Abstract
Soil moisture has a significant influence in the occurrence of drought since it influences the energy exchange between the atmosphere and the land surface. This paper discuss about the significance of soil moisture and the estimation of soil moisture index (SMI) using remote sensing. Optical and the thermal spectra is processed in SAGA GIS for the computation of Land Surface Temperature (LST) using thermal band of Landsat 8 and the Normalized difference vegetation (NDVI) using the Red and Near Infrared Band of Landsat 8. A linear regression analysis is performed between LST and the NDVI is to estimate the soil moisture index. The derived soil moisture index is used to map the severity of drought from extreme drought to no drought condition and the results were validated with the NDVI results. The Results shows that the relationship between LST and the NDVI can be utilized to map drought risk areas with the help of Landsat-8 images at a higher resolution which is beneficial for hydrological studies.
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John, J., Jaganathan, R., Dharshan Shylesh, D.S. (2022). Mapping of Soil Moisture Index Using Optical and Thermal Remote Sensing. In: Marano, G.C., Ray Chaudhuri, S., Unni Kartha, G., Kavitha, P.E., Prasad, R., Achison, R.J. (eds) Proceedings of SECON’21. SECON 2021. Lecture Notes in Civil Engineering, vol 171. Springer, Cham. https://doi.org/10.1007/978-3-030-80312-4_65
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