| Grassland is one of the most important vegetation forms in China. It is an important renewal resource and raw material base for the animal husbandry. To man, the grassland plays a key role in living and development. But the grassland deterioration has alerted us. From 1989 to 1999, the deterioration area had increased by 4333 thousand hm2. The deterioration can cause the descent with grassland ecosystem productivity and net ecosystem productivity. Overgrazing and reclaiming cause the deterioration. So investigating the grassland resource is very important to guide husbandry animal and figure out macro-economy and development plan.Remote sensing shows its charming in investigating resources, monitoring environment and planning region etc. Many researchers have spent much time in grassland resource by using Landsat/MSS, Landsat/TM and NOAA/AVHRR. Based on the actual use-time and the practical yield, the carrying capacity measured is crucial. Yet the relevant literatures about using remote sensing to measure the grassland according to season were seldom.Aletai prefecture lies in the northern of the Xinjiang Uygur Autonomous Region. Aletai have 9842.4 thousand hm2 grassland area. 7239.3 thousands hm2 can be utilized directly. It is one of the important pastures in China and the central grassland animal husbandry bases in Xinjiang. As a simple stock raising district,the seasonal grazing is the traditional use means.MODIS's time resolution is superior to TM'and SPOT's. While its spatial resolution is bigger than NOAA/AVHRR's. Since MODIS was launched in 1999,relevant MODIS literatures in grassland applications were short.The research utilized ERDAS IMAGINE software to process the MODIS datum in order to match the measured values. The correlation relationship between the normalized difference vegetation index from MODIS and the yield of grassland was regressed. The yield of the grassland and the classified output according to the classification rule were provided. With GIS, the carrying capacity of the summer, winter, spring and autumn pasture has been analysed.The main results of the research are as follows:(1) By collecting a long-time ARNDVI, every maximal value of pictorial element was abstracted. This can improve the accuracy.(2) The relationship of ARNDVI and the survey yield had been compared and the regression model was worked out according to seasonal pastures. Spring and autumn pasture:y1=137.8311+1.219613x 0≤x≤190y2=-90.3710+1.243571x 255≥x>190 R=0.857 Winter pasture:y1=57.31877+0.021251x 0≤x≤121　　　　　　　　　　　　　 y2=-579.465+5.148731x 255≥x>121 R=0.867　　　　　　　Summer pasture:y1=17.19495+0.411811x 0≤x≤148 　　　　　　　　　　　 y2=-23.9173+1.966378x 255≥x>148 R=0.807y—grassland yield ,x—ARNDVI number,R—Correlation expressed between y and x(3) The research showed that in the year 2002 the total area was 9640504.24hm2 in Aletai prefecture. According to the classification, the 3rd grade, 4th grade, 5th grade and 6th grade accounted for 3.46%,34.95%,13.14% and 33.26% respectively. The theoretical carrying capacity in 2002 was 6584005 sheep units. But the practical carrying capacity was 7887390 sheep units and so overload 48.38%. Summer pasture became the key pasture. So comply with the use from "summer pasture's preponderance" add to spring and autumn pasture and winter pasture. Because of the limit time and so on, some further study as followed should be carried out.(1) The better vegetation index should be selected by thoroughly research about the correlation between vegetation index and the yield.(2) The stable regression model should be established. So more time should be spent to establish grassland ecological environment security measures index and monitoring warning system.(3) Overgrazing and the climate element are two kinds of viewpoint leading to grassland deterioration. Soil use and the soil cover alternation is a pressing task in the world environmental change research...
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