Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques

Tropical forest has been recognized as mostly disturbed natural land cover which contribute to deprived ecological balance. Malaysia is one of the primary exports of palm oil and timber in Southeast Asia. Hence, the objectives of this research mainly to evaluate the deforestation activity and pr...

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Main Author:	Othman, Mohamad Al-Ekhwan
Format:	Thesis
Language:	English
Published:	2019
Subjects:	Deforestation - Malaysia - Southeast Pahang Forest management - Malaysia - Southeast Pahang Land use - Environmental aspects
Online Access:	http://psasir.upm.edu.my/id/eprint/105542/1/MOHAMAD%20AL-EKHWAN%20-%20IR.pdf
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spelling	my-upm-ir.1055422024-02-05T00:37:17Z Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques 2019-11 Othman, Mohamad Al-Ekhwan Tropical forest has been recognized as mostly disturbed natural land cover which contribute to deprived ecological balance. Malaysia is one of the primary exports of palm oil and timber in Southeast Asia. Hence, the objectives of this research mainly to evaluate the deforestation activity and predict the future extent of forest land in the highly deforested area in Pahang. These could be achieved through; (1) assessing the deforestation dynamics in Southeast Pahang using remote sensing, and (2) predicting the future spatio-temporal deforestation using CA-Markov model for year 2025 and 2035. The most critical issue is that forest land are usually inaccessible, therefore, remote sensing (RS) and Geographical Information System (GIS) are the important tools and recent approach for forest cover monitoring. The imageries from Landsat 5TM and 8 OLI satellite platforms were retrieved and categorized into four types of land cover including forest, nonforest vegetation, openland/ built-up, and waterbodies using Maximum Likelihood Classification (MLC). In addition, contour data was utilised to produce the elevation and slope maps, while Euclidean Distance analysis were applied to city centre, and Permanent Reserved Forest (PRF) for proximity maps. The overall accuracies are ranging from 83.7%, 80.9%, 85.6%, and 84.4% with Kappa value of 0.65, 0.65, 0.74, and 0.74 for 1990, 2000, 2010, and 2017 respectively. The results from land change analysis show that state land had changed from 42% of total forest area in 1990 to 21% in 2017 with a steady negative change over time. Dipterocarp reserved forest are consistently exploited for timber extraction, but the forest covers are able to be regenerated after more than 20 years from sustainable management practices. The distance to population centre has a positive relationship with deforestation, and the protected area have a clear restriction on deforestation in the area because forest loss inside protection region only happen after 20 years of study period compared to the outside of protected region. Furthermore, elevation and slope have similar effects on deforestation where the increase in their value will reduce the risk for deforestation. For land cover prediction, Markov chain integrated with cellular automata model were used for future forest land cover forecasting. The model calibrations achieved up to 62% accuracy for land cover prediction. The CA-Markov model prediction for year 2025 and 2035 suggests that the forest land cover will continuously reduce with 13 to 24 km2/year rate. Generally, state lands provide the highest level of deforestation in Rompin and Pekan district in both dipterocarp and peat swamp type, conversely the reserved forest in peat area are more protected compare to dipterocarp type. The comparison between using multiple and binary land cover as input suggest that the traditional CA-Markov model can simulate better when dealing with binary land cover. Other than that, the deforestation might be more than what were predicted in this study based on the standard error of the model. Deforestation - Malaysia - Southeast Pahang Forest management - Malaysia - Southeast Pahang Land use - Environmental aspects 2019-11 Thesis http://psasir.upm.edu.my/id/eprint/105542/ http://psasir.upm.edu.my/id/eprint/105542/1/MOHAMAD%20AL-EKHWAN%20-%20IR.pdf text en public masters Universiti Putra Malaysia Deforestation - Malaysia - Southeast Pahang Forest management - Malaysia - Southeast Pahang Land use - Environmental aspects Ash’aari, Zulfa Hanan
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Ash’aari, Zulfa Hanan
topic	Deforestation - Malaysia - Southeast Pahang Forest management - Malaysia - Southeast Pahang Land use - Environmental aspects
spellingShingle	Deforestation - Malaysia - Southeast Pahang Forest management - Malaysia - Southeast Pahang Land use - Environmental aspects Othman, Mohamad Al-Ekhwan Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques
description	Tropical forest has been recognized as mostly disturbed natural land cover which contribute to deprived ecological balance. Malaysia is one of the primary exports of palm oil and timber in Southeast Asia. Hence, the objectives of this research mainly to evaluate the deforestation activity and predict the future extent of forest land in the highly deforested area in Pahang. These could be achieved through; (1) assessing the deforestation dynamics in Southeast Pahang using remote sensing, and (2) predicting the future spatio-temporal deforestation using CA-Markov model for year 2025 and 2035. The most critical issue is that forest land are usually inaccessible, therefore, remote sensing (RS) and Geographical Information System (GIS) are the important tools and recent approach for forest cover monitoring. The imageries from Landsat 5TM and 8 OLI satellite platforms were retrieved and categorized into four types of land cover including forest, nonforest vegetation, openland/ built-up, and waterbodies using Maximum Likelihood Classification (MLC). In addition, contour data was utilised to produce the elevation and slope maps, while Euclidean Distance analysis were applied to city centre, and Permanent Reserved Forest (PRF) for proximity maps. The overall accuracies are ranging from 83.7%, 80.9%, 85.6%, and 84.4% with Kappa value of 0.65, 0.65, 0.74, and 0.74 for 1990, 2000, 2010, and 2017 respectively. The results from land change analysis show that state land had changed from 42% of total forest area in 1990 to 21% in 2017 with a steady negative change over time. Dipterocarp reserved forest are consistently exploited for timber extraction, but the forest covers are able to be regenerated after more than 20 years from sustainable management practices. The distance to population centre has a positive relationship with deforestation, and the protected area have a clear restriction on deforestation in the area because forest loss inside protection region only happen after 20 years of study period compared to the outside of protected region. Furthermore, elevation and slope have similar effects on deforestation where the increase in their value will reduce the risk for deforestation. For land cover prediction, Markov chain integrated with cellular automata model were used for future forest land cover forecasting. The model calibrations achieved up to 62% accuracy for land cover prediction. The CA-Markov model prediction for year 2025 and 2035 suggests that the forest land cover will continuously reduce with 13 to 24 km2/year rate. Generally, state lands provide the highest level of deforestation in Rompin and Pekan district in both dipterocarp and peat swamp type, conversely the reserved forest in peat area are more protected compare to dipterocarp type. The comparison between using multiple and binary land cover as input suggest that the traditional CA-Markov model can simulate better when dealing with binary land cover. Other than that, the deforestation might be more than what were predicted in this study based on the standard error of the model.
format	Thesis
qualification_level	Master's degree
author	Othman, Mohamad Al-Ekhwan
author_facet	Othman, Mohamad Al-Ekhwan
author_sort	Othman, Mohamad Al-Ekhwan
title	Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques
title_short	Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques
title_full	Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques
title_fullStr	Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques
title_full_unstemmed	Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques
title_sort	assessment of forest land change in southeast pahang, malaysia using remote sensing techniques
granting_institution	Universiti Putra Malaysia
publishDate	2019
url	http://psasir.upm.edu.my/id/eprint/105542/1/MOHAMAD%20AL-EKHWAN%20-%20IR.pdf
_version_	1794018908087255040

Assessment of forest land change in southeast Pahang, Malaysia using remote sensing techniques

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