GEMI-DFI model; Non-photosynthetic vegetation; Photosynthetic vegetation; Seasonal variation; Correlation coefficient; Development characteristics; Linear regression models; Normalized difference indices; Normalized difference vegetation index; Normalized differences; Ratio vegetation indices; Earth and Planetary Sciences (all)
Abstract :
[en] Estimating the fractional coverage of the photosynthetic vegetation (fPV) and non-photosynthetic vegetation (fNPV) is essential for assessing the growth conditions of vegetation growth in arid areas and for monitoring environmental changes and desertification. The aim of this study was to estimate the fPV, fNPV and the fractional coverage of the bare soil (fBS) in the lower reaches of Tarim River quantitatively. The study acquired field data during September 2020 for obtaining the fPV, fNPV and fBS . Firstly, six photosynthetic vegetation indices (PVIs) and six non-photosynthetic vegetation indices (NPVIs) were calculated from Sentinel-2A image data. The PVIs include normalized difference vegetation index (NDVI), ratio vegetation index (RVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI), reduced simple ratio index (RSR) and global environment monitoring index (GEMI). Meanwhile, normalized difference index (NDI), normalized difference tillage index (NDTI), normalized difference senescent vegetation index (NDSVI), soil tillage index (STI), shortwave infrared ratio (SWIR32) and dead fuel index (DFI) constitutes the NPVIs. We then established linear regression model of different PVIs and fPV, and NPVIs and fNPV, respectively. Finally, we applied the GEMI-DFI model to analyze the spatial and seasonal variation of fPV and fNPV in the study area in 2020. The results showed that the GEMI and fPV revealed the best correlation coefficient (R2 ) of 0.59, while DFI and fNPV had the best correlation of R2 = 0.45. The accuracy of fPV, fNPV and fBS based on the determined PVIs and NPVIs as calculated by GEMI-DFI model are 0.69, 0.58 and 0.43, respectively. The fPV and fNPV are consistent with the vegetation phonological development characteristics in the study area. The study concluded that the application of the GEMI-DFI model in the fPV and fNPV estimation was sufficiently significant for monitoring the spatial and seasonal variation of vegetation and its ecological functions in arid areas.
Disciplines :
Agriculture & agronomy
Author, co-author :
Guo, Zengkun ; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; University of Chinese Academy of Sciences, Beijing, China
Kurban, Alishir ; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; University of Chinese Academy of Sciences, Beijing, China ; Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, China ; Sino-Belgian Joint Laboratory for Geo-Information, Xinjiang Institute of Ecology and Geography, Urumqi, China
Ablekim, Abdimijit; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; University of Chinese Academy of Sciences, Beijing, China
Wu, Shupu; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; University of Chinese Academy of Sciences, Beijing, China
de Voorde, Tim Van; Department of Geography, Ghent University, Ghent, Belgium ; Sino-Belgian Joint Laboratory for Geo-Information, Ghent University, Ghent, Belgium
Azadi, Hossein ; Université de Liège - ULiège > TERRA Research Centre > Modélisation et développement ; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; Department of Geography, Ghent University, Ghent, Belgium ; Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Prague, Czech Republic
De Maeyer, Philippe; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; Department of Geography, Ghent University, Ghent, Belgium ; Sino-Belgian Joint Laboratory for Geo-Information, Ghent University, Ghent, Belgium
Dufatanye Umwall, Edovia; Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China ; University of Chinese Academy of Sciences, Beijing, China
Language :
English
Title :
Estimation of photosynthetic and non-photosynthetic vegetation coverage in the lower reaches of tarim river based on sentinel-2a data
Funding: This research was funded by the National Natural Science Foundation of China (grant number 32071655; 31570536). Chinese Academy of Sciences President’s International Fellowship Initiative (PIFI, Grant No. 2021VCA0004, 2017VCA0002).
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