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Conference Paper: A NEW SPATIAL and TEMPORAL FUSION MODEL

TitleA NEW SPATIAL and TEMPORAL FUSION MODEL
Authors
KeywordsAuto-regression Error
Image Fusion
Landsat
MODIS
Spatial and Temporal Model
Issue Date2016
Citation
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016, v. 3, p. 203-206 How to Cite?
AbstractAs Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) has a tradeoff between the high temporal resolution and high spatial resolution, this paper proposed a spatial and temporal model with auto-regression error correction (AREC) method to blend the two types of images in order to obtain the composed image with both high spatial and temporal resolution. Experiments and validation were conducted on a data set located in Shenzhen, China and compared with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in several objective indexes and visual analysis. It was found that AREC could effectively predict the land cover changes and the fusion results had better performances versus the ones of STARFM.
Persistent Identifierhttp://hdl.handle.net/10722/329510
ISSN
2023 SCImago Journal Rankings: 0.317

 

DC FieldValueLanguage
dc.contributor.authorWang, Jing-
dc.contributor.authorHuang, Bo-
dc.date.accessioned2023-08-09T03:33:18Z-
dc.date.available2023-08-09T03:33:18Z-
dc.date.issued2016-
dc.identifier.citationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016, v. 3, p. 203-206-
dc.identifier.issn2194-9042-
dc.identifier.urihttp://hdl.handle.net/10722/329510-
dc.description.abstractAs Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) has a tradeoff between the high temporal resolution and high spatial resolution, this paper proposed a spatial and temporal model with auto-regression error correction (AREC) method to blend the two types of images in order to obtain the composed image with both high spatial and temporal resolution. Experiments and validation were conducted on a data set located in Shenzhen, China and compared with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in several objective indexes and visual analysis. It was found that AREC could effectively predict the land cover changes and the fusion results had better performances versus the ones of STARFM.-
dc.languageeng-
dc.relation.ispartofISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences-
dc.subjectAuto-regression Error-
dc.subjectImage Fusion-
dc.subjectLandsat-
dc.subjectMODIS-
dc.subjectSpatial and Temporal Model-
dc.titleA NEW SPATIAL and TEMPORAL FUSION MODEL-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.5194/isprs-annals-III-7-203-2016-
dc.identifier.scopuseid_2-s2.0-85048922974-
dc.identifier.volume3-
dc.identifier.spage203-
dc.identifier.epage206-
dc.identifier.eissn2194-9050-

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