A Study on Simulating Directional Land Surface Emissivity Based on Kernel-Driven Models and Its Application to the Generalized Split-Window Algorithm
文献类型：期刊论文
| 作者 | Wu, Dan9,10,11; Sun, Hao9,10; Chen, Yunhao1,5; Wang, Dandan4; He, Zhi-Wei2,3; Tang, Bo-Hui2,3,8; Xu, Zhenheng9,10; Gao, Jinhua9,10; Wang, Yunjia9,10; Zhang, Tian7,9,10 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2025 |
| 卷号 | 63页码:5010724 |
| 关键词 | Angular effects directional emissivity generalized split-window (GSW) algorithm kernel-driven model (KDM) land surface temperature (LST) |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2025.3642323 |
| 产权排序 | 9 |
| 文献子类 | Article |
| 英文摘要 | In radiometric measurements, the emissivity of natural objects exhibits a dependence on the viewing angle. Ignoring the angular effect of surface emissivity can increase the uncertainty of land surface temperature (LST) retrievals. To mitigate this issue, we evaluated the simulation performance of 11 parametric kernel-driven models (KDMs) and developed directional emissivity models using MYD21 and MYD03 products. Afterward, the directional and classification-based emissivities were input into the refined generalized split-window (GSW) algorithm to retrieve LSTs with and without considering angular effects (LST_GSW_DE and LST_GSW_CE, respectively). Coupled with the MYD21 LST product (LST_TES), three LSTs were evaluated via SURFRAD in situ data and ERA5-Land products. The main findings were as follows. First, the RMSEs of directional emissivity simulated by different KDMs ranged from similar to 0.0003 to similar to 0.001, and their performance differences were generally slight, indicating that parameterized KDMs demonstrate reliable simulation performance in satellite-based directional emissivity modeling. Second, the directional emissivity simulation performances of different KDMs were ranked as follows: dual-kernel model (with both hotspot and base shape kernels) >= multikernel model > single-kernel model. The USEA and GUTA-sparse models exhibited advantages over the other KDMs when simulating impervious surfaces during the daytime. Third, we evaluated the three types of retrieved LSTs via SURFRAD in situ data. The rankings of the RMSE and MBE values were consistent: LST_TES was optimal, followed by LST_GSW_DE and LST_GSW_CE, with average RMSEs of 2.47, 2.62, and 2.80 K. Furthermore, we evaluated the three types of retrieved LSTs against the ERA5-Land data, and the rankings of the RMSE and MBE values were also consistent: LST_TES was comparable to (slightly better than) LST_GSW_DE in some seasons and consistently better than LST_GSW_CE. The average RMSEs were 2.45, 2.52, and 2.60 K. In addition, the RMSE and MBE values at different viewing zenith angles (VZAs) for the three LSTs increased with increasing VZA, especially when the VZA was greater than 40 degrees. The results demonstrated that it is feasible to use KDMs to simulate directional emissivity from satellite data, offering theoretical interpretability and addressing the issues of discrete and missing emissivity data. Future studies could be devoted to establishing new KDMs or kernels that conform to different land surface and solar illumination conditions to improve the LST retrieval accuracy. |
| URL标识 | 查看原文 |
| WOS关键词 | ALBEDO PRODUCT MCD43A ; BRIGHTNESS TEMPERATURE ; THERMAL ANISOTROPY ; GEOMETRIC MODEL ; CANOPY ; VALIDATION ; SEPARATION |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001643463900026 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219407]  |
| 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 | Sun, Hao |
| 作者单位 | 1.Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China; 2.Dept Educ Yunnan Prov, Key Lab Plateau Remote Sensing, Kunming 650093, Peoples R China; 3.Kunming Univ Sci & Technol, Fac Land Resource Engn, Kunming 650093, Peoples R China; 4.China Univ Geosci, Sch Land Sci & Technol, Beijing 100083, Peoples R China; 5.Beijing Key Lab Environm Remote Sensing & Digital, Beijing 100875, Peoples R China; 6.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100094, Peoples R China 7.China Aero Geophys Survey & Remote Sensing Ctr Nat, Beijing 100083, Peoples R China; 8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; 9.China Univ Min & Technol Beijing, Inner Mongolia Res Inst, Ordos 010300, Peoples R China; 10.China Univ Min & Technol Beijing, Coll Geosci & Surveying Engn, Beijing 100083, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wu, Dan,Sun, Hao,Chen, Yunhao,et al. A Study on Simulating Directional Land Surface Emissivity Based on Kernel-Driven Models and Its Application to the Generalized Split-Window Algorithm[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2025,63:5010724. |
| APA | Wu, Dan.,Sun, Hao.,Chen, Yunhao.,Wang, Dandan.,He, Zhi-Wei.,...&Xu, Huanyu.(2025).A Study on Simulating Directional Land Surface Emissivity Based on Kernel-Driven Models and Its Application to the Generalized Split-Window Algorithm.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,63,5010724. |
| MLA | Wu, Dan,et al."A Study on Simulating Directional Land Surface Emissivity Based on Kernel-Driven Models and Its Application to the Generalized Split-Window Algorithm".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 63(2025):5010724. |
入库方式： OAI收割
来源：地理科学与资源研究所
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