Integrating multisource RS data and GIS techniques to assist the evaluation of resource-environment carrying capacity in karst mountainous area
文献类型：期刊论文
| 作者 | Pu Jun-wei; Zhao Xiao-qing; Miao Pei-pei; Li Si-nan; Tan Kun; Wang Qian; Tang Wei |
| 刊名 | JOURNAL OF MOUNTAIN SCIENCE
 |
| 出版日期 | 2020 |
| 卷号 | 17期号:10页码:2528-2547 |
| 关键词 | Carrying capacity Multisource RS data GIS techniques Evaluation index system Data Integration Karst mountainous area Fuzzy comprehensive evaluation method |
| ISSN号 | 1672-6316 |
| DOI | 10.1007/s11629-020-6097-0 |
| 文献子类 | Article |
| 英文摘要 | The karst mountainous area is an ecologically fragile region with prominent human-land 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 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-carrying and low-carrying levels were the main types, accounting for more than 80.00% of the total study area. The areas with high carrying capacity were mainly distributed in the northern regions of the northwest-southeast line of the county, and other areas have a low carrying capacity comparatively. The coordination between regional resource-environment status and socioeconomic development is the key to improve RECC. This study explores the evaluation index system of RECC in karst mountainous area and the application of multisource RS data and GIS techniques in the comprehensive evaluation. The methods can be applied in related fields to provide suggestions for data/information extraction and integration, and sustainable development. |
| 电子版国际标准刊号 | 1993-0321 |
| 语种 | 英语 |
| WOS记录号 | WOS:000578876400015 |
| 源URL | [http://ir.imde.ac.cn/handle/131551/50624]  |
| 专题 | Journal of Mountain Science_Journal of Mountain Science-2020_Vol17 No.10 |
| 推荐引用方式 GB/T 7714 | Pu Jun-wei,Zhao Xiao-qing,Miao Pei-pei,et al. Integrating multisource RS data and GIS techniques to assist the evaluation of resource-environment carrying capacity in karst mountainous area[J]. JOURNAL OF MOUNTAIN SCIENCE,2020,17(10):2528-2547. |
| APA | Pu Jun-wei.,Zhao Xiao-qing.,Miao Pei-pei.,Li Si-nan.,Tan Kun.,...&Tang Wei.(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),2528-2547. |
| MLA | Pu Jun-wei,et al."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(2020):2528-2547. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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