Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/1839
DC FieldValueLanguage
dc.contributor.authorHadjimitsis, Diofantos G.-
dc.contributor.authorRetalis, Adrianos-
dc.contributor.authorClayton, Chris R I-
dc.date.accessioned2012-11-28T06:53:06Zen
dc.date.accessioned2013-05-17T05:21:58Z-
dc.date.accessioned2015-12-02T09:49:09Z-
dc.date.available2012-11-28T06:53:06Zen
dc.date.available2013-05-17T05:21:58Z-
dc.date.available2015-12-02T09:49:09Z-
dc.date.issued2003-09-
dc.identifier.citationRemote Sensing for Environmental Monitoring, GIS Applications, and Geology III, 2003, 8-12 September, Barcelona, Spainen_US
dc.identifier.issn0277-786X-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/1839-
dc.description.abstractAtmospheric correction is an essential part of the pre-processing of satellite remote sensing data. Several atmospheric correction approaches can be found in the literature ranging from simple to sophisticated methods. The sophisticated methods require auxiliary data, however the simple methods are based only on the image itself and are served to be suitable for operational use. One of the most widely used and well-known simple atmospheric correction methods is the darkest pixel (DP). Despite of its simplicity, the user must be aware of several key points in order to avoid any erroneous results. Indeed, this paper addresses a new strategy for selecting the suitable dark object based on the proposed analysis of digital number histograms and image examination. Several case studies, in which satellite remotely sensed image data intended for environmental applications have been atmospherically corrected using the DP method, are presented in this article.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© SPIEen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectRemote sensingen_US
dc.subjectAlgorithmsen_US
dc.subjectData reductionen_US
dc.subjectEnvironmental impact analysisen_US
dc.subjectImage analysisen_US
dc.subjectMeteorologyen_US
dc.subjectSatellitesen_US
dc.subjectRegression analysisen_US
dc.titleOn the darkest pixel atmospheric correction algorithm: a revised procedure applied over satellite remotely sensed images intended for environmental applicationsen_US
dc.typeConference Papersen_US
dc.affiliationCyprus University of Technologyen
dc.collaborationUniversity of Southamptonen_US
dc.collaborationFrederick Institute of Technologyen_US
dc.subject.categoryENGINEERING AND TECHNOLOGYen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1117/12.511520en_US
dc.dept.handle123456789/54en
cut.common.academicyear2003-2004en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-2684-547X-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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