Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113728
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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.creatorMa, Yen_US
dc.creatorLiu, Ten_US
dc.creatorYu, Zen_US
dc.creatorJiang, Cen_US
dc.creatorLu, Zen_US
dc.date.accessioned2025-06-19T06:23:32Z-
dc.date.available2025-06-19T06:23:32Z-
dc.identifier.issn1939-1404en_US
dc.identifier.urihttp://hdl.handle.net/10397/113728-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.rightsThe following publication Y. Ma, T. Liu, Z. Yu, C. Jiang and Z. Lu, "Assessment of Numerical Weather Models With Different Spatial Resolutions on Tropospheric Delay Correction for InSAR," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 14133-14144, 2024 is available at https://doi.org/10.1109/JSTARS.2024.3440648.en_US
dc.subjectInterferometric synthetic aperture radar (InSAR)en_US
dc.subjectNumerical weather models (NWMs)en_US
dc.subjectTropospheric correctionen_US
dc.titleAssessment of numerical weather models with different spatial resolutions on tropospheric delay correction for InSARen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage14133en_US
dc.identifier.epage14144en_US
dc.identifier.volume17en_US
dc.identifier.doi10.1109/JSTARS.2024.3440648en_US
dcterms.abstractSpatial variations in atmospheric parameters, including pressure, temperature, and humidity, significantly impact the precision of interferometric synthetic aperture radar (InSAR) measurements. This significantly limits the applicability of InSAR in the fields, such as terrain inversion and deformation monitoring. Fortunately, the evolving numerical weather models (NWMs) could offer a viable tropospheric correction solution. However, given the influence of complex terrain and areas with sparse atmospheric observation, the effectiveness of tropospheric correction with different NWMs' resolutions remains to be evaluated. This requires the examination of different NWMs tropospheric delay correction in detail with sufficient metrics. A total of 36 Sentinel-1 interferograms of 2023, which cover Berlin, Paris, and Milan, respectively, are used as examples. Tropospheric correction is carried out using ICOsahedral nonhydrostatic D2 (ICON-D2), the fifth-generation European Centre for Medium-Range Weather Forecast atmospheric reanalysis, and modern-era retrospective analysis for research and applications version 2. To assess the correction efficacy of various resolutions, standard deviation, semivariogram function, and phase-elevation correlation coefficient served as the evaluation method. Results show that the ICON-D2 model outperforms the other models in these metrics, especially in regions with significant topographic relief. Among them, the standard deviation of the corrected interferogram decreased by 21.6%-35.8%. NWMs have demonstrated effectiveness in mitigating altitude-related tropospheric delays without needing altitude assimilation. Overall, the present study underscores that despite potential uncalibrated atmospheric effects, high-resolution NWMs are anticipated to provide a more precise solution for InSAR, especially in regions exhibiting intricate and challenging terrain features.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE journal of selected topics in applied earth observations and remote sensing, 2024, v. 17, p. 14133-14144en_US
dcterms.isPartOfIEEE journal of selected topics in applied earth observations and remote sensingen_US
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85200806308-
dc.identifier.eissn2151-1535en_US
dc.description.validate202506 bchyen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera3753-
dc.identifier.SubFormID50949-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work was supported by the Key-Area Research and Development Program of Guangdong Province under Grant 2020B0303020001.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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