Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2015, Vol. 31 ›› Issue (23): 224-229.doi: 10.11924/j.issn.1000-6850.casb15030109

Special Issue: 资源与环境 农业生态

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Eco-Factor Feature Analysis in Kashgar City Based on Remote Sensing Data

亚库普.约麦尔   

  • Received:2015-03-13 Revised:2015-04-29 Accepted:2015-05-15 Online:2015-08-20 Published:2015-08-20

Abstract: The analysis of city ecological sensitive factor and its distribution characteristics plays an important role in the city environmental management and the formulation of the development policies in regional society and economy. The characteristics of ecological factors in Kashgar city were analyzed using the method of ArcGIS spatial analysis and single factor analysis. 5 ecological sensitive factors were selected including slope, elevation, vegetation index (NDVI), land use types and water. The results showed that: the high sensitive and sensitive areas mainly distributed in high NDVI, low terrain and slope and large green area, while the low sensitive and non-sensitive areas distributed in hills, uncultivated and unused lands of high terrain and slope. The biggest proportion among the sensitive factors was the water factor, and the smallest was the slope factor, and the two factors accounted for 75.46% and 0.33%, respectively. In terms of ecological sensitive degree, the degree of sensitivity was low in the area of high slope, while it was high in the area of low slope, the sensitivity was low in the area of high terrain, while it was high in the area of low terrain. From the characteristics of ecological sensitive areas, it could be concluded that the self-recovery ability was poor in high sensitive areas, the sensibility was in high degree; the moderate sensitive areas had the problems of weak ecological function and unstable ecosystem; the ecosystems of low ecological and non- ecological sensitivity were stable, the sensibility was in low degree, and the ability of bearing the external factors' damage and interference was strong.