Retrieval of global surface soil and vegetation temperatures based on multisource data fusion
文献类型：期刊论文
| 作者 | Liu, Xiangyang2; Li, Zhao-Liang1,2; Duan, Si-Bo2; Leng, Pei2; Si, Menglin1,2 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2025-03-01 |
| 卷号 | 318页码:18 |
| 关键词 | Soil temperature Vegetation temperature Multisource data fusion MODIS ERA5-land |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2024.114564 |
| 产权排序 | 2 |
| 英文摘要 | Soil and vegetation temperatures are crucial for various fields, including ecology, agriculture, and climate change. However, there remains a lack of entirely observation-based global datasets for these two component temperatures. To fill this gap, this study developed a multisource data Fusion-based global surface Soil and Vegetation Temperature retrieval method (FuSVeT). This novel method not only utilizes temporal and spatial information from MODIS data by adopting a temperature cycle model to capture temporal variation and using adjacent pixels to consider spatial differences and increase the number of equations solved, but also leverages ERA5-Land data to reduce unknown parameters, effectively compensating for the limitations of satellite observations. Its performances were comprehensively evaluated with simulated data, high-resolution satellite products, and in situ measurements, demonstrating competitive accuracy with root mean square errors below 2 K and Biases of under 1 K in most cases. Compared to previous retrieval method that relies solely on satellite-based temporal and spatial information, FuSVeT present enhanced accuracy, more complete spatial coverage, and improved computational efficiency, making it more applicable for global soil and vegetation temperature mapping. Using this method, we generated global 0.05 degrees monthly mean soil and vegetation temperatures for January and July 2020. These data can capture more pronounced temperature heterogeneities within biomes than existing soil temperature products, indicating its superiority for global analyses. Importantly, FuSVeT can also be applied to satellite observations with higher spatiotemporal resolution, holding significant potential for providing accurate, long-term, global maps of surface soil and vegetation temperatures. |
| WOS关键词 | DIURNAL CYCLES ; LAND ; EMISSIVITY ; ALGORITHM ; MODELS |
| 资助项目 | National Natural Science Foundation of China[41921001] ; National Natural Science Foundation of China[42101371] ; Central Public-interest Scientific Institution Basal Research Fund[Y2024QC17] |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001387829300001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 资助机构 | National Natural Science Foundation of China ; Central Public-interest Scientific Institution Basal Research Fund |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/211988]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Li, Zhao-Liang |
| 作者单位 | 1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Xiangyang,Li, Zhao-Liang,Duan, Si-Bo,et al. Retrieval of global surface soil and vegetation temperatures based on multisource data fusion[J]. REMOTE SENSING OF ENVIRONMENT,2025,318:18. |
| APA | Liu, Xiangyang,Li, Zhao-Liang,Duan, Si-Bo,Leng, Pei,&Si, Menglin.(2025).Retrieval of global surface soil and vegetation temperatures based on multisource data fusion.REMOTE SENSING OF ENVIRONMENT,318,18. |
| MLA | Liu, Xiangyang,et al."Retrieval of global surface soil and vegetation temperatures based on multisource data fusion".REMOTE SENSING OF ENVIRONMENT 318(2025):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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