Soil moisture plays a vital role in high agriculture yield and many satellite products are available to study their potentiality in soil moisture estimation. Hence, we considered a triangular network method (TVDI) based on MODIS products for soil moisture estimation. The reflectance data of MODIS was used to derive NDVI at 250 m and surface temperature was downscaled from 1 km to 250 m using TsHARP and TPS models. Furthermore, we have explored the ability of the TVDI at 250 m spatial resolution to capture daily soil moisture. TVDI and in-situ soil moisture has high negative correlation (R² = −0.80). The results show that the TVDI value on 19 January, 2013 was highly co-related with in-situ soil moisture on 19 January, 2013. The TVDI value after irrigation of second week of February, 2013 was lower than for periods of no irrigation month (January). Therefore, mapping of soil moisture under crop condition can be possible with TVDI and satellite data input.

土壤水分在高农业产量中起着至关重要的作用，许多卫星产品可用于研究它们在土壤水分估算中的潜力。因此，我们考虑了基于 MODIS 产品的三角网络方法 (TVDI) 用于土壤水分估计。MODIS 的反射率数据用于推导 250 m 处的 NDVI，并使用 TsHARP 和 TPS 模型将地表温度从 1 km 缩小到 250 m。此外，我们还探索了 TVDI 在 250 m 空间分辨率下捕获每日土壤水分的能力。TVDI 与原位土壤水分呈高度负相关（R ² = -0.80）。结果表明，2013年1月19日的TVDI值与2013年1月19日的原位土壤水分呈高度相关。2013年2月第二周灌水后的TVDI值低于无灌月时段（一月）。因此，利用 TVDI 和卫星数据输入可以绘制作物条件下的土壤水分图。