Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform

In this article, the capability of discrete wavelet transform (DWT) to discriminate tree species with different ages using airborne hyperspectral remote sensing is investigated. The performance of DWT is compared against commonly used traditional methods, i.e. original reflectance and first and seco...

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Main Authors: Ghiyamat, A., Shafri, H.Z.M., Mahdiraji, G.A., Ashurov, R., Shariff, A.R.M., Mansor, S.
Format: Article
Language:English
Published: 2015
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Online Access:http://eprints.um.edu.my/13926/1/Airborne_hyperspectral_discrimination_of_tree_species_with.pdf
http://eprints.um.edu.my/13926/
http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.995272#.VREOcI7fXP8
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spelling my.um.eprints.139262015-09-22T00:16:48Z http://eprints.um.edu.my/13926/ Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform Ghiyamat, A. Shafri, H.Z.M. Mahdiraji, G.A. Ashurov, R. Shariff, A.R.M. Mansor, S. T Technology (General) TK Electrical engineering. Electronics Nuclear engineering In this article, the capability of discrete wavelet transform (DWT) to discriminate tree species with different ages using airborne hyperspectral remote sensing is investigated. The performance of DWT is compared against commonly used traditional methods, i.e. original reflectance and first and second derivatives. The hyperspectral data are obtained from Thetford forest of the UK, which contains Corsican and Scots pines with different ages and broadleaved tree species. The discrimination is performed by employing three different spectral measurement techniques (SMTs) including Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and a combination of SAM and SID. Five different mother wavelets with a total of 50 different orders are tested. The wavelet detail coefficient (CD) from each decomposition level and combination of all CDs plus the approximation coefficient from the final decomposition level (C-All) are extracted from each mother wavelet. The results show the superiority of DWT against the reflectance and derivatives for all the three SMTs. In DWT, C-All provided the highest discrimination accuracy compared to other coefficients. An overall accuracy difference of about 20-30 is observed between the finest coefficient and C-All. Amongst the SMTs, SID provided the highest accuracy, while SAM showed the lowest accuracy. Using DWT in combination with SID, an overall accuracy up to around 71.4 is obtained, which is around 13.5, 14.7, and 27 higher than the accuracies achieved with reflectance and first and second derivatives, respectively. 2015 Article PeerReviewed application/pdf en http://eprints.um.edu.my/13926/1/Airborne_hyperspectral_discrimination_of_tree_species_with.pdf Ghiyamat, A. and Shafri, H.Z.M. and Mahdiraji, G.A. and Ashurov, R. and Shariff, A.R.M. and Mansor, S. (2015) Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform. International Journal of Remote Sensing, 36 (1). pp. 318-342. ISSN 0143-1161 http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.995272#.VREOcI7fXP8 Doi 10.1080/01431161.2014.995272
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle T Technology (General)
TK Electrical engineering. Electronics Nuclear engineering
Ghiyamat, A.
Shafri, H.Z.M.
Mahdiraji, G.A.
Ashurov, R.
Shariff, A.R.M.
Mansor, S.
Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
description In this article, the capability of discrete wavelet transform (DWT) to discriminate tree species with different ages using airborne hyperspectral remote sensing is investigated. The performance of DWT is compared against commonly used traditional methods, i.e. original reflectance and first and second derivatives. The hyperspectral data are obtained from Thetford forest of the UK, which contains Corsican and Scots pines with different ages and broadleaved tree species. The discrimination is performed by employing three different spectral measurement techniques (SMTs) including Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and a combination of SAM and SID. Five different mother wavelets with a total of 50 different orders are tested. The wavelet detail coefficient (CD) from each decomposition level and combination of all CDs plus the approximation coefficient from the final decomposition level (C-All) are extracted from each mother wavelet. The results show the superiority of DWT against the reflectance and derivatives for all the three SMTs. In DWT, C-All provided the highest discrimination accuracy compared to other coefficients. An overall accuracy difference of about 20-30 is observed between the finest coefficient and C-All. Amongst the SMTs, SID provided the highest accuracy, while SAM showed the lowest accuracy. Using DWT in combination with SID, an overall accuracy up to around 71.4 is obtained, which is around 13.5, 14.7, and 27 higher than the accuracies achieved with reflectance and first and second derivatives, respectively.
format Article
author Ghiyamat, A.
Shafri, H.Z.M.
Mahdiraji, G.A.
Ashurov, R.
Shariff, A.R.M.
Mansor, S.
author_facet Ghiyamat, A.
Shafri, H.Z.M.
Mahdiraji, G.A.
Ashurov, R.
Shariff, A.R.M.
Mansor, S.
author_sort Ghiyamat, A.
title Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
title_short Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
title_full Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
title_fullStr Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
title_full_unstemmed Airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
title_sort airborne hyperspectral discrimination of tree species with different ages using discrete wavelet transform
publishDate 2015
url http://eprints.um.edu.my/13926/1/Airborne_hyperspectral_discrimination_of_tree_species_with.pdf
http://eprints.um.edu.my/13926/
http://www.tandfonline.com/doi/abs/10.1080/01431161.2014.995272#.VREOcI7fXP8
_version_ 1643689686231678976
score 13.188404