Integrating multisource RS data and GIS techniques to assist the evaluation of resource-environment carrying capacity in
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Integrating multisource RS data and GIS techniques to assist the evaluation of resource-environment carrying capacity in karst mountainous area
PU Jun-wei1,2
http://orcid.org/0000-0001-9441-5976; e-mail: [email protected]
ZHAO Xiao-qing1* MIAO Pei-pei1
http://orcid.org/0000-0002-8721-1489;
e-mail: [email protected]
http://orcid.org/0000-0003-4076-7604; e-mail: [email protected]
LI Si-nan1
http://orcid.org/0000-0001-8758-1423; e-mail: [email protected]
TAN Kun1
http://orcid.org/0000-0001-8343-8734; e-mail: [email protected]
WANG Qian1 TANG Wei1
http://orcid.org/0000-0002-9057-3851; e-mail: [email protected] http://orcid.org/0000-0002-0946-5475; e-mail: [email protected]
*Corresponding author 1 School of Earth Sciences, Yunnan University, Kunming 650500, Yunnan, China 2 Institute of International Rivers & Eco-security, Yunnan University, Kunming 650500, Yunnan, China Citation: Pu JW, Zhao XQ, Miao PP et al. (2020) Integrating multisource RS data and GIS techniques to assist the evaluation of resource-environment carrying capacity in karst mountainous area. Journal of Mountain Science 17(10). https://doi.org/10.1007/s11629-020-6097-0
© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract: The karst mountainous area is an ecologically fragile region with prominent humanland contradictions. The resource-environment carrying capacity (RECC) of this region needs to be further clarified. The development of remote sensing (RS) and geographic information system (GIS) provides data sources and processing platform for RECC monitoring. This study analyzed and established the evaluation index system of RECC by considering particularity in the karst mountainous area of Southwest China; processed multisource RS data (Sentinel-2, Aster-DEM and Landsat-8) to extract the spatial distributions of nine key indexes by GIS techniques (information classification, overlay analysis and raster calculation); proposed the Received: 25-Mar-2020 Revised: 07-Jul-2020 Accepted: 18-Aug-2020
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methods of index integration and fuzzy comprehensive evaluation of the RECC by GIS; and took a typical area, Guangnan County in Yunnan Province of China, as an experimental area to explore the effectiveness of the indexes and methods. The results showed that: (1) The important indexes affecting the RECC of karst mountainous area are water resources, tourism resources, position resources, geographical environment and soil erosion environment. (2) Data on cultivated land, construction land, minerals, transportation, water conservancy, ecosystem services, topography, soil erosion and rocky desertification can be obtained from RS data. GIS techniques integrate the information into the RECC results. The data extraction and processing methods are feasible on evaluating RECC. (3) The RECC of Guangnan County was in the mid-carrying level in 2018. The mid-
J. Mt. Sci. (2020) 17(10): 2528-2547
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