Spatial-Temporal Pattern Analysis of Grassland Yield in Mongolian Plateau Based on Artificial Neural Network
文献类型：期刊论文
| 作者 | Li, Menghan2,3; Wang, Juanle3,4; Li, Kai2,3; Ochir, Altansukh5,6; Togtokh, Chuluun1; Xu, Chen7 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-08-01 |
| 卷号 | 15期号:16页码:19 |
| 关键词 | artificial neural network machine learning grass yield grassland degradation Mongolian Plateau |
| DOI | 10.3390/rs15163968 |
| 通讯作者 | Wang, Juanle(wangjl@igsnrr.ac.cn) |
| 英文摘要 | Accurate and timely estimation of grass yield is crucial for understanding the ecological conditions of grasslands in the Mongolian Plateau (MP). In this study, a new artificial neural network (ANN) model was selected for grassland yield inversion after comparison with multiple linear regression, K-nearest neighbor, and random forest models. The ANN performed better than the other machine learning models. Simultaneously, we conducted an analysis to examine the spatial and temporal characteristics and trends of grass yield in the MP from 2000 to 2020. Grassland productivity decreased from north to south. Additionally, 92.64% of the grasslands exhibited an increasing trend, whereas 7.35% exhibited a decreasing trend. Grassland degradation areas were primarily located in Inner Mongolia and the central Gobi region of Mongolia. Grassland productivity was positively correlated with land surface temperature and precipitation, although the latter was less sensitive than the former in certain areas. These findings indicate that ANN model-based grass yield estimation is an effective method for grassland productivity evaluation in the MP and can be used in a larger area, such as the Eurasian Steppe. |
| WOS关键词 | NET PRIMARY PRODUCTIVITY ; ABOVEGROUND BIOMASS ; TERRESTRIAL ECOSYSTEMS ; INNER-MONGOLIA ; CASA MODEL ; FOREST ; REGRESSION ; CLIMATE ; DRIVEN |
| 资助项目 | The authors are grateful for the support provided by the National University of Mongolia. ; National University of Mongolia |
| 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:001056570100001 |
| 资助机构 | The authors are grateful for the support provided by the National University of Mongolia. ; National University of Mongolia |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/196522]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Juanle |
| 作者单位 | 1.Natl Univ Mongolia, Inst Sustainable Dev, Ulaanbaatar 14201, Mongolia 2.China Univ Min & Technol Beijing, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China 3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 5.Natl Univ Mongolia, Sch Engn & Appl Sci, Dept Environm & Forest Engn, Environm Engn Lab, Ulaanbaatar 14201, Mongolia 6.Natl Univ Mongolia, Inst Sustainable Dev, Ulaanbaatar 14201, Mongolia 7.Jiangsu Ocean Univ, Coll Marine Resources & Environm, Lianyungang 222005, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Menghan,Wang, Juanle,Li, Kai,et al. Spatial-Temporal Pattern Analysis of Grassland Yield in Mongolian Plateau Based on Artificial Neural Network[J]. REMOTE SENSING,2023,15(16):19. |
| APA | Li, Menghan,Wang, Juanle,Li, Kai,Ochir, Altansukh,Togtokh, Chuluun,&Xu, Chen.(2023).Spatial-Temporal Pattern Analysis of Grassland Yield in Mongolian Plateau Based on Artificial Neural Network.REMOTE SENSING,15(16),19. |
| MLA | Li, Menghan,et al."Spatial-Temporal Pattern Analysis of Grassland Yield in Mongolian Plateau Based on Artificial Neural Network".REMOTE SENSING 15.16(2023):19. |
入库方式： OAI收割
来源：地理科学与资源研究所
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