Human Settlement Evaluation in Mountain Areas Based on Remote Sensing,GIS and Ecological Niche Modeling

作     者：ZHAO Jian XU Min LU Shi-lei CAO Chun-xiang 

作者机构：State Key Laboratory of Remote Sensing ScienceJointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Graduate School of Chinese Academy of Sciences 

出 版 物：《Journal of Mountain Science》 (山地科学学报（英文）)

年 卷 期：2013年第10卷第3期

页      面：378-387页

核心收录：

学科分类：083002[工学-环境工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 081603[工学-地图制图学与地理信息工程] 081802[工学-地球探测与信息技术] 07[理学] 08[工学] 070503[理学-地图学与地理信息系统] 0818[工学-地质资源与地质工程] 0705[理学-地理学] 0816[工学-测绘科学与技术] 0713[理学-生态学] 

基　　金：supported by the Natural Science Foundation of China (Grant No. 41171330) National High Technology Research and Development Program of China (863 Program)(Grant No. 2013AA12A302) the Special Foundation for Free Exploration of State Laboratory of Remote Sensing Science (Grant No.Y1Y00245KZ) 

主　　题：Human settlement Remote sensing Suitability assessment Ecological niche modeling 

摘      要：The Qinghai-Tibet Plateau is the word＇s highest and largest plateau. Due to increasing demands for environment exploration and tourism, a large transitional area is required for altitude adaptation. Hehuang valley, which locates in the transition zone between the Loess Plateau and the Qinghai-Tibet Plateau, has convenient transportation and relatively low elevation. Our question is whether the geographic conditions here are appropriate for adapted stay before going into the Qinghai-Tibet Plateau. Therefore, in this study, we examined the potential use of ecological niche modeling （ENM） for mapping current and potential distribution patterns of human settlements. We chose the Maximum Entropy Method （Maxent）, an ENM which integrates climate, remote sensing and geographical data, to model distributions and assess land suitability for transition areas. After preprocessing and selection, the correlation between variables and spatial auto- correlation input data were removed and 106 occurrence points and 9 environmental layers were determined as the model inputs. The threshold- independent model performance was reasonable according to lO times model running, with the area under the curve （AUC） values being 0.917± 0.01, and 0.923±0.002 for test data. Cohen＇s kappa coefficient of model performance was 0.848. Results showed that 82.22% of the study extent was not suitable for human settlement. Of the remaining areas, highly suitable areas aceounted for 1.19%, moderately for 5.3% and marginally for 11.28%. These suitable areas totaled 418.79 km2, and 86.25% of the sample data was identified in the different gradient of suitable *** decisive environmental factors were slope and two climate variables： mean diurnal temperature range and temperature seasonality. Our model showed a good performance in mapping and assessing human settlements. This study provides the first predicted potential habitat distribution map for human settlement in Ledu County, which could also help in