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An SW-TES hybrid algorithm for retrieving mountainous land surface temperature from high-resolution thermal infrared remote sensing data

文献类型：期刊论文

作者He, Zhi-Wei2,4,5; Tang, Bo-Hui2,4,5; Li, Zhao-Liang1,3
刊名ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
出版日期2026-02-01
卷号232页码:865-889
关键词Mountainous land surface temperature Topographic and adjacent effects Split-window algorithm Temperature and emissivity separation algorithm ASTER satellite data
ISSN号0924-2716
DOI10.1016/j.isprsjprs.2026.01.016
产权排序4
文献子类Article
英文摘要Mountainous land surface temperature (MLST) is a key parameter for studying the energy exchange between land surface and atmosphere in mountainous areas. However, traditional land surface temperature (LST) retrieval methods often neglect the influence of three-dimensional (3D) structures and adjacent pixels due to rugged terrain. To address this, a mountainous split-window and temperature-emissivity separation (MSW-TES) hybrid algorithm was proposed to retrieve MLST. The hybrid algorithm that combines the improved split window (SW) algorithm and temperature-emissivity separation (TES) algorithm, which considering the topographic and adjacent effects (T-A effect) to retrieve MLST from five thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). In this hybrid algorithm, an improved mountainous canopy multiple scattering TIR radiative transfer model was proposed to construct the simulation dataset. Then, an improved SW algorithm was developed to build a 3D lookup table (LUT) of regression coefficients using smallscale self-heating parameter (SSP) and sky-view factor (SVF) to estimate brightness temperature (BT) at ground level. Furthermore, The TES algorithm was refined to account for the influence of rugged terrain within pixel on mountainous land surface effective emissivity (MLSE) by reconstructing the relationship between minimum emissivity and maximum-minimum difference (MMD) for different SSPs. Results from simulated data show that the accuracy of the improved SW algorithm is increased by up to 0.5 K at most for estimating BT at ground level. The MSW-TES algorithm, considering the T-A effect, generally retrieves lower LST values compared to those without this consideration. The hybrid algorithm yielded root mean square error (RMSE) of 0.99 K and 1.83 K for LST retrieval with and without the T-A effect, respectively, with most differences falling between 0.0 K and 3.0 K. The sensitivity analysis indicated that the perturbation of input parameters has little influence on MLST and MLSE, which proves that the MSW-TES algorithm has strong robustness. Additionally, the accuracy of MLST retrieval by the MSW-TES algorithm was validated using both discrete anisotropic radiative transfer (DART) model simulations and in-situ measurements. The validation result of DART simulations showed biases ranging from -0.13 K to 1.03 K and RMSEs from 0.76 K to 1.29 K across the five ASTER TIR bands, while validation result of the in-situ measurements yielded a bias of 0.97 K and an RMSE of 1.25 K, demonstrating consistent and reliable results. This study underscores the necessity of accounting for the T-A effect to improve MLST retrieval and provides a promising pathway for global clear-sky high-resolution MLST mapping in upcoming thermal missions. The source code and simulated data are available at https://github.com/hezwppp/MSW-TES.
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WOS关键词SKY-VIEW FACTOR ; TIBETAN PLATEAU ; CLIMATE-CHANGE ; EMISSIVITY ; VALIDATION ; RADIATION ; MODIS ; ROUGHNESS ; PRODUCT ; PHYSICS
WOS研究方向Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001672182700001
出版者ELSEVIER
源URL[http://ir.igsnrr.ac.cn/handle/311030/220913]  
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, Bo-Hui
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.Yunnan Key Lab Quantitat Remote Sensing, Kunming 650093, Peoples R China;
3.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Key Lab Agr Remote Sensing, Minist Agr & Rural Affairs, Beijing 100081, Peoples R China
4.Yunnan Int Joint Lab Integrated Sky Ground Intelli, Kunming 650093, Peoples R China;
5.Kunming Univ Sci & Technol, Fac Land Resources Engn, Kunming 650093, Peoples R China;
推荐引用方式
GB/T 7714		 He, Zhi-Wei,Tang, Bo-Hui,Li, Zhao-Liang. An SW-TES hybrid algorithm for retrieving mountainous land surface temperature from high-resolution thermal infrared remote sensing data[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2026,232:865-889.
APA He, Zhi-Wei,Tang, Bo-Hui,&Li, Zhao-Liang.(2026).An SW-TES hybrid algorithm for retrieving mountainous land surface temperature from high-resolution thermal infrared remote sensing data.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,232,865-889.
MLA He, Zhi-Wei,et al."An SW-TES hybrid algorithm for retrieving mountainous land surface temperature from high-resolution thermal infrared remote sensing data".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 232(2026):865-889.

入库方式： OAI收割

来源：地理科学与资源研究所

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