Abstract
Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation ecosystems. The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies. However, most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space. This requires extensive data from a vast study area, and may lead to subjective results. In this study, a Modified Temperature-Vegetation Dryness Index (MTVDI) was used to monitor surface soil moisture status using MODIS (Moderate-resolution Imaging Spectroradiometer) remote sensing data, in which the dry edge conditions were determined at the pixel scale based on surface energy balance. The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index (TVDI). The results showed that the R2 for MTVDI and soil moisture obviously improved (0.45 for TVDI, 0.69 for MTVDI). As for spatial changes, MTVDI can also better reflect the actual soil moisture condition than TVDI. As a result, MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.
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Under the auspices of the National Natural Science Foundation of China (No. 41801180), the Natural Science Basic Research Plan in Shaanxi Province of China (No. 2020JQ415, 2019JQ-767)
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Wang, H., Li, Z., Zhang, W. et al. A Modified Temperature-Vegetation Dryness Index (MTVDI) for Assessment of Surface Soil Moisture Based on MODIS Data. Chin. Geogr. Sci. 32, 592–605 (2022). https://doi.org/10.1007/s11769-022-1288-y
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DOI: https://doi.org/10.1007/s11769-022-1288-y