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Remote sensing inversion of desert soil moisture based on improved spectral indices |
GAO Qi1,2(), WANG Yuzhen1, FENG Chunhui1, MA Ziqiang3, LIU Weiyang1, PENG Jie1, JI Yanzhen2 |
1. College of Plant Sciences, Tarim University, Alar 843300, China 2. Prefecture Geological and Environmental Monitoring Station, Changji 831100, China 3. Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100000, China |
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Abstract Soil moisture is an important indicator affecting dynamic climate changes, vegetation ecological recovery, and land desertification control in arid regions. Using Landsat8 OLI/TIRS multispectral remote sensing images, this study determined the optimal spectral indices by introducing thermal infrared (b10) band to improve nine traditional spectral indices and through significance tests and multiple covariance tests. Then, with the improved spectral indices as the modeling factors and based on the terrain data, this study constructed multispectral comprehensive inversion models of desert soil moisture using the multivariate linear regression (MLR) and random forest (RF) algorithms. Finally, the spatial distribution characteristics of soil moisture and their driving factors were analyzed using the optimal model. The results are as follows: ① The correlation coefficients of the improved spectral indices EBSI, ECI, ECal, ENDVI, and EPDI increased by 0.02~0.11; ② For the prediction datasets of linear and non-linear models, their R 2 increased by 0.12 and 0.05, respectively and their RPD values increased by 0.35 and 0.49, respectively after the spectral indices were improved. Moreover, the RPD value of model RF-II was up to 3.12, and thus this model can accurately predict soil moisture. ③ The accuracy of the non-linear models was significantly higher than that of the linear models. The R 2 of the prediction datasets of MLR-based linear models was only 0.59 and 0.71, while that of the RF-based non-linear models reached 0.86 and 0.91. ④ The distribution of soil moisture was influenced by both natural and artificial factors. The soil moisture content is [0, 5)% and [5, 12)% in the northeastern desert and shows cross-distribution in the southern farmland. Soil moisture is difficult to evaporate in the northern and central desert-oasis transition zones due to inhibiting factors such as the vegetation coverage and surface salt crust, with the content of [15, 20)% and [20, 40)% mostly.
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Keywords
improved spectral index
satellite remote sensing
soil moisture
desert soils
southern Xinjiang arid zone
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Issue Date: 14 March 2022
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