Textural measures for estimating oil palm age

In oil palm management, age is one of the yield determinant factors. The conventional field investigations are often exhaustive and costly methods when implemented on a large scale. Despite much attention to classify individual oil palm ages by using various remote sensing images, none of the studie...

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Main Authors: Hamsa, Camalia Saini, Kanniah, Kasturi Devi, Muharam, Farrah Melissa, Idris, Nurul Hazrina, Abdullah, Zainuriah, Mohamed, Luqman
Format: Article
Published: Taylor and Francis Ltd. 2019
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Online Access:http://eprints.utm.my/id/eprint/87539/
http://dx.doi.org/10.1080/01431161.2018.1530813
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.875392020-11-08T04:05:56Z http://eprints.utm.my/id/eprint/87539/ Textural measures for estimating oil palm age Hamsa, Camalia Saini Kanniah, Kasturi Devi Muharam, Farrah Melissa Idris, Nurul Hazrina Abdullah, Zainuriah Mohamed, Luqman NA Architecture In oil palm management, age is one of the yield determinant factors. The conventional field investigations are often exhaustive and costly methods when implemented on a large scale. Despite much attention to classify individual oil palm ages by using various remote sensing images, none of the studies depicted satisfying overall accuracies. The overall aim of this study was to optimize window size and number of texture measurements for oil palm ages classification. The study was conducted in a commercial oil palm plantation comprised of palms of multiple ages planted from 1991 to 2008. Three Satellite Pour l’Observation de la Terre (SPOT)-5 multispectral images, acquired on 12 April 2012, 4 April 2013, and 14 April 2014, were evaluated. The individual ages were successfully classified with accuracy ranging from 59% to 97%, with an average overall accuracy of 84%. The results illustrated that the largest window size related to the smallest oil palm planting block in the study area, 390 m × 390 m on-the-ground window size, and seven combination of texture measurements, resulted in the highest classification overall accuracy. The utilization of texture measurements produced synergistic effects able to discriminate the oil palm age, with mean, entropy, homogeneity, and angular second moment as among the significant textures. Taylor and Francis Ltd. 2019-10-02 Article PeerReviewed Hamsa, Camalia Saini and Kanniah, Kasturi Devi and Muharam, Farrah Melissa and Idris, Nurul Hazrina and Abdullah, Zainuriah and Mohamed, Luqman (2019) Textural measures for estimating oil palm age. International Journal of Remote Sensing, 40 (19). pp. 7516-7537. ISSN 0143-1161 http://dx.doi.org/10.1080/01431161.2018.1530813 DOI:10.1080/01431161.2018.1530813
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 NA Architecture
spellingShingle NA Architecture
Hamsa, Camalia Saini
Kanniah, Kasturi Devi
Muharam, Farrah Melissa
Idris, Nurul Hazrina
Abdullah, Zainuriah
Mohamed, Luqman
Textural measures for estimating oil palm age
description In oil palm management, age is one of the yield determinant factors. The conventional field investigations are often exhaustive and costly methods when implemented on a large scale. Despite much attention to classify individual oil palm ages by using various remote sensing images, none of the studies depicted satisfying overall accuracies. The overall aim of this study was to optimize window size and number of texture measurements for oil palm ages classification. The study was conducted in a commercial oil palm plantation comprised of palms of multiple ages planted from 1991 to 2008. Three Satellite Pour l’Observation de la Terre (SPOT)-5 multispectral images, acquired on 12 April 2012, 4 April 2013, and 14 April 2014, were evaluated. The individual ages were successfully classified with accuracy ranging from 59% to 97%, with an average overall accuracy of 84%. The results illustrated that the largest window size related to the smallest oil palm planting block in the study area, 390 m × 390 m on-the-ground window size, and seven combination of texture measurements, resulted in the highest classification overall accuracy. The utilization of texture measurements produced synergistic effects able to discriminate the oil palm age, with mean, entropy, homogeneity, and angular second moment as among the significant textures.
format Article
author Hamsa, Camalia Saini
Kanniah, Kasturi Devi
Muharam, Farrah Melissa
Idris, Nurul Hazrina
Abdullah, Zainuriah
Mohamed, Luqman
author_facet Hamsa, Camalia Saini
Kanniah, Kasturi Devi
Muharam, Farrah Melissa
Idris, Nurul Hazrina
Abdullah, Zainuriah
Mohamed, Luqman
author_sort Hamsa, Camalia Saini
title Textural measures for estimating oil palm age
title_short Textural measures for estimating oil palm age
title_full Textural measures for estimating oil palm age
title_fullStr Textural measures for estimating oil palm age
title_full_unstemmed Textural measures for estimating oil palm age
title_sort textural measures for estimating oil palm age
publisher Taylor and Francis Ltd.
publishDate 2019
url http://eprints.utm.my/id/eprint/87539/
http://dx.doi.org/10.1080/01431161.2018.1530813
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