Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering
文献类型:期刊论文
作者 | Song, Keyu5,6; Cheng, Weiming2,3,4,5,6; Wang, Baixue6; Xu, Hua5,6; Wang, Ruibo1,6; Zhang, Yutong5,6 |
刊名 | REMOTE SENSING
![]() |
出版日期 | 2024-05-01 |
卷号 | 16期号:10页码:1701 |
关键词 | landscape type land-use change 1990-2020 change in gravity center correlation analysis development suitability |
DOI | 10.3390/rs16101701 |
产权排序 | 1 |
文献子类 | Article |
英文摘要 | The study of the expansion potential of artificial oases based on remote sensing data is of great significance for the rational allocation of water resources and urban planning in arid areas. Based on the spatio-temporal relationship between morphogenetic landform types and the development of artificial oases in Xinjiang, this study explored the development pattern of artificial oases in the past 30 years by using trend analysis and centroid migration analysis, constructing a series of landform-artificial oasis change indices, and investigating the suitability of different landforms for the development of artificial oases based on geomorphological location by adopting a hierarchical clustering method. The following conclusions are drawn: (1) From 1990 to 2020, the area of artificial oases in the whole territory continued to increase, with significant expansion to the south from 2005 to 2010. (2) Six categories of landform types for artificial oasis development were created based on the clustering results. Of these, 7.39% and 6.15% of the area's geomorphological types belonged to the first and second suitability classes, respectively. (3) The optimal scale for analyzing the suitability of landforms for the development of artificial oases over the past 30 years in the whole area was 8 km, which could explain more than 96% of the changes in the growth of artificial oases. The distribution of landforms of first- and second-class suitability within the 8 km buffer zone of an artificial oasis in the year 2020 was 10.55% and 9.90%, respectively, and landforms of first-class suitability were mainly concentrated in the near plain side of the urban agglomerations located on the northern and southern slopes of the Tianshan Mountains, and the urban agglomerations at the southern edge of Altai Mountains. This study quantified the potential of different geomorphological types for the development of artificial oases and provided a basis for site selection in future artificial oasis planning and urban construction. |
WOS关键词 | LAND-USE CHANGE ; CONTINENTAL RIVER-BASIN ; NORTHERN SLOPE ; SUITABLE OASIS ; ARID REGION ; DESERTIFICATION ; CHINA ; AREA ; EVOLUTION ; PATTERNS |
WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
WOS记录号 | WOS:001231325800001 |
出版者 | MDPI |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/205390] ![]() |
专题 | 资源与环境信息系统国家重点实验室_外文论文 |
通讯作者 | Cheng, Weiming |
作者单位 | 1.Xinjiang Univ, Coll Geog & Remote Sensing Sci, Urumqi 830046, Peoples R China 2.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, Urumqi 830011, Peoples R China 3.Collaborat Innovat Ctr South China Sea Studies, Nanjing 210093, Peoples R China 4.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 6.Inst Geog Sci & Nat Resources Res, Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Song, Keyu,Cheng, Weiming,Wang, Baixue,et al. Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering[J]. REMOTE SENSING,2024,16(10):1701. |
APA | Song, Keyu,Cheng, Weiming,Wang, Baixue,Xu, Hua,Wang, Ruibo,&Zhang, Yutong.(2024).Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering.REMOTE SENSING,16(10),1701. |
MLA | Song, Keyu,et al."Study on the Expansion Potential of Artificial Oases in Xinjiang by Coupling Geomorphic Features and Hierarchical Clustering".REMOTE SENSING 16.10(2024):1701. |
入库方式: OAI收割
来源:地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。