Analysis on Land-Use Change and Its Driving Mechanism in Xilingol, China, during 2000-2020 Using the Google Earth Engine
文献类型：期刊论文
| 作者 | Ye, Junzhi1,2; Hu, Yunfeng1,3; Zhen, Lin1,3; Wang, Hao1,3; Zhang, Yuxin4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2021-12-01 |
| 卷号 | 13期号:24页码:23 |
| 关键词 | spatial pattern dynamic change driving factor time-series stability random forest statistical modeling |
| DOI | 10.3390/rs13245134 |
| 通讯作者 | Hu, Yunfeng(huyf@lreis.ac.cn) |
| 英文摘要 | Large-scale, long time-series, and high-precision land-use mapping is the basis for assessing the evolution and sustainability of ecosystems in Xilingol, the Inner Mongolia Autonomous Region, China. Based on Google Earth Engine (GEE) and Landsat satellite remote-sensing images, the random forest (RF) classification algorithm was applied to create a yearly land-use/land-cover change (LULC) dataset in Xilingol during the past 20 years (2000-2020) and to examine the spatiotemporal characteristics, dynamic changes, and driving mechanisms of LULC using principal component analysis and multiple linear stepwise regression methods. The main findings are summarized as follows. (1) The RF classification algorithm supported by the GEE platform enables fast and accurate acquisition of the LULC dataset, and the overall accuracy is 0.88 +/- 0.01. (2) The ecological condition across Xilingol has improved significantly in the last 20 years (2000-2020), and the area of vegetation (grassland and woodland) has increased. Specifically, the area of high-coverage grass and woodland increases (+13.26%, +1.19%), while the area of water and moderate- and low-coverage grass decreases (-15.96%, -7.23%, and -3.27%). Cropland increases first and then decreases (-34.85%) and is mainly distributed in the southeast. The area of deserted land decreases in the south and increases in the center and north, but the total area still decreases (-13.74%). The built-up land expands rapidly (+108.45%). (3) In addition, our results suggest that regional socioeconomic development factors are the primary causes of changes in built-up land, and climate-related factors are the primary causes of water changes, but the correlations between other land-use types and relevant factors are not significant (cropland and grassland). We conclude that the GEE+RF method is capable of automated, long time-series, and high-accuracy land-use mapping, and further changes in climatic, environmental, and socioeconomic development factors, i.e., climate warming and rotational grazing, might have significant implications on regional land surface morphology and landscape dynamics. |
| WOS关键词 | RANDOM FOREST ; COVER CLASSIFICATION ; GLOBAL CHANGE ; VEGETATION ; PATTERNS ; DYNAMICS ; CROPLAND ; CLIMATE ; FORCES ; INDEX |
| 资助项目 | National Natural Science Foundation of China[41977421] ; National Natural Science Foundation of China[42130505] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19040301] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA20010202] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23100200] |
| 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:000737285700001 |
| 资助机构 | National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/169045]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Hu, Yunfeng |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 2.Northwest A&F Univ, Coll Nat Resources & Environm, Yangling 712100, Shaanxi, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 4.Chinese Acad Forestry, Inst Desertificat Studies, Beijing 100091, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ye, Junzhi,Hu, Yunfeng,Zhen, Lin,et al. Analysis on Land-Use Change and Its Driving Mechanism in Xilingol, China, during 2000-2020 Using the Google Earth Engine[J]. REMOTE SENSING,2021,13(24):23. |
| APA | Ye, Junzhi,Hu, Yunfeng,Zhen, Lin,Wang, Hao,&Zhang, Yuxin.(2021).Analysis on Land-Use Change and Its Driving Mechanism in Xilingol, China, during 2000-2020 Using the Google Earth Engine.REMOTE SENSING,13(24),23. |
| MLA | Ye, Junzhi,et al."Analysis on Land-Use Change and Its Driving Mechanism in Xilingol, China, during 2000-2020 Using the Google Earth Engine".REMOTE SENSING 13.24(2021):23. |
入库方式： OAI收割
来源：地理科学与资源研究所
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