MARC Record from University of Toronto

LEADER: 02093nam 2200241 4500
001 AAIMR27471
005 20071128104236.5
008 071128s2007 onc|||||||||||||| ||eng d
020 $a9780494274712
039 $feh
100 1 $aLackner, Michael.
245 13 $aAn object-oriented approach to urban land-cover and land-use classification.
260 $c2007.
300 $a151 leaves.
500 $aSource: Masters Abstracts International, Volume: 45-06, page: 2899.
502 $aThesis (M.Sc.)--University of Toronto, 2007.
506 $aElectronic version licensed for access by U. of T. users.
520 $aThe greater availability of remotely sensed high-resolution imagery and recent advances in object-oriented analysis allows for more detail than ever before in urban image classification. This thesis explores object-oriented land-cover and land-use classifications with 1-meter resolution Ikonos imagery for an area in Mississauga, Ontario. First, three different ways of classifying land cover, with varying inclusion of ancillary building and road data, are examined. Second, the spatial relations of the land-cover information are examined to derive land use. Formal accuracy assessments, as well as statistical and visual evaluations, for the land-cover and land-use classifications show that the object-oriented approach works well for classifying an urban area. The results of this thesis confirm the observed trend in the literature to move away from the traditional pixel-based techniques for urban image classification in exchange for object-oriented classification methods; which include shape, textural, and contextual information in addition to spectral information.
590 $aROBARTS MICROTEXT copy on microfiche.$5CaOTU
653 $aGeography.
856 41 $uhttp://link.library.utoronto.ca/eir/EIRdetail.cfm?Resources__ID=452951&T=F$yConnect to resource
949 $atheses masters$wALPHANUM$c1$i6262747-1001$j2$lMICROTEXT$mMEDIA_COMM$rN$sY$tMICROFORM$u3/12/2007
949 $aOnline resource 452951$wASIS$c1$i6262747-2001$lONLINE$mE_RESOURCE$rY$sY$tE_RESOURCE$u3/12/2007