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

Zengkun Guo,Philippe De Maeyer,Hossein Azadi,Alishir Kurban,Edovia Dufatanye Umwali,Tim Van de Voorde,Shupu Wu,Abdimijit Ablekim

doi:10.3390/rs13081458

Abstract

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.

Highlights

Introduction conditions of the Creative CommonsVegetation cover is an important part of the ecosystem, which plays an important role in the soil and water conservation, restraining the desertification process, biodiversity protection and other ecological service and functions etc. [1,2]
This study explored the performance of several Sentinel-2A based photosynthetic vegetation indices (PVIs) by constructing linear regression models in the lower reaches of the Tarim River
The global environment monitoring index (GEMI) index has the best correlation with the fractional coverage of the photosynthetic vegetation (f photosynthetic vegetation (PV)), which is consistent with the conclusion of Liu [38] on the vegetation information monitoring this area

Summary

Introduction

Introduction conditions of the Creative CommonsVegetation cover is an important part of the ecosystem, which plays an important role in the soil and water conservation, restraining the desertification process, biodiversity protection and other ecological service and functions etc. [1,2]. Vegetation cover is an important part of the ecosystem, which plays an important role in the soil and water conservation, restraining the desertification process, biodiversity protection and other ecological service and functions etc. 2021, 13, 1458 of view, vegetation can be divided into two parts: the photosynthetic vegetation (PV). The non-photosynthetic vegetation (NPV) [3]. The PV mainly refers green leaves, while the NPV mainly includes the vegetation litter (dead leaves, dead branches and stems) and crop residues [4,5]. An accurate estimation of the fractional coverage of the photosynthetic (f PV ) and non-photosynthetic vegetation (f NPV ) is of great significance in evaluating the ecological conditions NPV is important as it affects the carbon storage, CO2 exchange capacity and temperature between the surface and soil [6,7] and slows down soil erosion, increases the soil organic matter and improves the soil quality [8,9,10,11,12].

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Conclusion