|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|
synthetic aperture radar (SAR)
|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.|
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