Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.

Discrimination of tree species with different ages is performed in three classifications using hyperspectral data. The first classification is between Broadleaves and pines; the second classification is between Broadleaves, Corsican Pines, and Scots Pines, and the third classification is between six...

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Main Authors: Mohd Shafri, Helmi Zulhaidi, Mohamed Shariff, Abd Rashid, Mansor, Shattri, Ashurov, Ravshan
Format: Article
Language:English
English
Published: 2013
Online Access:http://psasir.upm.edu.my/id/eprint/28510/1/Hyperspectral%20discrimination%20of%20tree%20species%20with%20different%20classifications%20using%20single.pdf
http://psasir.upm.edu.my/id/eprint/28510/
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spelling my.upm.eprints.285102015-10-08T02:51:45Z http://psasir.upm.edu.my/id/eprint/28510/ Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember. Mohd Shafri, Helmi Zulhaidi Mohamed Shariff, Abd Rashid Mansor, Shattri Ashurov, Ravshan Discrimination of tree species with different ages is performed in three classifications using hyperspectral data. The first classification is between Broadleaves and pines; the second classification is between Broadleaves, Corsican Pines, and Scots Pines, and the third classification is between six tree species including different ages of Corsican and Scots Pines. These three classifications are performed by having single- and multiple-endmember and considering five different spectral measure techniques (SMTs) in combination with reflectance spectra (ReflS), first and second derivative spectra. The result shows that using single-endmember, derivative spectra are not useful for a more challenging classification. This is further emphasized in multiple-endmember classification, where all SMTs perform better in ReflS rather than derivative in all classifications. Furthermore, using derivative spectra, discrimination accuracy become more dependent on the type of SMTs, especially in single-endmember. By employing multiple-endmember, the within-species variation is significantly reduced, thereby, the remaining challenge in discriminating tree species with different ages is only due to the between-species similarity. Overall, discrimination accuracies around 92.4, 76.8, and 71.5% are obtained using original reflectance and multiple-endmember for the first, second, and third classification, which is around 14.3, 17, and 8.3% higher than what were obtained in single-endmember classifications, respectively. Also, amongst the five SMTs, Euclidean distance (in both single- and multiple-endmember) and Jeffreys–Matusita distance (in single-endmember and derivative spectra) provided the highest discrimination accuracies in different classifications. Furthermore, when discrimination become more challenging from the first to second and third classification, the performance difference between different SMTs is increased from 1.4 to 3.8 and 7.3%, respectively. The study shows high potential of multiple-endmember to be employed in remote sensing applications in the future for improving tree species discrimination accuracy. 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28510/1/Hyperspectral%20discrimination%20of%20tree%20species%20with%20different%20classifications%20using%20single.pdf Mohd Shafri, Helmi Zulhaidi and Mohamed Shariff, Abd Rashid and Mansor, Shattri and Ashurov, Ravshan (2013) Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember. International Journal of Applied Earth Observation and Geoinformation, 23 (August). pp. 177-191. ISSN 0303-2434 10.1016/j.jag.2013.01.004 English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Discrimination of tree species with different ages is performed in three classifications using hyperspectral data. The first classification is between Broadleaves and pines; the second classification is between Broadleaves, Corsican Pines, and Scots Pines, and the third classification is between six tree species including different ages of Corsican and Scots Pines. These three classifications are performed by having single- and multiple-endmember and considering five different spectral measure techniques (SMTs) in combination with reflectance spectra (ReflS), first and second derivative spectra. The result shows that using single-endmember, derivative spectra are not useful for a more challenging classification. This is further emphasized in multiple-endmember classification, where all SMTs perform better in ReflS rather than derivative in all classifications. Furthermore, using derivative spectra, discrimination accuracy become more dependent on the type of SMTs, especially in single-endmember. By employing multiple-endmember, the within-species variation is significantly reduced, thereby, the remaining challenge in discriminating tree species with different ages is only due to the between-species similarity. Overall, discrimination accuracies around 92.4, 76.8, and 71.5% are obtained using original reflectance and multiple-endmember for the first, second, and third classification, which is around 14.3, 17, and 8.3% higher than what were obtained in single-endmember classifications, respectively. Also, amongst the five SMTs, Euclidean distance (in both single- and multiple-endmember) and Jeffreys–Matusita distance (in single-endmember and derivative spectra) provided the highest discrimination accuracies in different classifications. Furthermore, when discrimination become more challenging from the first to second and third classification, the performance difference between different SMTs is increased from 1.4 to 3.8 and 7.3%, respectively. The study shows high potential of multiple-endmember to be employed in remote sensing applications in the future for improving tree species discrimination accuracy.
format Article
author Mohd Shafri, Helmi Zulhaidi
Mohamed Shariff, Abd Rashid
Mansor, Shattri
Ashurov, Ravshan
spellingShingle Mohd Shafri, Helmi Zulhaidi
Mohamed Shariff, Abd Rashid
Mansor, Shattri
Ashurov, Ravshan
Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
author_facet Mohd Shafri, Helmi Zulhaidi
Mohamed Shariff, Abd Rashid
Mansor, Shattri
Ashurov, Ravshan
author_sort Mohd Shafri, Helmi Zulhaidi
title Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
title_short Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
title_full Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
title_fullStr Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
title_full_unstemmed Hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
title_sort hyperspectral discrimination of tree species with different classifications using single- and multiple-endmember.
publishDate 2013
url http://psasir.upm.edu.my/id/eprint/28510/1/Hyperspectral%20discrimination%20of%20tree%20species%20with%20different%20classifications%20using%20single.pdf
http://psasir.upm.edu.my/id/eprint/28510/
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score 13.222552