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Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area

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Bibliographic Details
Main Authors: Teoh, Chin Chuang, Dr., Shattri, Mansor, Abdul Rashid, Mohamed Shariff, Noordin, Ahmad
Other Authors: cchin@mardi.my
Format: Article
Language:English
Published: The Institution of Engineers, Malaysia 2011
Subjects:
Best Bands Selection
Image classification
Image visualisation
MASTER remotely sensed data
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/13700
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spelling my.unimap-137002011-09-10T07:22:53Z Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area Teoh, Chin Chuang, Dr. Shattri, Mansor Abdul Rashid, Mohamed Shariff Noordin, Ahmad cchin@mardi.my Best Bands Selection Image classification Image visualisation MASTER remotely sensed data Link to publisher's homepage at http://www.myiem.org.my/ A Best Band Selection Index (BBSI) algorithm to select the best band combination for image visualization and classification of high spectral resolution remotely sensed dataset was introduced in this paper. The BBSI is calculated by two components, one based on class mean (or cluster mean) difference and the other based on correlation coefficients. Using MODIS/ASTER A i r b o r n e Simulator (MASTER) images taken over Jertih, Te rengganu in 2000 as the test dataset, the BBSI correctly predicted the best t h ree-band combination that provided useful information for visualization of the image to collect training samples in superv i s e d classification. The BBSI also accurately selected the best four-band combination that produced high overall accuracy classification map with value of 89.7%. 2011-09-10T07:22:53Z 2011-09-10T07:22:53Z 2006-12 Article The Journal of the Institution of Engineers, Malaysia, vol. 67(4), 2006, pages 34-39 0126-513X http://myiem.org.my/content/iem_journal_2006-177.aspx http://hdl.handle.net/123456789/13700 en The Institution of Engineers, Malaysia
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Best Bands Selection
Image classification
Image visualisation
MASTER remotely sensed data
spellingShingle Best Bands Selection
Image classification
Image visualisation
MASTER remotely sensed data
Teoh, Chin Chuang, Dr.
Shattri, Mansor
Abdul Rashid, Mohamed Shariff
Noordin, Ahmad
Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area
description Link to publisher's homepage at http://www.myiem.org.my/
author2 cchin@mardi.my
author_facet cchin@mardi.my
Teoh, Chin Chuang, Dr.
Shattri, Mansor
Abdul Rashid, Mohamed Shariff
Noordin, Ahmad
format Article
author Teoh, Chin Chuang, Dr.
Shattri, Mansor
Abdul Rashid, Mohamed Shariff
Noordin, Ahmad
author_sort Teoh, Chin Chuang, Dr.
title Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area
title_short Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area
title_full Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area
title_fullStr Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area
title_full_unstemmed Image visualisation and classification of MODIS/ASTER Airborne Simulator (MASTER) remotely sensed data for agricultural area
title_sort image visualisation and classification of modis/aster airborne simulator (master) remotely sensed data for agricultural area
publisher The Institution of Engineers, Malaysia
publishDate 2011
url http://dspace.unimap.edu.my/xmlui/handle/123456789/13700
_version_ 1643790923015913472
score 13.222552

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