Dublin Core
Title
Perbandingan Object Oriented Classification dan Maximum Likelihood Classification pada Pemetaan Penutupan Lahan di Kabupaten Gayo Lues
Subject
object oriented classification; maximum likehood classification; segmentation; hierarchical
Description
Comparison of object Oriented Classification With Maximum Likelihood Classification on Land Cover Maaping in District of Gayo LuesABSTRACT. Image classification method used critically effects the classified image produced as well as its accuracy. One of the recently introduced classification methods is Object-Oriented Classification (OOC). The fundamental difference between this method and that of Maximum Likelihood Classification (MLC) lies on the basic unit of image analytical prosses, i.e., image object or segment, and not on a single pixed. The new classification method uses a segmentation procedure with a hierarchical approach which allows an addition of an object characteristic to other information related to the classified object, such as from, texture, and context. This object or segment is formed because the smallest region has a larger area than the image pixel. In this study, MLC and OOC classification methods were compered using Landsat ETM+ image for Gayo Lues District of Aceh. The objective of this study was to map out land cover/ landuse classes of the research area and compare the result and its accuracy using the MLC and OOC classification methods. Result of the study showed that a higher, more detailed, hierarchical land cover/ landuse class with a higher accuracy was obtained using OOC classification method which corresponds better to the contextual condition in the field compared to that of the pixel- based classification method.
Creator
Rusdi, Muhammad; Program Studi Ilmu Tanah, Fakultas Pertanian, Universitas Syiah Kuala
Source
Jurnal Agrista; Vol 12, No 2 (2008): Volume 12 Nomor 2 Agustus 2008; 73-79
1410-3389
1410-3389
Publisher
Fakultas Pertanian, Universitas Syiah Kuala
Date
2008-08-01
Relation
http://jurnal.unsyiah.ac.id/agrista/article/view/1136/1053
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
http://jurnal.unsyiah.ac.id/agrista/article/view/1136