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Article: Integrating ASTER and GLASS broadband emissivity products using a multi-resolution Kalman filter

TitleIntegrating ASTER and GLASS broadband emissivity products using a multi-resolution Kalman filter
Authors
KeywordsASTER
broadband emissivity
data fusion
Earth observation
GLASS
MKF
MODIS
optimal interpolation
Issue Date2016
Citation
International Journal of Digital Earth, 2016, v. 9, n. 11, p. 1098-1116 How to Cite?
AbstractIn this study, the multi-resolution Kalman filter (MKF) algorithm, which can handle multi-resolution problems with high computational efficiency, was used to blend two emissivity products: the Global LAnd Surface Satellite (GLASS) (BBE) product and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) narrowband emissivity (NBE) product. The ASTER NBE product was first converted into a BBE product. A new detrending method was used to transfer the BBEs into a process suitable for the MKF. The new detrending method was superior to the two existing methods. Finally, both the de-trended GLASS and ASTER BBE products were incorporated into the MKF framework to obtain the optimal estimation at each scale. Field measurements collected in North America were used to validate the integrated BBEs. Visually, the fusion map showed good continuity, with the exception of the border areas, and the quality of the fusion map was better than that of the original maps. The validation results indicate that the MKF improved the BBE product accuracy at the coarse scale. In addition, the MKF was capable of recovering missing pixels at a finer scale.
Persistent Identifierhttp://hdl.handle.net/10722/321674
ISSN
2023 Impact Factor: 3.7
2023 SCImago Journal Rankings: 0.950
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorShi, Linpeng-
dc.contributor.authorLiang, Shunlin-
dc.contributor.authorCheng, Jie-
dc.contributor.authorZhang, Quan-
dc.date.accessioned2022-11-03T02:20:40Z-
dc.date.available2022-11-03T02:20:40Z-
dc.date.issued2016-
dc.identifier.citationInternational Journal of Digital Earth, 2016, v. 9, n. 11, p. 1098-1116-
dc.identifier.issn1753-8947-
dc.identifier.urihttp://hdl.handle.net/10722/321674-
dc.description.abstractIn this study, the multi-resolution Kalman filter (MKF) algorithm, which can handle multi-resolution problems with high computational efficiency, was used to blend two emissivity products: the Global LAnd Surface Satellite (GLASS) (BBE) product and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) narrowband emissivity (NBE) product. The ASTER NBE product was first converted into a BBE product. A new detrending method was used to transfer the BBEs into a process suitable for the MKF. The new detrending method was superior to the two existing methods. Finally, both the de-trended GLASS and ASTER BBE products were incorporated into the MKF framework to obtain the optimal estimation at each scale. Field measurements collected in North America were used to validate the integrated BBEs. Visually, the fusion map showed good continuity, with the exception of the border areas, and the quality of the fusion map was better than that of the original maps. The validation results indicate that the MKF improved the BBE product accuracy at the coarse scale. In addition, the MKF was capable of recovering missing pixels at a finer scale.-
dc.languageeng-
dc.relation.ispartofInternational Journal of Digital Earth-
dc.subjectASTER-
dc.subjectbroadband emissivity-
dc.subjectdata fusion-
dc.subjectEarth observation-
dc.subjectGLASS-
dc.subjectMKF-
dc.subjectMODIS-
dc.subjectoptimal interpolation-
dc.titleIntegrating ASTER and GLASS broadband emissivity products using a multi-resolution Kalman filter-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/17538947.2016.1170897-
dc.identifier.scopuseid_2-s2.0-84964447021-
dc.identifier.volume9-
dc.identifier.issue11-
dc.identifier.spage1098-
dc.identifier.epage1116-
dc.identifier.eissn1753-8955-
dc.identifier.isiWOS:000382961400004-

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