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

TitleMapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data
Authors
Issue Date2018
Citation
International Journal of Remote Sensing, 2018, v. 39, n. 2, p. 432-452 How to Cite?
Abstract© 2017 Informa UK Limited, trading as Taylor and Francis Group. 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).
Persistent Identifierhttp://hdl.handle.net/10722/296856
ISSN
2023 Impact Factor: 3.0
2023 SCImago Journal Rankings: 0.776
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCheng, Yuqi-
dc.contributor.authorYu, Le-
dc.contributor.authorXu, Yidi-
dc.contributor.authorLu, Hui-
dc.contributor.authorCracknell, Arthur P.-
dc.contributor.authorKanniah, Kasturi-
dc.contributor.authorGong, Peng-
dc.date.accessioned2021-02-25T15:16:49Z-
dc.date.available2021-02-25T15:16:49Z-
dc.date.issued2018-
dc.identifier.citationInternational Journal of Remote Sensing, 2018, v. 39, n. 2, p. 432-452-
dc.identifier.issn0143-1161-
dc.identifier.urihttp://hdl.handle.net/10722/296856-
dc.description.abstract© 2017 Informa UK Limited, trading as Taylor and Francis Group. 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).-
dc.languageeng-
dc.relation.ispartofInternational Journal of Remote Sensing-
dc.titleMapping oil palm extent in Malaysia using ALOS-2 PALSAR-2 data-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/01431161.2017.1387309-
dc.identifier.scopuseid_2-s2.0-85050564954-
dc.identifier.volume39-
dc.identifier.issue2-
dc.identifier.spage432-
dc.identifier.epage452-
dc.identifier.eissn1366-5901-
dc.identifier.isiWOS:000416848600008-
dc.identifier.issnl0143-1161-

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