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An Urban Thermal Radiation Analytical Model Based on Sky View Factor

文献类型：期刊论文

作者Zhang, Qi3,5; Qian, Yonggang5; Li, Kun5; Wang, Dandan2; Lan, Qiongqiong1; Wang, Cheng5; Ma, Chenyang7; Dou, Xianhui6; Ma, Xinran5; He, Zhaoning6
刊名IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
出版日期2024
卷号62页码:16
关键词3-D structure multiple scattering sky view factor (SVF) thermal radiation 3-D structure multiple scattering sky view factor (SVF) thermal radiation
ISSN号0196-2892
DOI10.1109/TGRS.2024.3468396
产权排序5
英文摘要Urban land surface temperature (LST) plays a crucial role in observing and comprehending energy exchange within urban environments. Urban geometric structure and material composition are critical parameters to characterize urban thermal radiation accurately. In this article, an urban thermal radiation analytical model based on the sky view factor (UTRAM-SVF) was developed by considering the multiple scattering within the urban canopy and the radiation composition of urban components. The cross-comparison of the proposed method was conducted in four ways: the discrete anisotropic radiation transfer (DART) model, urban effective emissivity model based on SVF (UEM-SVF), Landsat 8 Thermal Infrared Sensor (TIRS) data, and Airborne Hyperspectral Scanner (AHS) TIR data. Compared with DART, the results revealed that the root-mean-square error (RMSE) of radiance by the UTRAM-SVF model is 0.04 W/(m $<^>{2}\cdot $ sr $\cdot \mu $ m). Furthermore, two field applications were conducted using Landsat 8 TIRS data and AHS TIR data. The differences of at-sensor radiance from UTRAM-SVF model and Landsat 8 TIRS data vary from 0.05 to 0.3 W/(m $<^>{2}\cdot $ sr $\cdot \mu $ m), and the RMSE is 0.17 W/(m $<^>{2}\cdot $ sr $\cdot \mu $ m). The results of AHS TIR images on the UTRAM-SVF model present that the average biases of at-sensor radiance are 0.07 and 0.19 W/(m $<^>{2}\cdot $ sr $\cdot \mu $ m) for two TIR channels. The cross-comparison results show that the proposed method outperformed the UEM-SVF model in evaluating radiance over the complex and heterogenous urban areas (SVF <0.4). The UTRAM-SVF model can be used to monitor urban thermal radiation based on high-resolution TIR data and can further be helpful to retrieve high-resolution urban LST.
WOS关键词SURFACE TEMPERATURE RETRIEVAL ; LAND-SURFACE ; EFFECTIVE EMISSIVITY ; SCALE
资助项目Key Program of National Natural Science Foundation of China[42130108] ; National Natural Science Foundation of China[42371375]
WOS研究方向Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001338406700027
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构Key Program of National Natural Science Foundation of China ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/210715]  
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Qian, Yonggang; Li, Kun
作者单位1.China Ctr Resources Satellite Data & Applicat, Beijing 100094, Peoples R China
2.China Univ Geosci, Sch Land Sci & Technol, Beijing 100083, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Surveying & Mapping Stn, Xian 710000, Shanxi, Peoples R China
5.Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
6.Minist Nat Resources, Land Satellite Remote Sensing Applicat Ctr, Beijing 100094, Peoples R China
7.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Qi,Qian, Yonggang,Li, Kun,et al. An Urban Thermal Radiation Analytical Model Based on Sky View Factor[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2024,62:16.
APA Zhang, Qi.,Qian, Yonggang.,Li, Kun.,Wang, Dandan.,Lan, Qiongqiong.,...&Wu, You.(2024).An Urban Thermal Radiation Analytical Model Based on Sky View Factor.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,62,16.
MLA Zhang, Qi,et al."An Urban Thermal Radiation Analytical Model Based on Sky View Factor".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 62(2024):16.

入库方式： OAI收割

来源：地理科学与资源研究所

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