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Retrieval of High-Resolution Vegetation Optical Depth from Sentinel-1 Data over a Grassland Region in the Heihe River Basin

Authors :
Zhilan Zhou
Lei Fan
Gabrielle De Lannoy
Xiangzhuo Liu
Jian Peng
Xiaojing Bai
Frédéric Frappart
Nicolas Baghdadi
Zanpin Xing
Xiaojun Li
Mingguo Ma
Xin Li
Tao Che
Liying Geng
Jean-Pierre Wigneron
Source :
Remote Sensing; Volume 14; Issue 21; Pages: 5468
Publication Year :
2022
Publisher :
Multidisciplinary Digital Publishing Institute, 2022.

Abstract

Vegetation optical depth (VOD), as a microwave-based estimate of vegetation water and biomass content, is increasingly used to study the impact of global climate and environmental changes on vegetation. However, current global operational VOD products have a coarse spatial resolution (~25 km), which limits their use for agriculture management and vegetation dynamics monitoring at regional scales (1–5 km). This study aims to retrieve high-resolution VOD from the C-band Sentinel-1 backscatter data over a grassland of the Heihe River Basin in northwestern China. The proposed approach used an analytical solution of a simplified Water Cloud Model (WCM), constrained by given soil moisture estimates, to invert VOD over grassland with 1 km spatial resolution during the 2018–2020 period. Our results showed that the VOD estimates exhibited large spatial variability and strong seasonal variations. Furthermore, the dynamics of VOD estimates agreed well with optical vegetation indices, i.e., the mean temporal correlations with normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and leaf area index (LAI) were 0.76, 0.75, and 0.75, respectively, suggesting that the VOD retrievals could precisely capture the dynamics of grassland.

Details

Language :
English
ISSN :
20724292
Database :
OpenAIRE
Journal :
Remote Sensing; Volume 14; Issue 21; Pages: 5468
Accession number :
edsair.doi.dedup.....8d89d37492a149dd83be9a403a687b6d
Full Text :
https://doi.org/10.3390/rs14215468