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Synergy of Active and Passive Remote Sensing Data for Effective Mapping of Oil Palm Plantation in Malaysia

Oil palm is recognized as a golden crop, as it produces the highest oil yield among oil seed crops. Malaysia is the world’s second largest producer of palm oil; 16% of its land is planted with oil palm. To cope with the ever-increasing global demand on edible oil, additional areas of oil palm are fo...

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Published in:Forests 2020-08, Vol.11 (8), p.858
Main Authors: Mohd Najib, Nazarin Ezzaty, Kanniah, Kasturi Devi, Cracknell, Arthur P., Yu, Le
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description Oil palm is recognized as a golden crop, as it produces the highest oil yield among oil seed crops. Malaysia is the world’s second largest producer of palm oil; 16% of its land is planted with oil palm. To cope with the ever-increasing global demand on edible oil, additional areas of oil palm are forecast to increase globally by 12 to 19 Mha by 2050. Multisensor remote sensing plays an important role in providing relevant, timely, and accurate information that can be developed into a plantation monitoring system to optimize production and sustainability. The aim of this study was to simultaneously exploit the synthetic aperture radar ALOS PALSAR 2, a form of microwave remote sensing, in combination with visible (red) data from Landsat Thematic Mapper to obtain a holistic view of a plantation. A manipulation of the horizontal–horizontal (HH) and horizontal–vertical (HV) polarizations of ALOS PALSAR data detected oil palm trees and water bodies, while the red spectra L-band from Landsat data (optical) could effectively identify built up areas and vertical–horizontal (VH) polarization from Sentinel C-band data detected bare land. These techniques produced an oil palm area classification with overall accuracies of 98.36% and 0.78 kappa coefficient for Peninsular Malaysia. The total oil palm area in Peninsular Malaysia was estimated to be about 3.48% higher than the value reported by the Malaysian Palm Oil Board. The over estimation may be due the MPOB’s statistics that do not include unregistered small holder oil palm plantations. In this study, we were able to discriminate most of the rubber areas.
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identifier ISSN: 1999-4907
ispartof Forests, 2020-08, Vol.11 (8), p.858
issn 1999-4907
1999-4907
language eng
recordid cdi_proquest_journals_2432337211
source Publicly Available Content (ProQuest)
subjects Accuracy
Area classification
Biomass
C band
Classification
Climate change
Crop yield
Datasets
Detection
Dielectric properties
Economic forecasting
Edible oils
Horizontal polarization
Landsat
Landsat satellites
Mapping
Oil
Oil palm trees
Oilseeds
Palm oil
Plantations
Remote sensing
Seed crops
Studies
Sustainability
Synthetic aperture radar
Topography
Vegetable oils
Vegetation
Vertical polarization
title Synergy of Active and Passive Remote Sensing Data for Effective Mapping of Oil Palm Plantation in Malaysia
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