Hyperspectral Data Recognition and Mapping of Soil Salinization in Arid Environments

摘要

Hyperspectral imagery of airborne imaging spectrometer (Pushbroom Hyperspectral Imager (PHI)) was acquired over KeLaMaYi, which situated in arid region of northwestern China. In situ hyperspectral data obtained with FieldSpec® Handheld spectrometer (ASD) simultaneously were analyzed for recognition of soil salinization. Some types of transformation were applied to the reflectance data of 60 soil samples, which preprocessed with a simple smoothing followed by band merging. A comparative study among these methods was made to ascertain their applicability for recognition accuracies. After multivariate analysis between ion concentration and reflectance data or their derivatives, a best statistical model was then extracted to predict the soil salinity and PH. Using this prediction model, subpixel classification applied to the corrected imagery helped to yield quantitative maps of soil salinity and PH. Such maps contributed to suggesting soil distribution and aggregation, estimating the spatial controls of erosion, and consequently, helping to plan soil improvement and soil conservation schemes.