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An analytical urban temperature model with building heterogeneity using geometric optical theory

hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorBIAN, Zunjian
hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorFAN, Tengyuan
hal.structure.identifierCentre d'études spatiales de la biosphère [CESBIO]
dc.contributor.authorROUJEAN, J.-L.
hal.structure.identifierChina University of Geosciences [Beijing]
dc.contributor.authorWANG, Dandan
hal.structure.identifierInteractions Sol Plante Atmosphère [UMR ISPA]
dc.contributor.authorIRVINE, Mark
hal.structure.identifierLaboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
dc.contributor.authorWU, Shengbiao
hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorCAO, Biao
hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorLI, Hua
hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorDU, Yongming
hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorXIAO, Qing
hal.structure.identifierAerospace Information Research Institute [AIRICAS]
dc.contributor.authorLIU, Qinhuo
dc.date.accessioned2024-04-08T11:38:45Z
dc.date.available2024-04-08T11:38:45Z
dc.date.issued2024-02
dc.identifier.issn0034-4257
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/195029
dc.description.abstractEnThe enhancement of the living conditions in big cities since the end of the last century is closely related to changes in the thermal environment and besides in urban microclimate, particularly for metropolitan areas. In this context, a knowledge of the spatial and temporal variability of urban heat island (UHI) became an increasing matter of concern, which can be measured from land surface temperature (LST). Actually, LST can be derived from thermal infrared (TIR) remote sensing observations to ensure the necessary spatial and time frequency coverage. But a full exploitation of satellite TIR data cannot be achieved without accounting for the strong anisotropy of urban landscape. Hitherto, a poor investigation was focused on the modeling and the analysis of the directional anisotropies of LSTs considering the complexity of urban building surfaces (e.g., heterogeneity of building morphology and temperature distribution) whereas it is fundamental to establish reliable critical indicators derived from energy balance. Herein, we propose an analytical model to simulate the angular signatures of urban temperatures, in which the geometric optical theory is considered to model the direct radiances of the main components (i.e., sunlit and shaded street, roof and wall). The built model assumes a random distribution of low/middle-rise and high-rise buildings, which depicts realistically the heterogeneity of urban architectural distribution. We evaluated the proposed model using both measured datasets from airborne and satellite sensors and a simulated dataset from a 3D ray-tracing model so-called discrete anisotropic radiative transfer (DART). Results indicate that 1) the proposed model is effective for simulating directional anisotropies of LSTs, with a root mean square error (RMSE) lower than 0.90 C and R-2 > 0.49 for comparison with measured datasets; and 2) the directional anisotropies of LSTs are significantly affected by variations in building height, with values possibly exceeding 1.5 degree celsius. The proposed model can be perceived as a useful tool to analyze the contribution of each component and to assess the impact of urban structure. Furthermore, it can serve to improve urban radiation budget estimations in mixed pixels.
dc.language.isoen
dc.publisherElsevier
dc.subject.enUrban temperature
dc.subject.enRadiative transfer
dc.subject.enDirectional anisotropies
dc.subject.enEnergy budget
dc.subject.enAnalytical model
dc.title.enAn analytical urban temperature model with building heterogeneity using geometric optical theory
dc.typeArticle de revue
dc.identifier.doi10.1016/j.rse.2023.113948
dc.subject.halSciences de l'environnement
bordeaux.journalRemote Sensing of Environment
bordeaux.page113948
bordeaux.volume301
bordeaux.hal.laboratoriesInteractions Soil Plant Atmosphere (ISPA) - UMR 1391*
bordeaux.institutionBordeaux Sciences Agro
bordeaux.institutionINRAE
bordeaux.peerReviewedoui
hal.identifierhal-04400853
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-04400853v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Remote%20Sensing%20of%20Environment&rft.date=2024-02&rft.volume=301&rft.spage=113948&rft.epage=113948&rft.eissn=0034-4257&rft.issn=0034-4257&rft.au=BIAN,%20Zunjian&FAN,%20Tengyuan&ROUJEAN,%20J.-L.&WANG,%20Dandan&IRVINE,%20Mark&rft.genre=article


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