Soil moisture estimation using triangular method at higher resolution from MODIS products

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 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 applicability 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. •Soil moisture was estimated based on triangular network method.•NDVI at 250 m was derived from MODIS reflectance data.•TsHARP and TPS models were applied to downscale surface temperature from 1 km to 250 m.•TVDI and in-situ soil moisture shows significant high negative correlation (R2 = −0.80).