Spatial soil organic carbon (SOC) prediction by regression kriging using remote sensing data

Abstract

The present study has illustrated the estimation of the soil organic carbon (SOC) distribution from point survey data (prepared after laboratory test) by a hybrid interpolation method, viz. regression kriging (RK) in a part of the Narmada river basin in the central India. In this study, eight selected predictor variables are used such as, brightness index (BI), greenness index (GI), wetness index (WI), normalized difference vegetation index (NDVI), vegetation temperature condition index (VTCI), digital elevation model (DEM), and slope and compound topographic index (CTI). The RK method has given satisfactory results as observed from the level of accuracy. Finally, the amount of SOC content in varied slope, soil and landuse categories has been analysed. Concentration of SOC has been observed to be more in low elevated areas in clay soil with mainly agricultural and vegetated lands.

Keywords

• SOC
• Hybrid interpolation
• Regression kriging
• Predictor variables