Comparison between Physical and Empirical Methods for Simulating Surface Brightness Temperature Time Series
文献类型：期刊论文
| 作者 | Bian, Zunjian4; Lu, Yifan4; Du, Yongming4; Zhao, Wei3 ; Cao, Biao4; Hu, Tian2; Li, Ruibo4; Li, Hua4; Xiao, Qing1,4; Liu, Qinhuo1,4
|
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-07-01 |
| 卷号 | 14期号:14页码:24 |
| 关键词 | land surface temperature radiative transfer random forest regression LSTM SCOPE |
| DOI | 10.3390/rs14143385 |
| 通讯作者 | Li, Hua(lihua@aircas.ac.cn) |
| 英文摘要 | Land surface temperature (LST) is a vital parameter in the surface energy budget and water cycle. One of the most important foundations for LST studies is a theory to understand how to model LST with various influencing factors, such as canopy structure, solar radiation, and atmospheric conditions. Both physical-based and empirical methods have been widely applied. However, few studies have compared these two categories of methods. In this paper, a physical-based method, soil canopy observation of photochemistry and energy fluxes (SCOPE), and two empirical methods, random forest (RF) and long short-term memory (LSTM), were selected as representatives for comparison. Based on a series of measurements from meteorological stations in the Heihe River Basin, these methods were evaluated in different dimensions, i.e., the difference within the same surface type, between different years, and between different climate types. The comparison results indicate a relatively stable performance of SCOPE with a root mean square error (RMSE) of approximately 2.0 K regardless of surface types and years but requires many inputs and a high computational cost. The empirical methods performed relatively well in dealing with cases either within the same surface type or changes in temporal scales individually, with an RMSE of approximately 1.50 K, yet became less compatible in regard to different climate types. Although the overall accuracy is not as stable as that of the physical method, it has the advantages of fast calculation speed and little consideration of the internal structure of the model. |
| WOS关键词 | RANDOM FOREST ; DIRECTIONAL ANISOTROPY ; SOIL-MOISTURE ; SCOPE MODEL ; REFLECTANCE ; FLUORESCENCE ; RESOLUTION ; PRODUCTS ; LANDSAT ; SCALES |
| 资助项目 | Chinese Natural Science Foundation[41901287] ; Chinese Natural Science Foundation[42130111] ; Chinese Natural Science Foundation[42071317] ; Chinese Natural Science Foundation[41930111] ; Chinese Natural Science Foundation[41871258] ; National Key R&D Program of China[2020YFA0714102] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000831555600001 |
| 资助机构 | Chinese Natural Science Foundation ; National Key R&D Program of China |
| 源URL | [http://ir.imde.ac.cn/handle/131551/56770]  |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 通讯作者 | Li, Hua |
| 作者单位 | 1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 2.Luxembourg Inst Sci & Technol, Dept ERIN, Remote Sensing & Nat Resources Modeling, L-2450 Luxembourg, Luxembourg 3.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China 4.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bian, Zunjian,Lu, Yifan,Du, Yongming,et al. Comparison between Physical and Empirical Methods for Simulating Surface Brightness Temperature Time Series[J]. REMOTE SENSING,2022,14(14):24. |
| APA | Bian, Zunjian.,Lu, Yifan.,Du, Yongming.,Zhao, Wei.,Cao, Biao.,...&Liu, Qinhuo.(2022).Comparison between Physical and Empirical Methods for Simulating Surface Brightness Temperature Time Series.REMOTE SENSING,14(14),24. |
| MLA | Bian, Zunjian,et al."Comparison between Physical and Empirical Methods for Simulating Surface Brightness Temperature Time Series".REMOTE SENSING 14.14(2022):24. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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。