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Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials

Hyperspectral data are valuable for urban studies because of the continuous narrow bands and high spectral resolution of such data. However, using hyperspectral data presents certain difficulties because of the high dimensionality. Hyperspectral data dimensionality should be reduced without losing t...

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Main Authors: Kalantar, Bahareh, Mohd Shafri, Helmi Zulhaidi
Format: Article
Language:English
Published: Institute of Research and Development, Walailak University 2016
Online Access:http://psasir.upm.edu.my/id/eprint/53954/1/Synergistic%20use%20of%20genetic%20algorithm%20and%20spectral%20angle%20mapper%20.pdf
http://psasir.upm.edu.my/id/eprint/53954/
http://wjst.wu.ac.th/index.php/wjst/article/view/1623
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spelling my.upm.eprints.539542018-02-22T04:27:44Z http://psasir.upm.edu.my/id/eprint/53954/ Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials Kalantar, Bahareh Mohd Shafri, Helmi Zulhaidi Hyperspectral data are valuable for urban studies because of the continuous narrow bands and high spectral resolution of such data. However, using hyperspectral data presents certain difficulties because of the high dimensionality. Hyperspectral data dimensionality should be reduced without losing the spectral detail of the data. In this study, we aim to assess the capability of hyperspectral data to discriminate roof materials and evaluate the feasibility of the genetic algorithm (GA) combined with the spectral angle mapper classification to identify significant bands that are effective in discriminating roof materials. The performance of GA was estimated using the overall classification accuracy. Field spectral reflectance from 4 types of roof materials in different conditions based on age (new and old) was collected using an Analytical Spectral Devices FieldSpec 3 Spectroradiometer with a wavelength range of 350 nm to 2500 nm. In this study, we confirm the potential of GA, with high overall classification accuracy (85 %), for the selection of significant bands that have valuable information to discriminate various types of roof materials. Overall, the results from the GA analysis show 3 principle locations of bands which are located at 517, 823 and 2008 nm in the visible, near infrared and shortwave region for discriminating different materials. This finding is in agreement with previous studies in determining the significant bands for man-made materials discrimination. Previous studies also discovered similar locations and ranges in the electromagnetic spectrum. Institute of Research and Development, Walailak University 2016 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/53954/1/Synergistic%20use%20of%20genetic%20algorithm%20and%20spectral%20angle%20mapper%20.pdf Kalantar, Bahareh and Mohd Shafri, Helmi Zulhaidi (2016) Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials. Walailak Journal of Science and Technology, 13 (8). pp. 641-651. ISSN 1686-3933; ESSN: 2228-835X http://wjst.wu.ac.th/index.php/wjst/article/view/1623
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
description Hyperspectral data are valuable for urban studies because of the continuous narrow bands and high spectral resolution of such data. However, using hyperspectral data presents certain difficulties because of the high dimensionality. Hyperspectral data dimensionality should be reduced without losing the spectral detail of the data. In this study, we aim to assess the capability of hyperspectral data to discriminate roof materials and evaluate the feasibility of the genetic algorithm (GA) combined with the spectral angle mapper classification to identify significant bands that are effective in discriminating roof materials. The performance of GA was estimated using the overall classification accuracy. Field spectral reflectance from 4 types of roof materials in different conditions based on age (new and old) was collected using an Analytical Spectral Devices FieldSpec 3 Spectroradiometer with a wavelength range of 350 nm to 2500 nm. In this study, we confirm the potential of GA, with high overall classification accuracy (85 %), for the selection of significant bands that have valuable information to discriminate various types of roof materials. Overall, the results from the GA analysis show 3 principle locations of bands which are located at 517, 823 and 2008 nm in the visible, near infrared and shortwave region for discriminating different materials. This finding is in agreement with previous studies in determining the significant bands for man-made materials discrimination. Previous studies also discovered similar locations and ranges in the electromagnetic spectrum.
format Article
author Kalantar, Bahareh
Mohd Shafri, Helmi Zulhaidi
spellingShingle Kalantar, Bahareh
Mohd Shafri, Helmi Zulhaidi
Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
author_facet Kalantar, Bahareh
Mohd Shafri, Helmi Zulhaidi
author_sort Kalantar, Bahareh
title Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
title_short Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
title_full Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
title_fullStr Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
title_full_unstemmed Synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
title_sort synergistic use of genetic algorithm and spectral angle mapper for hyperspectral band selection of roof materials
publisher Institute of Research and Development, Walailak University
publishDate 2016
url http://psasir.upm.edu.my/id/eprint/53954/1/Synergistic%20use%20of%20genetic%20algorithm%20and%20spectral%20angle%20mapper%20.pdf
http://psasir.upm.edu.my/id/eprint/53954/
http://wjst.wu.ac.th/index.php/wjst/article/view/1623
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score 13.211869

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