Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method
文献类型：期刊论文
| 作者 | Li, Xiaoting1; Hu, Tengyun2; Gong, Peng1,3,4; Du, Shihong5,6; Chen, Bin7; Li, Xuecao8; Dai, Qi9,10 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2021-02-01 |
| 卷号 | 13期号:3页码:22 |
| 关键词 | area of interest urban land use sample collection building scale random forest |
| DOI | 10.3390/rs13030477 |
| 通讯作者 | Gong, Peng(penggong@tsinghua.edu.cn) |
| 英文摘要 | Urban land use mapping is critical to understanding human activities in space. The first national mapping result of essential urban land use categories of China (EULUC-China) was released in 2019. However, the overall accuracies in some of the plain cities such as Beijing, Chengdu, and Zhengzhou were lower than 50% because many parcel-based mapping units are large with mixed land uses. To address this shortcoming, we proposed an area of interest (AOI)-based mapping approach, choosing Beijing as our study area. The mapping process includes two major steps. First, grids with different sizes (i.e., 300 m, 200 m, and 100 m) were derived from original land parcels to obtain classification units with a suitable size. Then, features within these grids were extracted from Sentinel-2 spectral data, point of interest (POI), and Tencent Easygo crowdedness data. These features were classified using a random forest (RF) classifier with AOI data, resulting in a 10-category map of EULUC. Second, we superimposed the AOIs layer on classified units to do some rectification and offer more details at the building scale. The overall accuracy of the AOI layer reached 98%, and the overall accuracy of the mapping results reached 77%. This study provides a fast method for accurate geographic sample collection, which substantially reduces the amount of fieldwork for sample collection and improves the classification accuracy compared to previous EULUC mapping. The detailed urban land use map could offer more support for urban planning and environmental policymaking. |
| 资助项目 | National Key Research and Development Program of China[2016YFA0600103] ; Delos Living LLC ; Cyrus Tang Foundation |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000615476800001 |
| 资助机构 | National Key Research and Development Program of China ; Delos Living LLC ; Cyrus Tang Foundation |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/160599]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Gong, Peng |
| 作者单位 | 1.Tsinghua Univ, Dept Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China 2.Beijing Municipal Inst City Planning & Design, Beijing 100045, Peoples R China 3.Tsinghua Univ, Tsinghua Urban Inst, Beijing 100084, Peoples R China 4.Tsinghua Univ, Inst China Sustainable Urbanizat, Ctr Hlth Cities, Beijing 100084, Peoples R China 5.Peking Univ, Inst Remote Sensing, Beijing 100871, Peoples R China 6.Peking Univ, GIS, Beijing 100871, Peoples R China 7.Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA 8.China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China 9.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China 10.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Xiaoting,Hu, Tengyun,Gong, Peng,et al. Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method[J]. REMOTE SENSING,2021,13(3):22. |
| APA | Li, Xiaoting.,Hu, Tengyun.,Gong, Peng.,Du, Shihong.,Chen, Bin.,...&Dai, Qi.(2021).Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method.REMOTE SENSING,13(3),22. |
| MLA | Li, Xiaoting,et al."Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method".REMOTE SENSING 13.3(2021):22. |
入库方式： OAI收割
来源：地理科学与资源研究所
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