Author_Institution :
Resource & Environ. Inst., Northeastern Agric. Univ., Harbin, China
Abstract :
The health of land use system is the fundamental guarantee to realize the sustainable utilization of land resources. This article takes Bayan County, Heilongjiang province as the research area, and based on the Landsat TM / ETM + remote sensing image and statistical data in 2009. Constructing evaluation index of land use system health system from three aspects ,that the structural index, function index, efficiency index ,interpreting the image to extract relevant information by using remote sensing and GIS technology, using the comprehensive parameter evaluation method, calculate the land use system health index of Bayan county and modify the index by BP neural network evaluation method, to take clustering analysis on the status of land use system health in the research area. The results showed: In general, there is certain difference of the land use system health among the 18 townships and towns in Bayan County. The health of land use system in a state of health: Hongguang township, Xinglong town, Fengle township, Xiji town and rural Songhuajiang town; in the sub-health state: Wanfa town, Tianzeng town, Dexiang township, Heishan town, Wa xing town, Longmiao town, Huashan township, Zhendong town, Longquan town and Bayan town; in a state of unhealth:Shanhou township, Bayangang town and Fujiang township.
Keywords :
geographic information systems; geophysical image processing; land use planning; neural nets; terrain mapping; AD 2009; BP neural network evaluation method; Bayan County; Bayan town; Bayangang town; China; Fengle township; Fujiang township; GIS technology; Heilongjiang province; Hongguang township; Huashan township; Landsat ETM+ remote sensing image; Landsat TM remote sensing image; Longmiao town; Longquan town; Songhuajiang town; Songnen High Plains; Wanfa town; Xiji town; Xinglong town; Zhendong town; clustering analysis; health index; land resources; land use system health evaluation; parameter evaluation method; statistical data; subhealth state; Cities and towns; Ecosystems; Humans; Indexes; Neural networks; Remote sensing; Soil;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2012 2nd International Conference on
