Combining Large Language Models with Satellite Embedding to Comprehensively Evaluate the Tibetan Plateau's Ecological Quality
文献类型：期刊论文
| 作者 | Yang, Yuejuan1; Wang, Junbang2; Wu, Pengcheng3,4; Liu, Yang1; Zhao, Xinquan5 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2026-02-19 |
| 卷号 | 18期号:4页码:643 |
| 关键词 | Tibetan Plateau satellite embedding large language models ecological indicators remote sensing geospatial artificial intelligence |
| DOI | 10.3390/rs18040643 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | As an important ecological obstacle prone to climatic changes, the Tibetan Plateau has been transformed by retreating glaciers, degrading permafrost, and deteriorating grasslands. Recent ecological remote sensing evaluations typically use medium-resolution and single-source optical imagery, highlight natural factors while ignoring human impacts, and encounter difficulties with time-focused interpretability and continuity within complex terrains. This research proposes a theory combining large language models with satellite embedding to holistically examine the ecology of the Tibetan Plateau between 2000 and 2024. We created an ecological satellite embedding (ESE) model applying self-supervised learning to integrate 12 ecological variables into combined space and time representations as of 2024, according to the Prithvi-Earth Observation (Prithvi-EO) foundational model involving low-rank adaptation (LoRA). GeoChat reasoning was applied to turn the embedded variables into a comprehensive representation feature (CRF). Field research demonstrated strong accuracy for the fraction of absorbed photosynthetically active radiation (FAPAR, R-2 = 0.9923) and aboveground biomass (AGB, R-2 = 0.8690). Space and temporal analyses demonstrated a general ecology-dependent enhancement accompanied by significant space-based clustering (Moran's I = 0.50-0.80), hotspots in humid southeastern areas, major upward trends in vegetation indices and productivity metrics (p < 0.05), and higher shifts in transition regions. Despite the marginal degradation risk, the grassland carrying capacity has expanded extensively in the main farming regions. The comprehensible CRF schema identified three management areas: potential risk, enhancement potential, and stable conservation management. This transferable modular approach connects expert reasoning with data-driven modeling, presenting adaptable methods for assessing ecosystems in high-altitude, data-sparse environments, and practical ways to promote ecological management. |
| URL标识 | 查看原文 |
| WOS关键词 | ABSOLUTE ERROR MAE ; REMOTE ; DATASET ; STATE ; CHINA ; RMSE |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001702354000001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221234]  |
| 专题 | 生态系统网络观测与模拟院重点实验室_外文论文 |
| 通讯作者 | Zhao, Xinquan |
| 作者单位 | 1.Weifang Univ, Sch Adv Agr Sci, Weifang 261061, Peoples R China; 2.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 3.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China; 4.China Univ Geosci, Sch Sci, Beijing 100083, Peoples R China; 5.Qinghai Univ, State Key Lab Plateau Ecol & Agr, Xining 810016, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Yuejuan,Wang, Junbang,Wu, Pengcheng,et al. Combining Large Language Models with Satellite Embedding to Comprehensively Evaluate the Tibetan Plateau's Ecological Quality[J]. REMOTE SENSING,2026,18(4):643. |
| APA | Yang, Yuejuan,Wang, Junbang,Wu, Pengcheng,Liu, Yang,&Zhao, Xinquan.(2026).Combining Large Language Models with Satellite Embedding to Comprehensively Evaluate the Tibetan Plateau's Ecological Quality.REMOTE SENSING,18(4),643. |
| MLA | Yang, Yuejuan,et al."Combining Large Language Models with Satellite Embedding to Comprehensively Evaluate the Tibetan Plateau's Ecological Quality".REMOTE SENSING 18.4(2026):643. |
入库方式： OAI收割
来源：地理科学与资源研究所
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