Understanding the Spatial Distribution of Urban Forests in China Using Sentinel-2 Images with Google Earth Engine
文献类型：期刊论文
| 作者 | Duan, Qianwen1,2; Tan, Minghong1,3; Guo, Yuxuan4; Wang, Xue1; Xin, Liangjie1 |
| 刊名 | FORESTS
 |
| 出版日期 | 2019-09-01 |
| 卷号 | 10期号:9页码:15 |
| 关键词 | urban greening urban area China Sentinel-2 Google Earth Engine |
| DOI | 10.3390/f10090729 |
| 通讯作者 | Tan, Minghong(tanmh@igsnrr.ac.cn) |
| 英文摘要 | Urban forests are vitally important for sustainable urban development and the well-being of urban residents. However, there is, as yet, no country-level urban forest spatial dataset of sufficient quality for the scientific management of, and correlative studies on, urban forests in China. At present, China attaches great importance to the construction of urban forests, and it is necessary to map a high-resolution and high-accuracy dataset of urban forests in China. The open-access Sentinel images and the Google Earth Engine platform provide a significant opportunity for the realization of this work. This study used eight bands (B2-B8, B11) and three indices of Sentinel-2 in 2016 to map the urban forests of China using the Random Forest machine learning algorithms at the pixel scale with the support of Google Earth Engine (GEE). The 7317 sample points for training and testing were collected from field visits and very high resolution images from Google Earth. The overall accuracy, producer's accuracy of urban forest, and user's accuracy of urban forest assessed by independent validation samples in this study were 92.30%, 92.27%, and 92.18%, respectively. In 2016, the percentage of urban forest cover was 19.2%. Nearly half of the cities had an urban forest cover between 10% and 20%, and the average percentage of large cities whose urban populations were over 5 million was 24.8%. Cities with less than half of the average were mainly distributed in northern and western parts of China, which should be focused on in urban greening planning. |
| WOS关键词 | LANDSAT IMAGES ; GREEN SPACE ; CITIES ; SURFACE ; INDEX ; BIODIVERSITY ; TEMPERATURES ; COMMUNITIES ; PM2.5 |
| 资助项目 | National Natural Science Foundation of China[41771116] |
| WOS研究方向 | Forestry |
| 语种 | 英语 |
| WOS记录号 | WOS:000487978700078 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/129818]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tan, Minghong |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resource & Environm, Beijing 100049, Peoples R China 3.Univ Chinese Acad Sci, Int Coll, Beijing 100049, Peoples R China 4.Dalian Jiaotong Univ, Dept Control Sci & Engn, Dalian 116028, Peoples R China |
| 推荐引用方式 GB/T 7714 | Duan, Qianwen,Tan, Minghong,Guo, Yuxuan,et al. Understanding the Spatial Distribution of Urban Forests in China Using Sentinel-2 Images with Google Earth Engine[J]. FORESTS,2019,10(9):15. |
| APA | Duan, Qianwen,Tan, Minghong,Guo, Yuxuan,Wang, Xue,&Xin, Liangjie.(2019).Understanding the Spatial Distribution of Urban Forests in China Using Sentinel-2 Images with Google Earth Engine.FORESTS,10(9),15. |
| MLA | Duan, Qianwen,et al."Understanding the Spatial Distribution of Urban Forests in China Using Sentinel-2 Images with Google Earth Engine".FORESTS 10.9(2019):15. |
入库方式： OAI收割
来源：地理科学与资源研究所
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