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Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach

Oil palm is a commercial crop that is important for its food value and as a biofuel, along with its other benefits towards the economy and human health. Currently, Malaysia cultivates approximately 5.64 million ha of oil palm. To date, a study identifying abandoned oil palm areas using satellite ima...

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Main Authors: Yusoff, Noryusdiana Mohamad, Muharam, Farrah Melissa, Khairunniza-Bejo, Siti
Format: Article
Language:English
Published: Taylor & Francis 2017
Online Access:http://psasir.upm.edu.my/id/eprint/63592/1/Towards%20the%20use%20of%20remote-sensing%20data%20for%20monitoring%20of%20abandoned%20oil%20palm%20lands%20in%20Malaysia.pdf
http://psasir.upm.edu.my/id/eprint/63592/
https://www.tandfonline.com/doi/abs/10.1080/01431161.2016.1266111
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spelling my.upm.eprints.635922018-11-07T08:16:25Z http://psasir.upm.edu.my/id/eprint/63592/ Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach Yusoff, Noryusdiana Mohamad Muharam, Farrah Melissa Khairunniza-Bejo, Siti Oil palm is a commercial crop that is important for its food value and as a biofuel, along with its other benefits towards the economy and human health. Currently, Malaysia cultivates approximately 5.64 million ha of oil palm. To date, a study identifying abandoned oil palm areas using satellite images is almost non-existent. Conventionally, the monitoring of abandoned oil palm lands is tedious and time consuming, especially over large areas. Hence, in this article, the capability of high resolution satellite image via Satellite Pour I’Observation de la Terre-6 (SPOT-6) products to extract abandoned oil palm areas was explored, as was the use of multi-temporal Landsat Operational Land Imager (OLI) imagery to develop the phenology of abandoned oil palm sites. Homogeneity measures derived through SPOT images played a more important role to identify abandoned oil palm than crop phenology characteristics extracted from high spectral resolution of Landsat images. With the advancement of object-oriented classification, monitoring of abandoned oil palm areas can be done semi-automatically with an accuracy of 92±1%. Taylor & Francis 2017 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/63592/1/Towards%20the%20use%20of%20remote-sensing%20data%20for%20monitoring%20of%20abandoned%20oil%20palm%20lands%20in%20Malaysia.pdf Yusoff, Noryusdiana Mohamad and Muharam, Farrah Melissa and Khairunniza-Bejo, Siti (2017) Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach. International Journal of Remote Sensing, 38 (2). 432 - 449. ISSN 0143-1161; ESSN: 1366-5901 https://www.tandfonline.com/doi/abs/10.1080/01431161.2016.1266111 10.1080/01431161.2016.1266111
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 Oil palm is a commercial crop that is important for its food value and as a biofuel, along with its other benefits towards the economy and human health. Currently, Malaysia cultivates approximately 5.64 million ha of oil palm. To date, a study identifying abandoned oil palm areas using satellite images is almost non-existent. Conventionally, the monitoring of abandoned oil palm lands is tedious and time consuming, especially over large areas. Hence, in this article, the capability of high resolution satellite image via Satellite Pour I’Observation de la Terre-6 (SPOT-6) products to extract abandoned oil palm areas was explored, as was the use of multi-temporal Landsat Operational Land Imager (OLI) imagery to develop the phenology of abandoned oil palm sites. Homogeneity measures derived through SPOT images played a more important role to identify abandoned oil palm than crop phenology characteristics extracted from high spectral resolution of Landsat images. With the advancement of object-oriented classification, monitoring of abandoned oil palm areas can be done semi-automatically with an accuracy of 92±1%.
format Article
author Yusoff, Noryusdiana Mohamad
Muharam, Farrah Melissa
Khairunniza-Bejo, Siti
spellingShingle Yusoff, Noryusdiana Mohamad
Muharam, Farrah Melissa
Khairunniza-Bejo, Siti
Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach
author_facet Yusoff, Noryusdiana Mohamad
Muharam, Farrah Melissa
Khairunniza-Bejo, Siti
author_sort Yusoff, Noryusdiana Mohamad
title Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach
title_short Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach
title_full Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach
title_fullStr Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach
title_full_unstemmed Towards the use of remote-sensing data for monitoring of abandoned oil palm lands in Malaysia: a semi-automatic approach
title_sort towards the use of remote-sensing data for monitoring of abandoned oil palm lands in malaysia: a semi-automatic approach
publisher Taylor & Francis
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/63592/1/Towards%20the%20use%20of%20remote-sensing%20data%20for%20monitoring%20of%20abandoned%20oil%20palm%20lands%20in%20Malaysia.pdf
http://psasir.upm.edu.my/id/eprint/63592/
https://www.tandfonline.com/doi/abs/10.1080/01431161.2016.1266111
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score 13.211869

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