Optimizing Latent Heat Flux Calculation via Composited Thermal Infrared Temperatures
文献类型：期刊论文
| 作者 | Jiang, Yazhen1,2; Zhao, Jianing1,2; Wu, Anqi3; Si, Menglin1,2; Bian, Zunjian4; Tang, Ronglin1,2; Li, Zhao-Liang1,2,5 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2025 |
| 卷号 | 63页码:4420311 |
| 关键词 | Land surface temperature Land surface Soil Surface resistance Biological system modeling Vegetation mapping Atmospheric modeling Temperature sensors Estimation Remote sensing Angular effect latent heat flux (LE) land surface temperature (LST) single-source energy balance models |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2025.3618869 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Latent heat flux (LE) is pivotal in the regional water-energy nexus, exemplifying complex interplays between atmosphere and land surface. Thermal infrared (TIR) land surface temperature (LST) offers direct and vital information for estimating LE through the single-source energy balance method. Nevertheless, variations in the viewing angles of remote sensing sensors can introduce angular effects in the retrieval of LST, potentially causing significant incompatibility issues in estimating LE. To alleviate this uncertainty, we adopt a viable approach by using two composited LSTs derived from the integration of soil and vegetation component temperatures from Sentinel-3 SLSTR, combined with fraction vegetation cover (FVC) obtained from both the GEOV2 FVC product and MODIS LAI-derived estimates. This composited LST was subsequently used as one of the inputs of a surface energy balance system (SEBS) model driven by measured meteorological and ERA5 reanalysis data in Heihe River Basin in China during 2016-2022, respectively. The results demonstrate that two types of composited LST reduced the root mean square error (RMSE) of estimated LE by 4.8 and 8.8 W/m(2), respectively, by using measured meteorological data, and using ERA5 meteorological data, the RMSE was reduced by 6.8 and 11.0 W/m(2), respectively. Regardless of the meteorological data and FVC used, the RMSE for all stations assessed in the study decreased. This indicates that by partially mitigating the angular effects of TIR LST, improvements in TIR-based surface LE estimation can be achieved over regional scales. |
| URL标识 | 查看原文 |
| WOS关键词 | MAPPING DAILY EVAPOTRANSPIRATION ; ENERGY BALANCE ALGORITHM ; SYSTEM SEBS ; SURFACE ; VALIDATION ; MODELS ; SOIL |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001611731400005 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219506]  |
| 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 | Tang, Ronglin |
| 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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 3.China Univ Geosci, Sch Geog & Informat Engn, Wuhan 430074, Peoples R China; 4.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100094, Peoples R China; 5.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 | Jiang, Yazhen,Zhao, Jianing,Wu, Anqi,et al. Optimizing Latent Heat Flux Calculation via Composited Thermal Infrared Temperatures[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2025,63:4420311. |
| APA | Jiang, Yazhen.,Zhao, Jianing.,Wu, Anqi.,Si, Menglin.,Bian, Zunjian.,...&Li, Zhao-Liang.(2025).Optimizing Latent Heat Flux Calculation via Composited Thermal Infrared Temperatures.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,63,4420311. |
| MLA | Jiang, Yazhen,et al."Optimizing Latent Heat Flux Calculation via Composited Thermal Infrared Temperatures".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 63(2025):4420311. |
入库方式： OAI收割
来源：地理科学与资源研究所
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