Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data

The extent of oil palm plantations has increased rapidly in Malaysia over the past few decades. To evaluate ecological effects and economic values, it is important to produce an accurate oil palm map for Malaysia. The Phased Array Type L-band Synthetic Aperture Radar (PALSAR) on the Advance Land Obs...

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Main Authors: Cheng, Yuqi, Le, Yu, Xu, Yidi, Lu, Hui, Cracknell, Arthur P., Kanniah, Kasturi Devi, Gong, Peng
Format: Article
Published: Taylor and Francis Inc. 2018
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Online Access:http://eprints.utm.my/id/eprint/84686/
http://dx.doi.org/10.1080/01431161.2017.1387309
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spelling my.utm.846862020-02-27T04:52:48Z http://eprints.utm.my/id/eprint/84686/ Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data Cheng, Yuqi Le, Yu Xu, Yidi Lu, Hui Cracknell, Arthur P. Kanniah, Kasturi Devi Gong, Peng HD1394-1394.5 Real estate management The extent of oil palm plantations has increased rapidly in Malaysia over the past few decades. To evaluate ecological effects and economic values, it is important to produce an accurate oil palm map for Malaysia. The Phased Array Type L-band Synthetic Aperture Radar (PALSAR) on the Advance Land Observing Satellite (ALOS) is useful in land-cover mapping in tropical regions under all-weather conditions. In this study, PALSAR-2 images from 2015 were used for oil palm mapping with maximum likelihood classifier (MLC)-based supervised classification. The processed PALSAR-2 data were resampled to multiple coarser resolutions (50, 100, 250, 500, and 1000 m), and then used to investigate the effect of speckle in oil palm mapping. Both independent testing samples and inventories from the Malaysia Palm Oil Board (MPOB) were used to evaluate the mapping accuracy. The oil palm mapping result indicates 50—500 m to be a good resolution for either retaining spatial details or reducing speckle noise of PALSAR-2 images. Among which, the best overall mapping accuracies and average oil palm accuracies reached 94.50% and 89.78%, respectively. Moreover, the oil palm area derived from the 100-m resolution map is 6.14 million hectares (Mha), which is the closest to the official MPOB inventories (~8.87% overestimation). Taylor and Francis Inc. 2018-01 Article PeerReviewed Cheng, Yuqi and Le, Yu and Xu, Yidi and Lu, Hui and Cracknell, Arthur P. and Kanniah, Kasturi Devi and Gong, Peng (2018) Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data. International Journal of Remote Sensing, 39 (2). pp. 432-452. ISSN 0143-1161 http://dx.doi.org/10.1080/01431161.2017.1387309
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 HD1394-1394.5 Real estate management
spellingShingle HD1394-1394.5 Real estate management
Cheng, Yuqi
Le, Yu
Xu, Yidi
Lu, Hui
Cracknell, Arthur P.
Kanniah, Kasturi Devi
Gong, Peng
Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
description The extent of oil palm plantations has increased rapidly in Malaysia over the past few decades. To evaluate ecological effects and economic values, it is important to produce an accurate oil palm map for Malaysia. The Phased Array Type L-band Synthetic Aperture Radar (PALSAR) on the Advance Land Observing Satellite (ALOS) is useful in land-cover mapping in tropical regions under all-weather conditions. In this study, PALSAR-2 images from 2015 were used for oil palm mapping with maximum likelihood classifier (MLC)-based supervised classification. The processed PALSAR-2 data were resampled to multiple coarser resolutions (50, 100, 250, 500, and 1000 m), and then used to investigate the effect of speckle in oil palm mapping. Both independent testing samples and inventories from the Malaysia Palm Oil Board (MPOB) were used to evaluate the mapping accuracy. The oil palm mapping result indicates 50—500 m to be a good resolution for either retaining spatial details or reducing speckle noise of PALSAR-2 images. Among which, the best overall mapping accuracies and average oil palm accuracies reached 94.50% and 89.78%, respectively. Moreover, the oil palm area derived from the 100-m resolution map is 6.14 million hectares (Mha), which is the closest to the official MPOB inventories (~8.87% overestimation).
format Article
author Cheng, Yuqi
Le, Yu
Xu, Yidi
Lu, Hui
Cracknell, Arthur P.
Kanniah, Kasturi Devi
Gong, Peng
author_facet Cheng, Yuqi
Le, Yu
Xu, Yidi
Lu, Hui
Cracknell, Arthur P.
Kanniah, Kasturi Devi
Gong, Peng
author_sort Cheng, Yuqi
title Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
title_short Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
title_full Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
title_fullStr Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
title_full_unstemmed Mapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
title_sort mapping oil palm extent in malaysia using alos-2 palsar-2 data
publisher Taylor and Francis Inc.
publishDate 2018
url http://eprints.utm.my/id/eprint/84686/
http://dx.doi.org/10.1080/01431161.2017.1387309
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