This paper presents the SARWATER algorithm as a valid and robust tool for automatic extraction of surface waters and hydroperiod mapping from time series of Synthetic Aperture Radar (SAR) data. The algorithm relies on a parametric thresholding approach applied to bimodal SAR backscatter intensity distributions, investigating the use of diverse polarizations. The method is assessed by means of a dataset of 116 Sentinel-1 dual-polarized (VH+VV) images covering the wetland “Zone Umide della Capitanata” (Italy) during the period Sep 1, 2021-Aug 31, 2022. The results from all SAR-derived water masks, in comparison with the masks from in field survey and expert knowledge, show that all polarizations yield robust time series of water masks for hydroperiod extraction. Moreover, the geometric mean from both polarizations results preferable as it ensures a higher number of images characterized by bimodality, making it well-suited for method application.

AUTOMATED SURFACE WATERS AND HYDROPERIOD MAPPING BY MEANS OF SAR SENTINEL-1 TIME SERIES

V. Tomaselli;M. Adamo
2024-01-01

Abstract

This paper presents the SARWATER algorithm as a valid and robust tool for automatic extraction of surface waters and hydroperiod mapping from time series of Synthetic Aperture Radar (SAR) data. The algorithm relies on a parametric thresholding approach applied to bimodal SAR backscatter intensity distributions, investigating the use of diverse polarizations. The method is assessed by means of a dataset of 116 Sentinel-1 dual-polarized (VH+VV) images covering the wetland “Zone Umide della Capitanata” (Italy) during the period Sep 1, 2021-Aug 31, 2022. The results from all SAR-derived water masks, in comparison with the masks from in field survey and expert knowledge, show that all polarizations yield robust time series of water masks for hydroperiod extraction. Moreover, the geometric mean from both polarizations results preferable as it ensures a higher number of images characterized by bimodality, making it well-suited for method application.
2024
979-8-3503-6032-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/506583
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