Use of UK-DMC 2 and ALOS PALSAR for studying the age of oil palm trees in southern peninsular Malaysia

2013 ◽  
Vol 34 (20) ◽  
pp. 7424-7446 ◽  
Author(s):  
Kian Pang Tan ◽  
Kasturi Devi Kanniah ◽  
Arthur Philip Cracknell
Forests ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 858
Author(s):  
Nazarin Ezzaty Mohd Najib ◽  
Kasturi Devi Kanniah ◽  
Arthur P. Cracknell ◽  
Le Yu

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.


2021 ◽  
Vol 173 ◽  
pp. 95-121
Author(s):  
Juepeng Zheng ◽  
Haohuan Fu ◽  
Weijia Li ◽  
Wenzhao Wu ◽  
Le Yu ◽  
...  

Mycobiology ◽  
2015 ◽  
Vol 43 (2) ◽  
pp. 107-117 ◽  
Author(s):  
Yit Kheng Goh ◽  
Teik Khiang Goh ◽  
Nurul Fadhilah Marzuki ◽  
Hun Jiat Tung ◽  
You Keng Goh ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Soni Darmawan ◽  
Ita Carolita ◽  
Rika Hernawati ◽  
Dede Dirgahayu ◽  
Agustan ◽  
...  

Information about oil palm phenology is required for oil palm plantation management, but using spaceborne polarimetric radar imagery remains challenging. However, spaceborne polarimetric radar on X-, C-, and L-band is promising on structure vegetation and cloud area. This study investigates the scattering model of oil palm phenology based on spaceborne X-, C-, and L-band polarimetric Synthetic Aperture Radar (SAR) imaging. The X-, C-, and L-band polarimetric SAR are derived from spaceborne of TerraSAR-X, Sentinel-1A, and ALOS PALSAR 2. Study area is located in oil palm plantations, Asahan District, North Sumatra, Indonesia. The methodology includes data collection, preprocessing, radiometric calibration, speckle filtering, terrain correction, extraction of scattering value, and development of scattering model of oil palm phenology. The results showed different scattering characteristics for the X-, C-, and L-band polarimetric SAR of oil palm for age and found the potential of the scattering model for oil palm phenology based on the X-band on HH polarization that showed a nonlinear model with R 2 = 0.65 . The C-band on VH and VV polarization showed a nonlinear model with R 2 = 0.56 and R 2 = 0.89 . The L-band on HV and HH polarization showed a logarithmic model with R 2 = 0.50 and R 2 = 0.51 . In this case, the most potential of the scattering model of oil palm phenology based on R 2 is using C-band on VV polarization. However, the scattering model based on X-, C-, and L-band is potentially to be used and applied to identify the phenology of oil palm in Indonesia, which is the main parameter in yield estimation. For the future phenology model needs to improve accuracy by integrating multisensors, including different wavelengths on optical and microwave sensors and more in situ data.


MATEMATIKA ◽  
2019 ◽  
Vol 35 (1) ◽  
pp. 95-104
Author(s):  
Mohd Ismail Abd Aziz ◽  
Noryanti Nasir ◽  
Akbar Banitalebi

Successful palm oil plantation should have high returns profit, clean and environmental friendly. Since oil palm trees have a long life and it takes years to be fully grown, controlling the felling rate of the palm oil trees is a fundamental challenge. It needs to be addressed in order to maximize oil production. However, a good arrangement of the felling palm oil trees may still affect the amount of carbon absorption. The objective of this study is to develop an optimal felling model of the palm oil plantation system taking into account both oil production and carbon absorption. The model facilitates in providing the optimal control of felling rate that results in maximizing both oil production and carbon absorption. With this aim, the model is formulated considering palm oil biomass, carbon absorption rate, oil production rate and the average prices of carbon and oil palm. A set of real data is used to estimate the parameters of the model and numerical simulation is conducted to highlight the application of the proposed model. The resulting parameter estimation is solved that leads to an optimal control of felling rate problem.


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