HEAL DSpace

Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment: A case study from the Greek wildland fires of 2007

Αποθετήριο DSpace/Manakin

Εμφάνιση απλής εγγραφής

dc.contributor.author Petropoulos, GP en
dc.contributor.author Knorr, W en
dc.contributor.author Scholze, M en
dc.contributor.author Boschetti, L en
dc.contributor.author Karantounias, G en
dc.date.accessioned 2014-06-06T06:50:06Z
dc.date.available 2014-06-06T06:50:06Z
dc.date.issued 2010 en
dc.identifier.issn 15618633 en
dc.identifier.uri http://62.217.125.90/xmlui/handle/123456789/4964
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-77149164782&partnerID=40&md5=b2e7e40dadbe2028a62a611ca76bd9d6 en
dc.subject.other ASTER en
dc.subject.other cartography en
dc.subject.other catastrophic event en
dc.subject.other forest fire en
dc.subject.other image analysis en
dc.subject.other Mediterranean environment en
dc.subject.other multispectral image en
dc.subject.other satellite imagery en
dc.subject.other thematic mapping en
dc.subject.other wildfire en
dc.title Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment: A case study from the Greek wildland fires of 2007 en
heal.type journalArticle en
heal.publicationDate 2010 en
heal.abstract Remote sensing is increasingly being used as a cost-effective and practical solution for the rapid evaluation of impacts from wildland fires. The present study investigates the use of the support vector machine (SVM) classification method with multispectral data from the Advanced Spectral Emission and Reflection Radiometer (ASTER) for obtaining a rapid and cost effective post-fire assessment in a Mediterranean setting. A further objective is to perform a detailed intercomparison of available burnt area datasets for one of the most catastrophic forest fire events that occurred near the Greek capital during the summer of 2007. For this purpose, two ASTER scenes were acquired, one before and one closely after the fire episode. Cartography of the burnt area was obtained by classifying each multi-band ASTER image into a number of discrete classes using the SVM classifier supported by land use/cover information from the CORINE 2000 land nomenclature. Overall verification of the derived thematic maps based on the classification statistics yielded results with a mean overall accuracy of 94.6% and a mean Kappa coefficient of 0.93. In addition, the burnt area estimate derived from the post-fire ASTER image was found to have an average difference of 9.63% from those reported by other operationally-offered burnt area datasets available for the test region. en
heal.journalName Natural Hazards and Earth System Science en
dc.identifier.issue 2 en
dc.identifier.volume 10 en
dc.identifier.spage 305 en
dc.identifier.epage 317 en


Αρχεία σε αυτό το τεκμήριο

Αρχεία Μέγεθος Μορφότυπο Προβολή

Δεν υπάρχουν αρχεία που σχετίζονται με αυτό το τεκμήριο.

Αυτό το τεκμήριο εμφανίζεται στην ακόλουθη συλλογή(ές)

Εμφάνιση απλής εγγραφής

Αναζήτηση DSpace


Σύνθετη Αναζήτηση

Αναζήτηση

Ο Λογαριασμός μου

Στατιστικές