Modelling aboveground biomass of oil palm using destructive method and remote sensing data

Biomass serves as an important indicator to assess the role of oil palm in the global carbon cycle, particularly its contribution towards carbon sequestration. Indonesia is a country that has the largest palm oil plantation, and is the second largest country to export CPO (Crude Palm Oil) after Mala...

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Main Author:	Sunaryathy, Putri Ida
Format:	Thesis
Language:	English
Published:	2016
Subjects:	G70.39-70.6 Remote sensing
Online Access:	http://eprints.utm.my/id/eprint/79017/1/PutriIdaSunaryathyPFGHT2016.pdf
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spelling	my-utm-ep.790172018-09-27T04:14:29Z Modelling aboveground biomass of oil palm using destructive method and remote sensing data 2016-09 Sunaryathy, Putri Ida G70.39-70.6 Remote sensing Biomass serves as an important indicator to assess the role of oil palm in the global carbon cycle, particularly its contribution towards carbon sequestration. Indonesia is a country that has the largest palm oil plantation, and is the second largest country to export CPO (Crude Palm Oil) after Malaysia. As the world market demand for palm oil increases, Indonesia is developing large oil palm plantations. However, information about biomass or carbon stocks contained in oil palm trees is still limited. The study quantified the aboveground biomass (AGB) of oil palm trees in South Sulawesi, Indonesia using harvesting method, allometric equations and remote sensing techniques. Nine oil palm trees ranging from three trees o f young (1- 3 years), three trees of intermediate (4-10 years) and three trees of matured (11-20 years) trees were harvested, their wet and dry biomass for different components from the stems, fronds, leaflets, fruit bunches as well as flowers were obtained. In addition, 96 trees were also sampled to get Diameters o f Breast Height (DBH), height and age information. All the information were used to develop specific allometric equations to estimate dry aboveground biomass of young, intermediate and matured oil palm trees. The use o f allometric models resulted in high accuracy when AGB estimated from the equations was compared with DBH and height. Since harvesting method and allometric equations can only be used to get AGB at local (plot) scale, remote sensing data o f Advanced Land Observing Satellite Phase Array type L-band Synthetic Aperture Radar/ALOS PALSAR were used to up-scale AGB to the entire study area. Dry AGB obtained from the harvesting method was 0.75 t ha'1, 22.17 t ha’1 and 105.41 t ha’1 for young, intermediate and matured trees respectively. The allometric equations with dbh parameter produced 0.71 t h a '1, 20.15 t ha'1, 107.41 t h a '1, and dbh with height parameters have produced 1.40 t h a'1, 27.20 t ha'1, 248.52 t ha' 1 for young, intermediate and matured trees respectively. Manipulation of HH polarization, (HH + HV)/2 and ^/(HHxHV) produced better correlation with AGB (R2 between 0.53 to 0.61). Empirical models developed with these manipulation polarizations were used to estimate the AGB in South Sulawesi. Total AGBs of the area for intermediate trees ranged between 29.94 t ha’1 to 31.51 t ha’1 whereas it was between 68.32 t ha' 1 to 71.29 t ha' 1 for matured oil palm trees. AGB estimate from ALOS PALSAR showed a 24.5 to 28 percent difference in comparison to AGB obtained via allometric equations for intermediate and matured palms. The results (AGB) obtained in this study have a potential to inform decision makers to impose better land management in oil palm plantation so to alleviate climate change. 2016-09 Thesis http://eprints.utm.my/id/eprint/79017/ http://eprints.utm.my/id/eprint/79017/1/PutriIdaSunaryathyPFGHT2016.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106914 phd doctoral Universiti Teknologi Malaysia, Faculty of Geoinformation and real estate Faculty of Geoinformation and real estate
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	G70.39-70.6 Remote sensing
spellingShingle	G70.39-70.6 Remote sensing Sunaryathy, Putri Ida Modelling aboveground biomass of oil palm using destructive method and remote sensing data
description	Biomass serves as an important indicator to assess the role of oil palm in the global carbon cycle, particularly its contribution towards carbon sequestration. Indonesia is a country that has the largest palm oil plantation, and is the second largest country to export CPO (Crude Palm Oil) after Malaysia. As the world market demand for palm oil increases, Indonesia is developing large oil palm plantations. However, information about biomass or carbon stocks contained in oil palm trees is still limited. The study quantified the aboveground biomass (AGB) of oil palm trees in South Sulawesi, Indonesia using harvesting method, allometric equations and remote sensing techniques. Nine oil palm trees ranging from three trees o f young (1- 3 years), three trees of intermediate (4-10 years) and three trees of matured (11-20 years) trees were harvested, their wet and dry biomass for different components from the stems, fronds, leaflets, fruit bunches as well as flowers were obtained. In addition, 96 trees were also sampled to get Diameters o f Breast Height (DBH), height and age information. All the information were used to develop specific allometric equations to estimate dry aboveground biomass of young, intermediate and matured oil palm trees. The use o f allometric models resulted in high accuracy when AGB estimated from the equations was compared with DBH and height. Since harvesting method and allometric equations can only be used to get AGB at local (plot) scale, remote sensing data o f Advanced Land Observing Satellite Phase Array type L-band Synthetic Aperture Radar/ALOS PALSAR were used to up-scale AGB to the entire study area. Dry AGB obtained from the harvesting method was 0.75 t ha'1, 22.17 t ha’1 and 105.41 t ha’1 for young, intermediate and matured trees respectively. The allometric equations with dbh parameter produced 0.71 t h a '1, 20.15 t ha'1, 107.41 t h a '1, and dbh with height parameters have produced 1.40 t h a'1, 27.20 t ha'1, 248.52 t ha' 1 for young, intermediate and matured trees respectively. Manipulation of HH polarization, (HH + HV)/2 and ^/(HHxHV) produced better correlation with AGB (R2 between 0.53 to 0.61). Empirical models developed with these manipulation polarizations were used to estimate the AGB in South Sulawesi. Total AGBs of the area for intermediate trees ranged between 29.94 t ha’1 to 31.51 t ha’1 whereas it was between 68.32 t ha' 1 to 71.29 t ha' 1 for matured oil palm trees. AGB estimate from ALOS PALSAR showed a 24.5 to 28 percent difference in comparison to AGB obtained via allometric equations for intermediate and matured palms. The results (AGB) obtained in this study have a potential to inform decision makers to impose better land management in oil palm plantation so to alleviate climate change.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Sunaryathy, Putri Ida
author_facet	Sunaryathy, Putri Ida
author_sort	Sunaryathy, Putri Ida
title	Modelling aboveground biomass of oil palm using destructive method and remote sensing data
title_short	Modelling aboveground biomass of oil palm using destructive method and remote sensing data
title_full	Modelling aboveground biomass of oil palm using destructive method and remote sensing data
title_fullStr	Modelling aboveground biomass of oil palm using destructive method and remote sensing data
title_full_unstemmed	Modelling aboveground biomass of oil palm using destructive method and remote sensing data
title_sort	modelling aboveground biomass of oil palm using destructive method and remote sensing data
granting_institution	Universiti Teknologi Malaysia, Faculty of Geoinformation and real estate
granting_department	Faculty of Geoinformation and real estate
publishDate	2016
url	http://eprints.utm.my/id/eprint/79017/1/PutriIdaSunaryathyPFGHT2016.pdf
_version_	1747818126724038656

Modelling aboveground biomass of oil palm using destructive method and remote sensing data

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