The study area lies in the Dadu River drainage area in upstream Yangtze River.The spatial distribution of subalpine coniferous forests in 1989 and 2009 was extracted by means of a combined method of object orientation and visual interpretation,and then the overlaying analysis of these data was conducted.The type and spatial location of succession were discovered and served as the sample of dependant variable.Meanwhile,supported by GIS technology and based on DEM and thematic data,the eight variables including altitude,slope,sin and cosin of aspect,curvity of land surface,and distance to residential area,cultivated land and road were extracted served as the sample of spatial succession of subalpine coniferous forests to fit Logistic Regression,and then the contribution of each independent variable as well as the spatial property of the occurrence probability of succession was calculated.The results suggested that,during the succession of subalpine coniferous forests to meadow,the closer to the residential area and cultivated land,the greater the contribution to succession is.In particular,when the distance to the residential area decreases by one unit,the probability for its conversion to meadow will be increased by 1.15 times.During the succession of subalpine coniferous forests to deciduous-broadleaved shrubs,the sin of aspect and distance to residential area contribute more,and the probability of succession increases with increasing degree of northwardness,i.e.when the degree of northwardness increases by one unit,the probability will be increased by 1.2 times.The quantitative analysis of spatial succession property of subalpine coniferous forests will supply scientific basis to the protection and restoration of subalpine coniferous forests.
Alpine wetlands are very sensitive to global change, have great impacts on the hydrological condition of rivers, and are closely related to peoples＇ living in lower reaches. It is essential to monitor alpine wetland changes to appropriately manage and protect wetland resources; however, it is quite difficult to accurately extract such information from remote sensing images due to spectral confusion and arduous field verification. In this study, we identified different wetland types in the Damqu River Basin located in the Yangze River source region from Landsat remote sensing data using the object-based method. In order to ensure the interpretation accuracy of wetland, a digital elevation model （DEM） and its derived data （slope, aspect）, Normalized Difference Vegetation Index （NDVI）, Normalized Difference Water Index （NDWI）, and Kauth-Thomas transformation were considered as the components of the spectral characteristics of wetland types. The spectral characteristics, texture features and spatial structure characteristics of each wetland type were comprehensively analyzed based on the success of image segmentation. The extraction rules for each wetland type were established by determining the thresholds of the spatial, texture and spectral attributes of typical parameter layers according to their histogram statistics. The classification accuracy was assessed using error matrixes and field survey verification data. According to the accuracy assessment, the total accuracy of image classification was 89%.
