Extraction of Karst Rocky Desertification Information from Eo-1 Hyperion Data

Karst rocky desertification is a special kind of land desertification developed under violent human impacts on the vulnerable ecogeo-environment in karst ecosystem. The process of karst rocky desertification results in simultaneous and complex variations of many interrelated soil, rock and vegetation biophysical parameters, rendering it difficult to develop simple and robust remote sensing mapping and monitoring approaches. In this study, we aimed to use Earth Observing 1 (EO-1) Hyperion hyperspectral data to extract the karst rocky desertification information. A spectral unmixing model based on Monte Carlo approach, AutoSWIR, was used to quantify the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare bedrock. The results showed that SWIR2 (2.1-2.4μm) region of the spectrum were significantly different in PV, NPV and bare rock spectral properties. It has limitations in using full optical range (0.4-2.5μm) or only SWIR2 region of Hyperion to decompose image into PV, NPV and bare bedrock covers. However, when use the tied-SWIR2, the sub-pixel fractional covers of PV, NPV and bare bedrock constituents were accurately estimated. It was due to the tied-SWIR2 minimized the contribution of intra-canopy structural variation to nonlinear photon-tissue interactions. Our study indicated that AutoSWIR unmixing spectral model is a useful tool to accurately extract mixed ground objects in karst ecosystem. Karst rocky desertification information can be accurately extracted from EO-1 Hyperion. Hyperspectral data can provide a powerful methodology toward understanding the extent and spatial pattern of karst rocky desertification in Southwest China. ∗ Corresponding author.