Multi-levels classification for tropical tree species identification using in-situ hyperspectral data

Multi-Levels classification process has been applied to handle a large number of tropical forest tree species using in-situ Hyperspectral data. Improvement in overall classification accuracy has been achieved with Support Vector Machine and Maximum Likelihood Classifier in identifying twenty tropica...

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Main Authors: Lau, Alvin Meng Shin, Chew, Wei Chuang, Lawal, M.
Format: Conference or Workshop Item
Published: 2015
Subjects:
Online Access:http://eprints.utm.my/id/eprint/62225/
http://radar.com.my/iwgrs2015/regform/iwgrs2015-call%20for%20papers%20Brochure.pdf
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Institution: Universiti Teknologi Malaysia
id my.utm.62225
record_format eprints
spelling my.utm.622252017-05-14T03:28:04Z http://eprints.utm.my/id/eprint/62225/ Multi-levels classification for tropical tree species identification using in-situ hyperspectral data Lau, Alvin Meng Shin Chew, Wei Chuang Lawal, M. SD Forestry Multi-Levels classification process has been applied to handle a large number of tropical forest tree species using in-situ Hyperspectral data. Improvement in overall classification accuracy has been achieved with Support Vector Machine and Maximum Likelihood Classifier in identifying twenty tropical forest tree species. The improvement in accuracy for the both classifiers about 5% from the first level classification to the third level classification process in this study. The findings have proven the effectiveness of this multi- levels classification procedure in handling the issue of high diversity is tropical forest environmental during tree species mapping. 2015 Conference or Workshop Item PeerReviewed Lau, Alvin Meng Shin and Chew, Wei Chuang and Lawal, M. (2015) Multi-levels classification for tropical tree species identification using in-situ hyperspectral data. In: IEEE Workshop on Geoscience and Remote Sensing 2015, 16-17 Nov, 2015, Kuala Lumpur, Malaysia. http://radar.com.my/iwgrs2015/regform/iwgrs2015-call%20for%20papers%20Brochure.pdf
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic SD Forestry
spellingShingle SD Forestry
Lau, Alvin Meng Shin
Chew, Wei Chuang
Lawal, M.
Multi-levels classification for tropical tree species identification using in-situ hyperspectral data
description Multi-Levels classification process has been applied to handle a large number of tropical forest tree species using in-situ Hyperspectral data. Improvement in overall classification accuracy has been achieved with Support Vector Machine and Maximum Likelihood Classifier in identifying twenty tropical forest tree species. The improvement in accuracy for the both classifiers about 5% from the first level classification to the third level classification process in this study. The findings have proven the effectiveness of this multi- levels classification procedure in handling the issue of high diversity is tropical forest environmental during tree species mapping.
format Conference or Workshop Item
author Lau, Alvin Meng Shin
Chew, Wei Chuang
Lawal, M.
author_facet Lau, Alvin Meng Shin
Chew, Wei Chuang
Lawal, M.
author_sort Lau, Alvin Meng Shin
title Multi-levels classification for tropical tree species identification using in-situ hyperspectral data
title_short Multi-levels classification for tropical tree species identification using in-situ hyperspectral data
title_full Multi-levels classification for tropical tree species identification using in-situ hyperspectral data
title_fullStr Multi-levels classification for tropical tree species identification using in-situ hyperspectral data
title_full_unstemmed Multi-levels classification for tropical tree species identification using in-situ hyperspectral data
title_sort multi-levels classification for tropical tree species identification using in-situ hyperspectral data
publishDate 2015
url http://eprints.utm.my/id/eprint/62225/
http://radar.com.my/iwgrs2015/regform/iwgrs2015-call%20for%20papers%20Brochure.pdf
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