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Under the changing climatic scenarios, sustaining agricultural production and enhancing input use efficiency is highly crucial to ensure food security in future. As crop productivity is considerably affected by soil characteristics such as soil organic carbon (SOC), nutrient availability, pH, salinity and soil moisture etc., thus their spatial variability needs to be assessed for site-specific and more efficient management. RS, GIS and GPS can be used quite successfully for assessing spatial variability in these properties. Recently with the advent of highly sophisticated sensors, it is possible to assess various soil properties by observing spectral reflectance in different wavelength bands and computing various spectral indices from the data recorded through satellite remote sensing. Spectral reflectance in different wavelength bands viz. visible, thermal and microwave etc. along with different spectral indices computed from spectral reflectance viz. normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), modified soil adjusted vegetation index (MSAVI), ratio vegetation index (RVI), soil moisture index (SMI), normalised difference water index (NDWI) and normalized difference salinity index (NDSI) etc. are used to retrieve different soil properties from satellite data. Similarly, various spatial interpolation techniques viz. inverse distance weighting (IDW), ordinary kriging (OK), radial basis function (RBF) and empirical bayes kriging (EBK) etc. are used for spatial interpolation of various soil characteristics. A critical review concluded that geospatial techniques can be used successfully for retrieval and spatial interpolation of various soil properties, which can be highly beneficial in site specific management leading to improved input use efficiency and sustained agricultural productivity for future food security. |
