir. The threshold (dB) sampling routine (95th percentile) is presented as a manual process in this study, and the values are scene specific due to weather effects on the backscattering but can be automated based on training data or other surface water inventories (Peiman, Husam, Brisco, & Hopkinson, ). Pixels not selected as surface water after the FAV filter and not in FGAMMA are then not included as open water to again preserve edges (White et al, ).…”
Section: Methodsmentioning
confidence: 99%
“…Texture analysis is typically performed over a single backscatter channel of SAR data (i.e., HH, HV, VH, or VV), analysing the spatial variation in image appearance. In the context of wetlands, texture analysis has been applied to vegetation community analysis and/or flood area mapping (i.e., open water extent mapping) with success [203,204]. In many cases, textural components of SAR imagery have been utilised in the manual interpretation of vegetation and wetland land cover classes [205,206].…”
Section: Texture Analysismentioning
confidence: 99%
“…This is due to the high dielectric constant of a (smooth) water surface, making it a specular reflector, meaning very little backscatter is detectable at the sensor, causing it to appear dark in imagery [11,13]. While texture analysis (i.e., analysing the spatial variation in image appearance) has been used to threshold open water surfaces [14], the most common method of mapping these features is through backscatter intensity thresholding schemes [13,15,16], where backscatter below a defined threshold is classified as water. For example, DeLancey et al [17] applied a threshold based on the local minimum between the land/water bimodal backscatter distribution.…”
Section: Introductionmentioning
confidence: 99%