Assessing Kernel-Driven Models' Efficacy in Urban Thermal Radiation Directionality Modeling Using DART-Simulated Scenarios.
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| Title: | Assessing Kernel-Driven Models' Efficacy in Urban Thermal Radiation Directionality Modeling Using DART-Simulated Scenarios. |
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| Authors: | Zhu, Xiaolin1 (AUTHOR), Li, Zhao-Liang1,2 (AUTHOR) lizl@unistra.fr, Nerry, Franҫoise1 (AUTHOR) |
| Source: | Remote Sensing. Aug2025, Vol. 17 Issue 16, p2884. 26p. |
| Subjects: | Land surface temperature, Brightness temperature, Urban heat islands, Urban morphology, Simulation methods & models, Radiative transfer |
| Abstract: | The intensification of the urban thermal environment has brought attention to urban land surface temperature (ULST). Complex building geometry and manmade material lead to significant thermal radiation directionality (TRD) of the urban canopy, and the TRD effect directly influences the accuracy of ULST retrieval algorithms. Therefore, it is essential to understand and eliminate the TRD effect to achieve high-accuracy ULST. In this context, the hemispherical brightness temperature maximum–minimum discrepancy (BTD) was quantitatively analyzed via different spectral bands, component temperature thresholds, urban geometries, and component temperature differences. Meanwhile, the DART simulations database was used to systematically evaluate 1 single-kernel- and 30 dual-kernel-driven models (KDMs), which were combined from 5 base-shape kernels (RossThick, Vinnikov, uea, RossThin, and LSF) and 6 hotspot kernels (RL, Roujean, Vinnikov, LiSparseR, LiDense, and Chen). Results show that the BTD discrepancy (ΔBTD) can reach up to 0.91 K with different band emissivities, whereas the ΔBTD is over 10 K with different component temperature differences. The building density and ratio between building heights and road widths (H/W) also exhibit their importance over urban regions. In addition, the RossThick–/Vinnikov–Roujean dual-kernel KDMs demonstrate better performance with an overall RMSE of 1.12 K. The RL-series KDMs can describe the hotspot distribution well, but the uea-series KDMs outperform at the solar principal plane (SPP) and cross-solar principal plane (CSPP). Specifically, the performance of all KDMs is sensitive to the H/W and component temperature thresholds, and urban geometry can affect the TRD RMSE with increasing H/W and a depletion of high building density. The quantitative TRD analysis and comparison provide a comprehensive reference for understanding the distribution of thermal radiation, which is also a reliable basis for developing the new TRD model over urban regions. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 187613870 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Assessing Kernel-Driven Models' Efficacy in Urban Thermal Radiation Directionality Modeling Using DART-Simulated Scenarios. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhu%2C+Xiaolin%22">Zhu, Xiaolin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Zhao-Liang%22">Li, Zhao-Liang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> lizl@unistra.fr</i><br /><searchLink fieldCode="AR" term="%22Nerry%2C+Franҫoise%22">Nerry, Franҫoise</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Aug2025, Vol. 17 Issue 16, p2884. 26p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Land+surface+temperature%22">Land surface temperature</searchLink><br /><searchLink fieldCode="DE" term="%22Brightness+temperature%22">Brightness temperature</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+heat+islands%22">Urban heat islands</searchLink><br /><searchLink fieldCode="DE" term="%22Urban+morphology%22">Urban morphology</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Radiative+transfer%22">Radiative transfer</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The intensification of the urban thermal environment has brought attention to urban land surface temperature (ULST). Complex building geometry and manmade material lead to significant thermal radiation directionality (TRD) of the urban canopy, and the TRD effect directly influences the accuracy of ULST retrieval algorithms. Therefore, it is essential to understand and eliminate the TRD effect to achieve high-accuracy ULST. In this context, the hemispherical brightness temperature maximum–minimum discrepancy (BTD) was quantitatively analyzed via different spectral bands, component temperature thresholds, urban geometries, and component temperature differences. Meanwhile, the DART simulations database was used to systematically evaluate 1 single-kernel- and 30 dual-kernel-driven models (KDMs), which were combined from 5 base-shape kernels (RossThick, Vinnikov, uea, RossThin, and LSF) and 6 hotspot kernels (RL, Roujean, Vinnikov, LiSparseR, LiDense, and Chen). Results show that the BTD discrepancy (ΔBTD) can reach up to 0.91 K with different band emissivities, whereas the ΔBTD is over 10 K with different component temperature differences. The building density and ratio between building heights and road widths (H/W) also exhibit their importance over urban regions. In addition, the RossThick–/Vinnikov–Roujean dual-kernel KDMs demonstrate better performance with an overall RMSE of 1.12 K. The RL-series KDMs can describe the hotspot distribution well, but the uea-series KDMs outperform at the solar principal plane (SPP) and cross-solar principal plane (CSPP). Specifically, the performance of all KDMs is sensitive to the H/W and component temperature thresholds, and urban geometry can affect the TRD RMSE with increasing H/W and a depletion of high building density. The quantitative TRD analysis and comparison provide a comprehensive reference for understanding the distribution of thermal radiation, which is also a reliable basis for developing the new TRD model over urban regions. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs17162884 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 2884 Subjects: – SubjectFull: Land surface temperature Type: general – SubjectFull: Brightness temperature Type: general – SubjectFull: Urban heat islands Type: general – SubjectFull: Urban morphology Type: general – SubjectFull: Simulation methods & models Type: general – SubjectFull: Radiative transfer Type: general Titles: – TitleFull: Assessing Kernel-Driven Models' Efficacy in Urban Thermal Radiation Directionality Modeling Using DART-Simulated Scenarios. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhu, Xiaolin – PersonEntity: Name: NameFull: Li, Zhao-Liang – PersonEntity: Name: NameFull: Nerry, Franҫoise IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 08 Text: Aug2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 17 – Type: issue Value: 16 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
