Prediction of Soil Organic Carbon by Hyperspectral Remote Sensing Imagery

Conventional analyses of soil characteristic are expensive, time-consuming, and may result in environmental pollutants. Hence, the objective of this study was: 1) to investigate the potential of VIS-NIR spectroscopy to estimate soil organic carbon (SOC), 2) to use the Hyper ion reflectance data (400-2500 nm) to map SOC in the bare soils. Forty-nine soil samples were collected from the soil surface (0-10 cm) in Zhangye city. Models for SOC showed moderate accuracy (R²>;0.6, RPD>;1.5). The method of Hyper ion image offers a fresh opportunity for modeling parameters of other non-photoactive soil nutrients.