Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/109981
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorDong, J-
dc.creatorZhang, T-
dc.creatorWang, L-
dc.creatorLi, Z-
dc.creatorWong, MS-
dc.creatorBilal, M-
dc.creatorZhu, Z-
dc.creatorMao, F-
dc.creatorXia, X-
dc.creatorHan, G-
dc.creatorXu, Q-
dc.creatorGu, Y-
dc.creatorLin, Y-
dc.creatorZhao, B-
dc.creatorLi, Z-
dc.creatorXu, K-
dc.creatorChen, X-
dc.creatorGong, W-
dc.date.accessioned2024-11-20T07:30:41Z-
dc.date.available2024-11-20T07:30:41Z-
dc.identifier.issn0924-2716-
dc.identifier.urihttp://hdl.handle.net/10397/109981-
dc.language.isoenen_US
dc.publisherElsevier BVen_US
dc.rights© 2024 The Author(s). Published by Elsevier B.V. on behalf of International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Dong, J., Zhang, T., Wang, L., Li, Z., Sing Wong, M., Bilal, M., Zhu, Z., Mao, F., Xia, X., Han, G., Xu, Q., Gu, Y., Lin, Y., Zhao, B., Li, Z., Xu, K., Chen, X., & Gong, W. (2024). First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation. ISPRS Journal of Photogrammetry and Remote Sensing, 211, 372-391 is available at https://doi.org/10.1016/j.isprsjprs.2024.04.020.en_US
dc.subjectDaily 160 m AOD dataseten_US
dc.subjectGaofen-1/6 WFVen_US
dc.subjectHigh resolution LSR modelingen_US
dc.subjectRetrieval algorithmen_US
dc.subjectUrban areasen_US
dc.titleFirst retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations : algorithm development and validationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage372-
dc.identifier.epage391-
dc.identifier.volume211-
dc.identifier.doi10.1016/j.isprsjprs.2024.04.020-
dcterms.abstractThe satellite-based aerosol optical depth (AOD), which can provide continuous spatial observations of aerosol loadings, is widely adopted to estimate atmospheric environmental quality and evaluate its risk for human health. However, current satellite-retrieved AOD products characterized by a comparatively coarse spatial resolution (≥1 km) can hardly analyze the structure of atmospheric pollution or its correlation with urban landscapes over populated urban areas. Existed studies have tried to address this deficiency by retrieving high-resolution AOD using Landsat images, whose long revisit period (16 days nominally), however, largely limits its applications related to urban air pollution research. To achieve both high spatial resolution and expected revisit period from satellite observation, in this study, a comprehensive AOD retrieval framework is developed for Wide-Field-of-View (WFV) satellite sensors to yield a daily AOD dataset over urban areas with 160 m spatial resolution, based on the Gaofen-1 and Gaofen-6 synergistic observations. To address the crucial challenge that the high spatial resolution and complex urban landscape both contribute a dramatic variation of land surface bidirectional reflectance, a Simulated-Annealing-coupled Semiempirical Modified Rahman-Pinty-Verstraete (SAS-MRPV) scheme is proposed to model and estimate the land surface reflectance (LSR) in the AOD retrieval framework, where the SAS-MRPV scheme is implemented using simulated annealing iteration initialized by the bidirectional reflectance distribution function (BRDF) products from the Moderate Resolution Imaging Spectrometer (MODIS) as a priori knowledge. The validation results demonstrate that the Gaofen WFV AOD retrievals exhibit good agreement with the ground-based AErosol RObotic NETwork (AERONET) and SONET (Sun-sky radiometer Observation NETwork) AOD, demonstrating the correlation coefficient and the expected error (EE)±(0.05 + 0.15AODAERONET/SONET) ratio respectively reaching up to 0.97 and over 80 %, and only slight bias fluctuations are found under different land cover types, aerosol loading, and seasonal conditions. Moreover, the validation results of Gaofen WFV AOD retrievals, with LSR estimated based on the SAS-MRPV scheme, the MODIS BRDF Products, and the Minimum Reflectance Technique (MRT) method, demonstrate better accuracy and completeness of AOD retrievals using the SAS-MPRV scheme over both natural and impervious land surfaces, indicating the stability and reliability of proposed SAS-MRPV LSR determination scheme in WFV AOD retrieval. In addition to that, the error analyses and quality control results demonstrate that the SAS-MRPV scheme is effective and necessary to guarantee the reliability and accuracy of land surface bidirectional reflectance estimation by identifying and excluding the land surface pixels unsuitable for LSR modeling, which mitigates the uncertainty and yield better accuracy in the final WFV AOD products. Furthermore, the inter-comparison between WFV-derived AOD against the operational MODIS Deep Blue (10 km), Dark Target (3 km), and Multi-Angle Implementation of Atmospheric Correction (MAIAC, 1 km) AOD products demonstrates that the 160 m WFV AOD retrievals, on the basis of obtaining similar aerosol overall descriptions as MODIS AOD retrievals, possess the capability to characterize the spatial distribution of atmospheric pollution at a finer scale with smoother variation under both clean and polluted conditions. With outstanding accuracy and reliable performance, the developed comprehensive high-resolution AOD retrieval framework exhibits substantial potential for operational AOD retrieval of Gaofen WFV satellite observations, which could be directly applied to other urban areas supporting further studies related to air pollution emission management and health risk assessment at extra-fine spatial scale.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationISPRS journal of photogrammetry and remote sensing, May 2024, v. 211, p. 372-391-
dcterms.isPartOfISPRS journal of photogrammetry and remote sensing-
dcterms.issued2024-05-
dc.identifier.scopus2-s2.0-85190876519-
dc.identifier.eissn1872-8235-
dc.description.validate202411 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextNational Natural Science Foundation of China; China Postdoctoral Science Foundationen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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