Estimation and Mapping of Aboveground Vegetation Water Storage in Jiuzhaigou Nature Reserve Using Sentinel Imagery
Junjie Lei 1,2,3
Xin Yang 1,3
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College of Earth Science, Chengdu University of Technology, Chengdu, 610059, China
College of Surveying and Planning, Shangqiu Normal University, Shangqiu 476000, China
Laboratory of Earth-Science Spatial Information Technology of Ministry of Land and Resources of P.R. China, Chengdu University of Technology, Chengdu 610059, China
Submission date: 2022-04-04
Final revision date: 2022-08-27
Acceptance date: 2022-09-29
Online publication date: 2022-12-13
Publication date: 2023-01-12
Corresponding author
Wunian Yang   

Chengdu University of Technology, China
Pol. J. Environ. Stud. 2023;32(1):599-608
In order to scientifically evaluate water resource reserves and the regulation mechanisms of vegetation in a hydrological cycle, it is necessary to improve the inversion accuracy of aboveground vegetation water storage (AVWS). To calculate more accurate AVWS, Sentinel-1 (S1) and Sentinel-2 (S2) imagery were used to map the AVWS of the Jiuzhaigou Nature Reserve. Predictors extracted from S1 and S2 imagery were divided into three modelling groups: S1 data (S1G), S2A data (S2G) and S12G data (combining S1G and S2G). The best linear model (LM) and Random Forest (RF) regression model of AVWS were established by predictors of the three groups; finally, RF regression models based on S2G (10-fold cross-validation determination coefficients [R2] = 0.67, relative root mean square error [rRMSE] = 13.78 %) and S12G (R2 = 0.72, rRMSE = 11.94 %) were selected for mapping AVWS in the study area. The results show that the aboveground vegetation water storage (AVWS) of the study area could be effectively estimated and mapped based on synergistic predictors derived from S1 and S2, as well as S12G predictors (cooperating with S1G and S2G).
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