Resources and environmental carrying capacity using RS and GIS

• Autorzy: Wang S.-X. , Shang M. , Zhou Y. , Liu W.-L. , Wang F. , Wang L.-T.
• Języki publikacji: EN

Abstrakty

EN

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

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2017
• Tom: 26
• Numer: 6
• Opis fizyczny: p.2793-2800,fig.,ref.

Twórcy

autor

Wang S.-X.

• Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

autor

Shang M.

• Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
• University of Chinese Academy of Sciences, Beijing 100049, China

autor

Zhou Y.

• Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

autor

Liu W.-L.

• Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

autor

Wang F.

• Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

autor

Wang L.-T.

• Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

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Identyfikatory

DOI

10.15244/pjoes/70927