Estimation of Photosynthetic and Non-Photosynthetic Vegetation Coverage in the Lower Reaches of Tarim River Based on Sentinel-2A Data

Estimating the fractional coverage of the photosynthetic vegetation (f_PV) and non-photosynthetic vegetation (f_NPV) 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 f_PV, f_NPV and the fractional coverage of the bare soil (f_BS) in the lower reaches of Tarim River quantitatively. The study acquired field data during September 2020 for obtaining the f_PV, f_NPV and f_BS . 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 f_PV, and NPVIs and f_NPV, respectively. Finally, we applied the GEMI-DFI model to analyze the spatial and seasonal variation of f_PV and f_NPV in the study area in 2020. The results showed that the GEMI and f_PV revealed the best correlation coefficient (R² ) of 0.59, while DFI and f_NPV had the best correlation of R² = 0.45. The accuracy of f_PV, f_NPV and f_BS based on the determined PVIs and NPVIs as calculated by GEMI-DFI model are 0.69, 0.58 and 0.43, respectively. The f_PV and f_NPV 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 f_PV and f_NPV estimation was sufficiently significant for monitoring the spatial and seasonal variation of vegetation and its ecological functions in arid areas.