Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/78685
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorKwan, C-
dc.creatorZhu, XL-
dc.creatorGao, F-
dc.creatorChou, BY-
dc.creatorPerez, D-
dc.creatorLi, J-
dc.creatorShen, YZ-
dc.creatorKoperski, K-
dc.creatorMarchisio, G-
dc.date.accessioned2018-09-28T01:17:17Z-
dc.date.available2018-09-28T01:17:17Z-
dc.identifier.issn1424-8220en_US
dc.identifier.urihttp://hdl.handle.net/10397/78685-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rightsCopyright © 2018 ZhonghuWu et al. This is an open access article distributed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.en_US
dc.rightsThe following publication Kwan, C., Zhu, X., Gao, F., Chou, B., Perez, D., Li, J., . . . Marchisio, G. (2018). Assessment of spatiotemporal fusion algorithms for planet and worldview images. Sensors (Switzerland), 18(4), 1051 is available at https://doi.org/10.3390/s18041051en_US
dc.subjectImage fusionen_US
dc.subjectPlaneten_US
dc.subjectWorldviewen_US
dc.subjectPansharpeningen_US
dc.subjectForward predictionen_US
dc.subjectSpatiotemporalen_US
dc.titleAssessment of spatiotemporal fusion algorithms for planet and worldview imagesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume18en_US
dc.identifier.issue4en_US
dc.identifier.doi10.3390/s18041051en_US
dcterms.abstractAlthough Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSensors (Switzerland), Apr. 2018, v. 18, no. 4, 1051-
dcterms.isPartOfSensors (Switzerland)-
dcterms.issued2018-
dc.identifier.isiWOS:000435574800123-
dc.identifier.scopus2-s2.0-85044977898-
dc.identifier.artn1051en_US
dc.identifier.rosgroupid2017004403-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201809 bcrcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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