The micrograss patch on the grassland surface refers specifically to t he patches shown by the mouse holes,bare soil,and vegetation on desertified grasslands in hyperspectral imag es.These are important indicators for evaluating grassland degradation.The identification and classification of s urface micro-plaques is based on the basic work of remote sensing grassland degradation monitoring and evaluation res earch,and plays a crucial role in grassland regional planning,system restoration and reconstruction.Due to the r easons of hyperspectral acquisition and analysis,there are few studies on the identification of hyperspectral micro scopic plaques.This study collected the hyperspectral data from the surface micr o-plaques in desert grasslands and proposed the surface mini-patch index (SMPI) method to achieve high-precision identificat ion of grassland surface micro-plaques classification.The research results show that the SMPI method c an identify and classify the surface micro-plaques in desertification grasslands with high accuracy.The Kappa coeff icient verification shows that the overall verification accuracy is higher than 96%.This study provides the basis for monitoring and quantitative inversion of grassland degradation using drones or low-altitude remote sensing.