In the karst regions of Southwest China,rocky desertification is one of the most serious problems of land degradation.Because of the inherent merits of macro scale,frequency,efficiency and synthesis,remote sensing is the promising method to monitor and assess karst rocky desertification.However,existing remote sensing methods can not directly be exploited to extract the information on karst rocky desertification owing to the high complexity and heterogeneity of karst environments.Based on NDVI,karst rocky desertification synthesis indices(KRDSI)and lignin-cellulose absorption index(LCA),this study compared the feasibility and accuracy of indicator extraction for the assessment of karst rocky desertification with Hyperion and simulated ASTER images.Results showed that Hyperion imagery can be used to efficiently and directly extract the information on the fractional covers of photosynthetic vegetation,non-photosynthetic vegetation and bare soil,while the proportion of exposed bedrock was not so good due to the different types and weathering processes of carbonate rocks.As for multi-spectral image,ASTER can be used to estimate the fractional cover of photosynthetic vegetation and bare soil,but could not be utilized for accurate estimation of the fractional covers of exposed bedrock and non-photosynthetic vegetation due to the limits of spectral bands and spectral resolution.