Author(s)

Chaokui Li^1,2,3, Jianhui Chen^1,2,3*, Mengguang Liao^1,2,3, Guo Chen^1,2,3, Qinlan Zhou^1,2,3

¹National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology, Hunan University of Science and Technology, Xiangtan, China.
²Hunan Province Engineering Laboratory of Geospatial Information, Hunan University of Science and Technology, Xiangtan, China.
³Institute of Geospatial Information Science, Hunan University of Science and Technology, Xiangtan, China.

In this paper, introducing new remote sensing and geographic information technology to solve the problem of data collection and analysis, this makes the study of ecological risk assessment very quick and accurate. Taking the Shan Xin mining area of the tin mine in Lengshuijiang of Hunan Province as the research object, using the remote sensing image data of three periods in 2005, 2010 and 2015, the remote sensing image is classified carefully and the landscape classification map of the mining area is obtained. The ecological risk index is introduced and the ecological risk values are sampled and interpolated on the ArcGIS platform. The ecological risk spatial distribution map based on the landscape pattern index was obtained. The ecological risk was divided into 5 levels by using the Jenks natural classification method, and each ecological risk grade area was counted. The research results show that: from year 2005 to year 2010, landscape ecological risk trend of the mining area is growing up; the trend rising area of landscape ecological risk is mainly in the southwest and northeast of the Shan Xin mining field; the area of higher and high ecological risk is increasing year by year; and the trend of dispersed development in space is obvious; the development trend of ecological risk in the mining area is rapidly increasing; in 2010 - 2015, the higher and high ecological risk area decrease slightly with the increasing of area of grassland and residential low vulnerability of landscape types; the ecological risk area showed a slow decreasing trend. The research results provide an objective reference for decision making of ecological environment governance.

RS & GIS Technology, Shan Xin Mining Field, Ecological Risk Assessment, Jenks Nature Classification, Risk Index

Li, C. , Chen, J. , Liao, M. , Chen, G. and Zhou, Q. (2018) Ecological Risk Assessment of Shan Xin Mining Area Based on Remote Sensing and Geography Information System Technology. Journal of Geographic Information System, 10, 234-246. doi: 10.4236/jgis.2018.102012.