Evaluation of soil conditions using spectral indices from hyperspectral datasets

Soil condition monitoring is critical job by existing chemical treatments which is essential for crop growth for food production in efficient way. As well as soil is spatially and temporally vary everywhere. In the current scenario, hyperspectral remote sensing datasets are widely used by the researchers which provide the minute details of the earth surface objects especially soils. In that constraint, current study focuses the soil condition evaluation using various narrow band spectral indices derived by the hyperspectral imaging and non-imaging datasets. The Analytical Spectral Device (ASD) Field Spec 4 Spectroradiometer instrument was used for receiving the soil reflectance spectra as a non-imaging data source along with Earth Observing-1 (EO-1) satellite Hyperion sensor imaging data. Phulambri Taluka of Aurangabad district of Maharashtra, India was the tested site of present study. Five narrow band spectral indices were used such as Normalized Soil Moisture Index (NSMI), Normalized Difference Soil Index (NDSI), Desertification Soil Index (DSI), Soil Adjusted Vegetation Index (SAVI) and Normalized Difference Vegetation Index (NDVI) to evaluate the soil condition. The experimental results indicate that, the moisture was less in soil with 0.12 maximum values. The NDSI index was previously used on multispectral datasets where green and short wave bands were fully utilized. In the present study, NDSI index was fist time tested on green band 560nm with two short wave bands 1650nm and 2220nm, where short wave band 1650nm was resulted well rather than 2220nm short wave band. The DSI resulted most of the regions with minimum values, hence the soil was not deserted. SAVI and NDVI resulted very well for both the datasets. The study is beneficial in agricultural planning and management in cost effective and rapid way to evaluate the soil condition.