| Soil moisture content inversion of subalpine meadow based on high\|resolution remote sensing image |
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| DOI：10.7606/j.issn.1000-7601.2024.03.24 |
| Key Words: soil moisture content vegetation supply water index spatial variability of soil moisture Qing\|Zang Plateau |
| Author Name | Affiliation | | ZHANG Qipeng | Gansu Normal College for Nationalities, Hezuo, Gansu 747000, China | | TIAN Fuheng | Gansu Normal College for Nationalities, Hezuo, Gansu 747000, China | | Zhuomalancao | Gansu Normal College for Nationalities, Hezuo, Gansu 747000, China | | ZHAO Dichen | Gansu Normal College for Nationalities, Hezuo, Gansu 747000, China |
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| Abstract: |
| This study aims to estimate soil moisture content in the subalpine meadow of the northeastern margin of the Qing\|Zang Plateau using high\|resolution satellite remote sensing images and the vegetation supply water index (VSWI). The suitability of combining high\|resolution remote sensing images (GF-2) with the VSWI method is explored, and the distribution of soil moisture content and its influencing factors are analyzed. The study uses GF-2 and Landsat-7 satellite images to construct a soil moisture inversion model based on the VSWI. The model is applied to the grasslands of Gannan Tibetan Autonomous Prefecture to obtain a soil moisture inversion map. The spatial distribution of soil moisture and its influencing factors are analyzed using semivariogram and principal component analysis. The findings indicated a certain degree of spatial variability in soil moisture content within the study area and different positions, ranging from 0.11% to 60.44%. Soil moisture content showed a positive correlation with slope, elevation, aspect, NDVI, and surface temperature, the distribution of soil moisture content was affected by NDVI, aspect,slope, and elevation. Using the vegetation water supply index method combined with high\|resolution remote sensing image to inversion soil moisture content was feasible, and the model established based on GF-2 remote sensing image had the best fitting degree and is more advantageous than Landsat-7 remote sensing image. |
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