Evaluation of optical and microwave-derived vegetation indices for monitoring aboveground biomass over China

Autor: Zhongbing Chang, Lei Fan, Jean-Pierre Wigneron, Ying-Ping Wang, Xiaojun Li, Mengjia Wang, Xiangzhuo Liu, Huan Wang, Tianxiang Cui, Ling Yu, Jianping Wu, Xin Xiong, Shuo Zhang, Xuli Tang, Junhua Yan
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Geo-spatial Information Science, Pp 1-16 (2024)
Druh dokumentu: article
ISSN: 10095020
1993-5153
1009-5020
DOI: 10.1080/10095020.2024.2311858
Popis: The microwave-derived vegetation optical depth (VOD) products were used to monitor aboveground biomass (AGB) at regional to global scales, but the ability of VOD to monitor AGB in China is uncertain. This study evaluated the sensitivity of four VOD products (e.g. L-VOD, IB-VOD, LPDR-VOD, and Liu-VOD) and optical vegetation indices (VI) (e.g. NDVI, EVI, LAI, and tree cover from MODIS) to the AGB across China. Our results showed tree cover product has the highest spatial agreement with reference AGBs (indicated by the median correlation value of 0.85), followed by L-VOD (with a median correlation value of 0.80), which performs better than other VIs and VODs. Further comparisons between reference and estimated AGB computed using the fitted logistic regression showed that AGB estimations from tree cover and L-VOD outperformed the estimations from other VIs and VODs over most vegetation types (except forest), indicated by the higher median correlation value of 0.86 and 0.83 and lower RMSD of 23.9 and 27.3 Mg/ha, respectively. The good performance of tree cover could be partly due to that tree cover product is not independent from the reference AGBs. The good performance of L-VOD can be explained by its higher sensitivity to the vegetation characteristics of the entire canopy (including woody component), relative to other VODs and VIs. Among the six reference AGB products, Saatchi-WT and Saatchi-RF products were found to have the best correlations with VIs and VODs. This study demonstrates that microwave VODs, particularly L-VOD, are effective proxies for large-scale monitoring of vegetation AGB in China.
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