Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/33681
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Clear-Cut Detection and Mapping Using Sentinel-1 Backscatter Coefficient and Short-Term Interferometric Coherence Time Series
Author(s): Akbari, Vahid
Solberg, Svein
Contact Email: vahid.akbari@stir.ac.uk
Keywords: Clear-cut
expectationmaximization (EM)
radar backscatter
repeat-pass coherence
Sentinel-1 (S-1)
synthetic aperture radar (SAR)
Issue Date: 2022
Date Deposited: 30-Nov-2021
Citation: Akbari V & Solberg S (2022) Clear-Cut Detection and Mapping Using Sentinel-1 Backscatter Coefficient and Short-Term Interferometric Coherence Time Series. IEEE Geoscience and Remote Sensing Letters, 19, Art. No.: 4006405. https://doi.org/10.1109/lgrs.2020.3039875
Abstract: Forest clear-cut detection would be valuable for forest management, if it could be done routinely in near-real-time with a spaceborne synthetic aperture radar (SAR) system, which provides data all year and all-weather. In Sentinel-1 (S-1) time-series data, a forest clearing will lead to reduced backscatter intensity and increased interferometric SAR (InSAR) coherence magnitude. A time-series of 108 interferomtric wide (IW) Single look complex (SLC) S-1 images collected in 2016, 2017, and 2018 are used to study the potential for mapping clear-cut areas in eastern Ireland. We combined multitemporal InSAR coherence and backscatter intensity for the detection. This is an extension of previous studies that used either backscatter intensity or InSAR coherence magnitude, while we show the added value of both together. Coherence magnitude was the strongest predictor of the two.
DOI Link: 10.1109/lgrs.2020.3039875
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