A physical method for downscaling land surface temperatures using surface energy balance theory
文献类型：期刊论文
| 作者 | Hu, Yongxin2,3,4; Tang, Ronglin2,4; Jiang, Xiaoguang1,2; Li, Zhao-Liang2,3,4; Jiang, Yazhen2,4; Liu, Meng6; Gao, Caixia1; Zhou, Xiaoming5 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2023-03-01 |
| 卷号 | 286页码:20 |
| ISSN号 | 0034-4257 |
| 关键词 | Land surface temperature Thermal infrared remote sensing Surface energy balance Downscaling DTsEB |
| DOI | 10.1016/j.rse.2022.113421 |
| 通讯作者 | Tang, Ronglin(tangrl@lreis.ac.cn) ; Jiang, Xiaoguang(xgjiang@ucas.ac.cn) |
| 英文摘要 | Fine-resolution land surface temperature (LST) derived from thermal infrared remote sensing images is a good indicator of surface water status and plays an essential role in the exchange of energy and water between land and atmosphere. A physical surface energy balance (SEB)-based LST downscaling method (DTsEB) is developed to downscale coarse remotely sensed thermal infrared LST products with fine-resolution visible and near-infrared data. The DTsEB method is advantageous for its ability to mechanically interrelate surface variables contributing to the spatial variation of LST, to quantitatively weigh the contributions of each related variable within a physical framework, and to efficaciously avoid the subjective selection of scaling factors and the establishment of statistical regression relationships. The applicability of the DTsEB method was tested by downscaling 12 scenes of 990 m Moderate Resolution Imaging Spectroradiometer (MODIS) and aggregated Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST products to 90 m resolution at six overpass times between 2005 and 2015 over three 9.9 km by 9.9 km cropland (mixed by grass, tree, and built-up land) study areas. Three typical LST downscaling methods, namely the widely applied TsHARP, the later developed least median square regression downscaling (LMS) and the geographically weighted regression (GWR), were introduced for inter comparison. The results showed that the DTsEB method could more effectively reconstruct the subpixel spatial variations in LST within the coarse-resolution pixels and achieve a better downscaling accuracy than the TsHARP, LMS and GWR methods. The DTsEB method yielded, on average, root mean square errors (RMSEs) of 2.01 K and 1.42 K when applied to the MODIS datasets and aggregated ASTER datasets, respectively, which were lower than those obtained with the TsHARP method, with average RMSEs of 2.41 K and 1.71 K, the LMS method, with average RMSEs of 2.35 K and 1.63 K, and the GWR method, with average RMSEs of 2.38 K and 1.64 K, respectively. The contributions of the related surface variables to the subpixel spatial variation in the LST varied both spatially and temporally and were different from each other. In summary, the DTsEB method was demonstrated to outperform the TsHARP, LMS, and GWR methods and could be used as a good alternative for downscaling LST products from coarse to fine resolution with high robustness and accuracy. |
| WOS关键词 | SPATIAL-SCALE ; URBAN AREA ; MODIS ; EVAPOTRANSPIRATION ; DISAGGREGATION ; RESOLUTION ; EMISSIVITY ; MODULATION ; LANDSCAPE ; DISTRAD |
| 资助项目 | National Natural Science Foundation of China[41922009] ; National Natural Science Foundation of China[42071332] ; National Natural Science Foundation of China[41971319] ; National Natural Science Foundation of China[41921001] ; National Key R&D Program of China[2018YFA0605401] ; National Key R&D Program of China[2018YFB050480304] ; National Key R&D Program of China[2018YFB050480404] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA19040403] ; Bureau of International Co-operation Chinese Academy of Sciences[181811KYSB20160040] ; Dragon 4 ESA-MOST Cooperation programme[32426_1] |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | ELSEVIER SCIENCE INC |
| WOS记录号 | WOS:000913792900001 |
| 资助机构 | National Natural Science Foundation of China ; National Key R&D Program of China ; Strategic Priority Research Program of Chinese Academy of Sciences ; Bureau of International Co-operation Chinese Academy of Sciences ; Dragon 4 ESA-MOST Cooperation programme |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/189809]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tang, Ronglin; Jiang, Xiaoguang |
| 作者单位 | 1.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Quantitat Remote Sensing Informat Technol, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China 3.Univ Strasbourg, ICube Lab, UMR 7357, CNRS, 300 Bd Sebastien Brant,CS 10413, F-67412 Illkirch Graffenstaden, France 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 5.Lanzhou Univ Technol, Sch Civil Engn, Lanzhou, Gansu, Peoples R China 6.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Yongxin,Tang, Ronglin,Jiang, Xiaoguang,et al. A physical method for downscaling land surface temperatures using surface energy balance theory[J]. REMOTE SENSING OF ENVIRONMENT,2023,286:20. |
| APA | Hu, Yongxin.,Tang, Ronglin.,Jiang, Xiaoguang.,Li, Zhao-Liang.,Jiang, Yazhen.,...&Zhou, Xiaoming.(2023).A physical method for downscaling land surface temperatures using surface energy balance theory.REMOTE SENSING OF ENVIRONMENT,286,20. |
| MLA | Hu, Yongxin,et al."A physical method for downscaling land surface temperatures using surface energy balance theory".REMOTE SENSING OF ENVIRONMENT 286(2023):20. |
入库方式： OAI收割
来源：地理科学与资源研究所
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