Estimation and Change Analysis of Grassland AGB in the China-Mongolia-Russia Border Area Based on Multi-Source Geospatial Data
文献类型：期刊论文
| 作者 | Ma, Jiani1; Zhang, Chao2; Ou, Cong3; Qiu, Chi2; Yang, Cuicui2; Wang, Beibei2; Mandakh, Urtnasan4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2025-07-20 |
| 卷号 | 17期号:14页码:2527 |
| 关键词 | AGB SHAP RF_PSO change analysis China-Mongolia-Russia border area |
| DOI | 10.3390/rs17142527 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Aboveground biomass (AGB) is a critical indicator for assessing carbon sequestration and ecosystem health in transboundary ecologically fragile areas. High-precision estimation and spatiotemporal inversion of AGB are the key to investigating transition zones. However, inadequate feature selection and complex parameter tuning limit accuracy and spatiotemporal representation in the estimation model. An AGB estimation model that integrates SHAP-based feature selection with a particle swarm optimization-enhanced random forest model (RF_PSO) was proposed. Then AGB trajectory clustering was used to characterize the grassland change pattern. The method was applied to grasslands across the China-Mongolia-Russia (CMR) border area from 2000 to 2020. The results show that (1) the SHAP-RF_PSO model achieved the highest accuracy (R2 = 0.87, RMSE = 45.8 g/m2), outperforming other estimation models. (2) AGB improvements were observed in 72.13% of the area, mainly in MN_EA, MN_CE, and CN_NMG, while 27.39% showed degradation, concentrated in CN_NMG and MN_CE. The stable area accounts for 0.48%, which is scattered in RU_BU and RU_ZA.CN_NMG. (3) Four change patterns, namely Fluctuating Low, Stable Low, Fluctuating High, and Stable High, were identified, with major shifts in 2007, 2012, and 2014. (4) Projections indicate that 80% of the region may maintain current trends, 13% may reverse, and 7% remain uncertain, requiring targeted interventions. This study offers a robust tool for high-precision AGB estimation and supports dynamic monitoring in the CMR border area. |
| URL标识 | 查看原文 |
| WOS关键词 | ABOVEGROUND BIOMASS ; GROUND BIOMASS ; CLASSIFICATION ; DEGRADATION ; PREDICTION ; FORESTS |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001535692800001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/215314]  |
| 专题 | 区域可持续发展分析与模拟院重点实验室_外文论文 |
| 通讯作者 | Zhang, Chao |
| 作者单位 | 1.Shanxi Normal Univ, Coll Geog Sci, Taiyuan 030031, Peoples R China; 2.China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China; 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 4.Mongolian Acad Sci, Inst Geog & Geoecol, Div GIS & Remote Sensing, Ulaanbaatar 15170, Mongolia |
| 推荐引用方式 GB/T 7714 | Ma, Jiani,Zhang, Chao,Ou, Cong,et al. Estimation and Change Analysis of Grassland AGB in the China-Mongolia-Russia Border Area Based on Multi-Source Geospatial Data[J]. REMOTE SENSING,2025,17(14):2527. |
| APA | Ma, Jiani.,Zhang, Chao.,Ou, Cong.,Qiu, Chi.,Yang, Cuicui.,...&Mandakh, Urtnasan.(2025).Estimation and Change Analysis of Grassland AGB in the China-Mongolia-Russia Border Area Based on Multi-Source Geospatial Data.REMOTE SENSING,17(14),2527. |
| MLA | Ma, Jiani,et al."Estimation and Change Analysis of Grassland AGB in the China-Mongolia-Russia Border Area Based on Multi-Source Geospatial Data".REMOTE SENSING 17.14(2025):2527. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。