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  1. University of Computer Studies, Yangon
  2. Conferences

Detection of Environmental Changes through Supervised Classification

http://hdl.handle.net/20.500.12678/0000003433
http://hdl.handle.net/20.500.12678/0000003433
cabd881a-904d-4144-93eb-f428f441c4b3
846d8079-96df-4767-bcb2-9a7192f55825
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psc2010paper psc2010paper (234).pdf (964 Kb)
Publication type
Article
Upload type
Publication
Title
Title Detection of Environmental Changes through Supervised Classification
Language en
Publication date 2010-12-16
Authors
Myint, Aye Yadanar
Thein, Nilar
Description
Nowadays, satellite based remote sensing technology has been successfully utilized for mapping, monitoring and detection of environmental changes. The interested information will be extracted from satellite images by using Digital Image Processing. In this paper, the environmental changes due to natural hazards can be detected and monitored using supervised classification. To extract the information from the multi-date images, the Minimum Distance classifier (MD) is used to identify the classes of images based on RGB color values. It is used in training and also in recognition. The Minimum distance classifier which is based on training data characterizes each class by its mean position on each band. The classification is performed by placing a pixel in the class of the nearest mean. The main purpose of this paper is to evaluate and compare the satellite images of before and after natural disasters in the world with results from the supervised training based methods.
Keywords
Remotely sensed image, Image Classification, Change detection, Minimum distance classifier
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1183
Journal articles
Fifth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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