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
Language:English
Published: Taylor & Francis 2018
Online Access:http://psasir.upm.edu.my/id/eprint/82159/1/Textural%20measures%20.pdf
http://psasir.upm.edu.my/id/eprint/82159/
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Institution: Universiti Putra Malaysia
Language: English
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spelling my.upm.eprints.821592020-12-16T14:52:14Z http://psasir.upm.edu.my/id/eprint/82159/ Textural measures for estimating oil palm age Hamsa, Camalia Saini Kanniah, Kasturi Devi Muharam, Farrah Melissa Idris, Nurul Hazrina Abdullah, Zainuriah Mohamed, Luqman 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 & Francis 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/82159/1/Textural%20measures%20.pdf Hamsa, Camalia Saini and Kanniah, Kasturi Devi and Muharam, Farrah Melissa and Idris, Nurul Hazrina and Abdullah, Zainuriah and Mohamed, Luqman (2018) Textural measures for estimating oil palm age. International Journal of Remote Sensing, 40 (4). pp. 1-22. ISSN 0143-1161; ESSN: 1366-5901 10.1080/01431161.2018.1530813
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 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
spellingShingle Hamsa, Camalia Saini
Kanniah, Kasturi Devi
Muharam, Farrah Melissa
Idris, Nurul Hazrina
Abdullah, Zainuriah
Mohamed, Luqman
Textural measures for estimating oil palm age
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 & Francis
publishDate 2018
url http://psasir.upm.edu.my/id/eprint/82159/1/Textural%20measures%20.pdf
http://psasir.upm.edu.my/id/eprint/82159/
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