Dual Polarimetric Radar Vegetation Index for monitoring forest moisture stress using time series of Sentinel-1 SAR data

利用Sentinel-1 SAR数据时间序列的双极化雷达植被指数监测森林水分胁迫

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Abstract

Global warming and anthropogenic climate change have intensified drought occurrences, raising concerns about their escalating frequency, intensity, and persistence. With the projection that droughts will increase at the end of the century, it is important to find efficient and cost-effective methods to assess and monitor drought impacts. We leverage freely available satellite-based remote sensing images to study drought stress in forest. In this study, we evaluate the impact of intense and prolonged drought on temperate broadleaf deciduous forests using Sentinel-1 (S1) Synthetic Aperture Radar (SAR) time series data. For the first time, we used the S1-derived Dual Polarimetric Radar Vegetation Index (DpRVI) to detect and characterize drought effects in forests. Monthly median DpRVI deviations were obtained from S1 SAR images acquired between 13 October 2014 and 3 July 2023. The forest exhibited drought effects through a decline in DpRVI during droughts. These can be attributed to both reduced canopy branches and leaves, and decreased canopy water content. The onset of drought effects in 2018 was captured with negative median DpRVI deviations. An accumulated effect of the multi-year drought 2018-2020 occurred, as evident by increased negative median DpRVI deviations in the subsequent years up to 2021. This study demonstrates the potential of using S1-derived DpRVI to assess the impacts of droughts on broadleaf forest canopies. Further investigation should be carried out to discriminate the relative contributions of the declining canopy water content and changes in the amount and structure of canopy branches and leaves to the observed DpRVI decline.

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