Resources and Environmental Carrying Capacity Using RS and GIS
Shi-Xin Wang1, Ming Shang1,2, Yi Zhou1, Wen-Liang Liu1, Feng Wang1, Li-Tao Wang1
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1Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2University of Chinese Academy of Sciences, Beijing 100049, China
Online publish date: 2017-10-10
Publish date: 2017-11-07
Submission date: 2017-03-15
Acceptance date: 2017-05-04
Pol. J. Environ. Stud. 2017;26(6):2793–2800
Evaluating resources and environmental carrying capacity (RECC) plays an important role in sustainable regional development. Using the urban agglomerations of Beijing, Tianjin, and Hebei Province as examples, in this paper we utilize remote sensing (RS) and geographic information system (GIS) techniques to study RECC. Based on data obtained from statistical information and RS technology, we selected 22 indicators with which to construct an RECC evaluation scheme. Then we conducted a mean-variance analysis to determine the weight of each indicator. Finally, we calculated the RECC of each city in the study area and statistically analyzed the main factors influencing RECC. Our results indicate that:
• The environment carries the most weight in RECC assessments, followed by resources, economic, and infrastructure
• In the study area, the RECC ranking is as follows: Beijing, Tianjin, Chengde, Langfang, Qinhuangdao, Cangzhou, Shijiazhuang, Tangshan, Baoding, Zhangjiakou, Hengshui, Handan, Xingtai
• Geographically, the eastern and central regions have higher RECC than the southern and northeast regions
• A region’s per capita fiscal income is the most important factor affecting its RECC