Quick and real-time monitoring of soil organic matter(SOM) distribution based on remote sensing can support the decision-making on precision crop management.However, most previous studies have been aimed at black soil, SOM content of which is commonly higher than 2%.The research about grey desert soil(average content of SOM is less than 2%) has been reported less.This paper tries to quantitatively retrieve SOM of grey soil by using HJ-1A/1B satellite remote sensing images.Ninety-one soil samples are collected from the oasis cotton field in northern Xinjiang, China during 2013-2014.The SOM content of these samples was determined, and the mult-spectral reflectances were measured.The spectrum characteristics of 65 soil samples were analyzed, the correlation analysis was conducted, and the characteristic bands for estimating retrieval model were sought; then, the stepwise regression analysis method was used to build the inversed models.And the models include one-variable linear regressive equation, quadratic regression model, cubic regression model, log-linear regression model, inverse regression model, power function model, growth regression model, S regression model and multiple regression model for different spectrum parameters.By means of comprehensive and comparative analysis of various models, the final monitoring model of SOM was then established.Taking into account the spatial difference between the samples and remote sensing images, 26 soil samples were used to test the model.And there was a good linear relationship between the estimated and the measured SOM values(determination coefficient 0.72).At last, based on the final monitoring mode, the distribution of the SOM was mapped.Results showed that: 1) The reflectance of each band had significant correlation with SOM content, and the reciprocal of reflectance at Band 3 had the most significant correlation with SOM content; 2) The cubic regression model was based on the refectance at Band 3, and combared with other models, it was the optimal one and could be used to retrieve the spatial distribution pattern of SOM in oasis cotton field; 3) Spatial distribution pattern of SOM indicated that the SOM content was higher in the north and south of study area, and lower in the middle.All of the present work implies that although the SOM content of grey desert soil is very different from black soil, the multi-spectral data, such as HJ-1A/1B satellite data, can be effectively used in SOM remote sensing monitoring.This conclusion can not only provide a scientific basis for cotton management and sustainable utilization of farmland in Xinjiang, but also offer the theory support for monitoring soil parameter by using remote sensing technology.