Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing

Ecosystem Integrity Index (EII) is a concept to determine the quality or the health of an ecosystem. The EII development can assist forest managers and decision makers in the conservation effort and forest management in Malaysia through the development of a simple and easy-to-adopt index. The aim of...

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Main Author:	Abdul Razak, Muhammad Azmil
Format:	Thesis
Language:	English English English
Published:	2021
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/1145/1/24p%20MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK.pdf http://eprints.uthm.edu.my/1145/2/MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1145/3/MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK%20WATERMARK.pdf
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spelling	my-uthm-ep.11452021-08-22T08:41:24Z Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing 2021-03 Abdul Razak, Muhammad Azmil T Technology (General) Ecosystem Integrity Index (EII) is a concept to determine the quality or the health of an ecosystem. The EII development can assist forest managers and decision makers in the conservation effort and forest management in Malaysia through the development of a simple and easy-to-adopt index. The aim of this study is to assess and evaluate the EII through the development of forest structure empirical models from remotely sensed data for lowland dipterocarp forest in Malaysia. The objectives of this study are: (i) to assess the structure and composition of lowland dipterocarp forest in Malaysia, (ii) to develop empirical model for estimating stand structure from remotely sensed data, and (iii) to derive the ecosystem integrity index for lowland dipterocarp forest. Tree Basal Area (BA), aboveground biomass (AGB) and volume plot from plot data were used as dependent variables, while remote sensing data from Landsat, Pleiades and LiDAR were used as independent variables for model development. Tree plot census was carried out from 17 to 19 May 2016, while remote sensing data acquisition dates for Landsat, Pleiades and LiDAR were 13 March 2016, 24 January 2015 and April 2015 respectively. Forest Structure Modeling was carried out by means of a correlation analysis with the calibration of dependent and independent data to select the most significant and accurate remote sensing variables to derive empiric equation (model), fitting stage to select the best model with the highest coefficient of determination (R2) and the lowest root mean square error ( RMSE) validation of the final selected. The Ecosystem Integrity Index was developed by the average percentage of the predicted BA, AGB and model volume. The EII was categorised at five integrity levels as high (81–100%), medium high (61–80%), moderate (41–60%), medium low (21–40%) and low (0–20%). A total of 1035 trees with diameter at breast height (DBH) of 5.0 cm and above were recorded in 69.115 ha sampling areas. The total trees recorded represented 150 species from 87 genera and 34 families. Shorea macroptera (Dipterocarpaceae), S. leprosula (Dipterocarpaceae) and S. parviflora (Dipterocarpaceae) are three dominant species, with Species Important Value Index (SIVi) of 6.49%, 6.23% and 5.51%, respectively. Dipterocarpaceae is the most dominant with Family Important Value Index (FIVi) of 33.54%. The developed final model is robust and consistent with high R2 with range of 0.84 to 0.87. The final models constructed for AGB, BA and volume value of R2 are 0.85, 0.84 and 0.87 respectively. The RMSE of AGB, BA and volume model are 53.1 Mg/ha, 3.54 m2/ha and 46.4 m3/ha, respectively. The overall stand AGB, BA and volume for Sungai Menyala Forest Reserve is 282.29 Mg/ha, 17.68 m2/ha and 239.51 m3/ha. An Ecosystem Integrity Index (EII) assessment has been successfully demonstrated by this study with production of practical, multi-scaled, flexible, adjustable and policy-relevant index. The overall EII of Sungai Menyala Forest Reserve is in Category 3, which shows that the area is within the medium value. 2021-03 Thesis http://eprints.uthm.edu.my/1145/ http://eprints.uthm.edu.my/1145/1/24p%20MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK.pdf text en public http://eprints.uthm.edu.my/1145/2/MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/1145/3/MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Faculty of Applied Science and Technology
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	T Technology (General)
spellingShingle	T Technology (General) Abdul Razak, Muhammad Azmil Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
description	Ecosystem Integrity Index (EII) is a concept to determine the quality or the health of an ecosystem. The EII development can assist forest managers and decision makers in the conservation effort and forest management in Malaysia through the development of a simple and easy-to-adopt index. The aim of this study is to assess and evaluate the EII through the development of forest structure empirical models from remotely sensed data for lowland dipterocarp forest in Malaysia. The objectives of this study are: (i) to assess the structure and composition of lowland dipterocarp forest in Malaysia, (ii) to develop empirical model for estimating stand structure from remotely sensed data, and (iii) to derive the ecosystem integrity index for lowland dipterocarp forest. Tree Basal Area (BA), aboveground biomass (AGB) and volume plot from plot data were used as dependent variables, while remote sensing data from Landsat, Pleiades and LiDAR were used as independent variables for model development. Tree plot census was carried out from 17 to 19 May 2016, while remote sensing data acquisition dates for Landsat, Pleiades and LiDAR were 13 March 2016, 24 January 2015 and April 2015 respectively. Forest Structure Modeling was carried out by means of a correlation analysis with the calibration of dependent and independent data to select the most significant and accurate remote sensing variables to derive empiric equation (model), fitting stage to select the best model with the highest coefficient of determination (R2) and the lowest root mean square error ( RMSE) validation of the final selected. The Ecosystem Integrity Index was developed by the average percentage of the predicted BA, AGB and model volume. The EII was categorised at five integrity levels as high (81–100%), medium high (61–80%), moderate (41–60%), medium low (21–40%) and low (0–20%). A total of 1035 trees with diameter at breast height (DBH) of 5.0 cm and above were recorded in 69.115 ha sampling areas. The total trees recorded represented 150 species from 87 genera and 34 families. Shorea macroptera (Dipterocarpaceae), S. leprosula (Dipterocarpaceae) and S. parviflora (Dipterocarpaceae) are three dominant species, with Species Important Value Index (SIVi) of 6.49%, 6.23% and 5.51%, respectively. Dipterocarpaceae is the most dominant with Family Important Value Index (FIVi) of 33.54%. The developed final model is robust and consistent with high R2 with range of 0.84 to 0.87. The final models constructed for AGB, BA and volume value of R2 are 0.85, 0.84 and 0.87 respectively. The RMSE of AGB, BA and volume model are 53.1 Mg/ha, 3.54 m2/ha and 46.4 m3/ha, respectively. The overall stand AGB, BA and volume for Sungai Menyala Forest Reserve is 282.29 Mg/ha, 17.68 m2/ha and 239.51 m3/ha. An Ecosystem Integrity Index (EII) assessment has been successfully demonstrated by this study with production of practical, multi-scaled, flexible, adjustable and policy-relevant index. The overall EII of Sungai Menyala Forest Reserve is in Category 3, which shows that the area is within the medium value.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abdul Razak, Muhammad Azmil
author_facet	Abdul Razak, Muhammad Azmil
author_sort	Abdul Razak, Muhammad Azmil
title	Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
title_short	Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
title_full	Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
title_fullStr	Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
title_full_unstemmed	Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
title_sort	assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Faculty of Applied Science and Technology
publishDate	2021
url	http://eprints.uthm.edu.my/1145/1/24p%20MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK.pdf http://eprints.uthm.edu.my/1145/2/MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1145/3/MUHAMMAD%20AZMIL%20BIN%20ABDUL%20RAZAK%20WATERMARK.pdf
_version_	1747830744933203968

Assessment of ecosystem integrity of lowland dipterocarp forest ecosystem using remote sensing

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