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dc.contributor.authorYin, Gaohong
dc.contributor.authorMariethoz, Gregoire
dc.contributor.authorMcCabe, Matthew
dc.date.accessioned2017-02-07T08:28:37Z
dc.date.available2017-02-07T08:28:37Z
dc.date.issued2016-12-28
dc.identifier.citationYin G, Mariethoz G, McCabe M (2016) Gap-Filling of Landsat 7 Imagery Using the Direct Sampling Method. Remote Sensing 9: 12. Available: http://dx.doi.org/10.3390/rs9010012.
dc.identifier.issn2072-4292
dc.identifier.doi10.3390/rs9010012
dc.identifier.urihttp://hdl.handle.net/10754/622838
dc.description.abstractThe failure of the Scan Line Corrector (SLC) on Landsat 7 imposed systematic data gaps on retrieved imagery and removed the capacity to provide spatially continuous fields. While a number of methods have been developed to fill these gaps, most of the proposed techniques are only applicable over relatively homogeneous areas. When they are applied to heterogeneous landscapes, retrieving image features and elements can become challenging. Here we present a gap-filling approach that is based on the adoption of the Direct Sampling multiple-point geostatistical method. The method employs a conditional stochastic resampling of known areas in a training image to simulate unknown locations. The approach is assessed across a range of both homogeneous and heterogeneous regions. Simulation results show that for homogeneous areas, satisfactory results can be obtained by simply adopting non-gap locations in the target image as baseline training data. For heterogeneous landscapes, bivariate simulations using an auxiliary variable acquired at a different date provides more accurate results than univariate simulations, especially as land cover complexity increases. Apart from recovering spatially continuous fields, one of the key advantages of the Direct Sampling is the relatively straightforward implementation process that relies on relatively few parameters.
dc.description.sponsorshipThe research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST).
dc.publisherMDPI AG
dc.relation.urlhttp://www.mdpi.com/2072-4292/9/1/12
dc.rightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectGap filling
dc.subjectLandsat ETM+
dc.subjectMultiple-point geostatistics
dc.subjectScan line corrector
dc.subjectSLC
dc.titleGap-Filling of Landsat 7 Imagery Using the Direct Sampling Method
dc.typeArticle
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Division
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)
dc.identifier.journalRemote Sensing
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionInstitute of Earth Surface Dynamics, University of Lausanne, Lausanne, 1015, Switzerland
kaust.personYin, Gaohong
kaust.personMcCabe, Matthew
refterms.dateFOA2018-06-13T10:14:17Z


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This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).