Resources and environmental carrying capacity using RS and GIS

14Citations
Citations of this article
41Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Wang, S. X., Shang, M., Zhou, Y., Liu, W. L., Wang, F., & Wang, L. T. (2017). Resources and environmental carrying capacity using RS and GIS. Polish Journal of Environmental Studies, 26(6), 2793–2800. https://doi.org/10.15244/pjoes/70927

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free