An accurate fringe extraction model of small- and medium-sized urban areas using multi-source data
文献类型：期刊论文
| 作者 | Li, Jianfeng; Peng, Biao; Liu, Siqi; Ye, Huping; Zhang, Zhuoying; Nie, Xiaowei |
| 刊名 | FRONTIERS IN ENVIRONMENTAL SCIENCE
 |
| 出版日期 | 2023-05-09 |
| 卷号 | 11页码:1118953 |
| 关键词 | landscape disorder degree kernel density estimation (KDE) night light intensity geographical detector (Geodetector) urban fringe |
| ISSN号 | 2296-665X |
| DOI | 10.3389/fenvs.2023.1118953 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Urban fringes are of great significance to urban development as connecting hubs between urban and rural areas. However, there are many problems in urban fringes, including disorderly spatial layout, waste of social resources, and low quality of human settlements. Rapid and accurate identification of urban fringes has important practical significance for optimizing urban spatial layout, controlling urban unlimited expansion, and protecting land resources. Given the lack of suitable and high-quality fringe extraction models for small- and medium-sized urban areas, this study was based on Gaofen-2 (GF-2) imagery, Suomi National Polar-orbiting Partnership Visible Infrared Imager Radiometer Suite (NPP-VIIRS) imagery, point of interest (POI) data, and WorldPop data, taking the landscape disorder degree, POI kernel density, and night light intensity as urban feature factors and constructing a fringe extraction model of small- and medium-sized urban areas (FEM-SMU). Taking Hantai District in China as the study area, the results of the model were compared to the landscape disorder degree threshold method and POI kernel density breakpoint analysis method, while the generality of the model was further tested in Shangzhou and Hanbin Districts. The results show that the FEM-SMU model has evident improvements over the conventional methods in terms of accuracy, detail, and integrity, and has higher versatility, which can better meet the research needs of small- and medium-sized urban fringes. |
| 学科主题 | Environmental Sciences & Ecology |
| WOS关键词 | KERNEL DENSITY-ESTIMATION ; REMOTE-SENSING IMAGERY ; LAND-USE ; IDENTIFICATION ; REGION ; CHINA ; CLASSIFICATION ; URBANIZATION ; SELECTION ; CITIES |
| WOS研究方向 | Environmental Sciences & Ecology |
| 出版者 | FRONTIERS MEDIA SA |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/193817]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Academy of Mathematics & System Sciences, CAS 2.Xi'an Jiaotong University 3.Chinese Academy of Sciences 4.Institute of Geographic Sciences & Natural Resources Research, CAS 5.Institute of Tibetan Plateau Research, CAS 6.Tibet University |
| 推荐引用方式 GB/T 7714 | Li, Jianfeng,Peng, Biao,Liu, Siqi,et al. An accurate fringe extraction model of small- and medium-sized urban areas using multi-source data[J]. FRONTIERS IN ENVIRONMENTAL SCIENCE,2023,11:1118953. |
| APA | Li, Jianfeng,Peng, Biao,Liu, Siqi,Ye, Huping,Zhang, Zhuoying,&Nie, Xiaowei.(2023).An accurate fringe extraction model of small- and medium-sized urban areas using multi-source data.FRONTIERS IN ENVIRONMENTAL SCIENCE,11,1118953. |
| MLA | Li, Jianfeng,et al."An accurate fringe extraction model of small- and medium-sized urban areas using multi-source data".FRONTIERS IN ENVIRONMENTAL SCIENCE 11(2023):1118953. |
入库方式： OAI收割
来源：地理科学与资源研究所
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