利用混合方法从高空间分辨率热红外图像估算城市地表发射的长波辐射

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES Remote Sensing of Environment Pub Date : 2024-10-01 DOI:10.1016/j.rse.2024.114442
Songyi Lin , Huazhong Ren , Rongyuan Liu , Jinxiang Li , Shanshan Chen , Yuanjian Teng , Wenjie Fan , Baozhen Wang , Yu Liu
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引用次数: 0

摘要

准确估算地表发射的长波辐射(SELR)对于了解其时空动态和地表热环境具有重要的科学价值。高空间分辨率的热红外(TIR)图像为研究复杂地表(如城市地表)的长波辐射提供了更有力的数据支持。本研究提出了一种新的面向城市的混合(UoHy)方法,利用天空视角因子考虑城市像素的多重散射和邻近效应,从高空间分辨率 TIR 图像的大气顶辐射度估算城市 SELR,并进行了灵敏度分析和应用。以 GF-5/VIMS 热图像为例,实验结果表明 UoHy 方法具有较高的精度,在低大气水汽条件下获得的 SELR 误差小于 12.0 W/m2,在高大气水汽条件下获得的 SELR 误差小于 17.0 W/m2。该方法在白天和夜间的应用也证明了其有效性和有效性。与面向自然地表的混合方法相比,UoHy 方法在 SELR 估算方面提高了约 7.0-10.0 W/m2,这表明该方法具有利用高空间分辨率 TIR 图像对城市地表 SELR 估算的实用潜力。
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Urban surface-emitted longwave radiation estimation from high spatial resolution thermal infrared images using a hybrid method
Accurate estimation of the surface-emitted longwave radiation (SELR) has important scientific value in understanding its spatiotemporal dynamics and surface thermal environment. Thermal infrared (TIR) images with high spatial resolution offer enhanced data support for studying SELR of complex surfaces, such as urban surface. This study proposes a new urban-oriented hybrid (UoHy) method, which considers multiple scattering and adjacent effects of urban pixel using the term sky view factor, to estimate urban SELR from the top-of-atmosphere radiance of TIR images with high spatial resolution, and performs sensitivity analysis and application. The experimental results for the thermal images of GF-5/VIMS as an example showed that the UoHy method has relatively high accuracy, and obtains SELR errors of less than 12.0 W/m2 under low atmospheric water vapor conditions and less than 17.0 W/m2 under high atmospheric water vapor conditions. The application of the method during daytime and nighttime also demonstrated the method's validity and effectiveness. Compared with the natural surface-oriented hybrid method, the UoHy method obtains an improvement of about 7.0–10.0 W/m2 in SELR estimation, which indicates that it has the potential for practical SELR estimation over urban surface with TIR images of high spatial resolution.
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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