Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique

Among other forest types, mangrove forest is one of the most important ecosystems. Being able to act as a “sponge” for carbon pools is one of the biological services provided by mangrove forest. Tree biomass estimates and analyses are essential for carbon accounting and other feasibility studies inc...

Full description

Saved in:

Bibliographic Details
Main Author:	Mohamed Eusop, Muhammad Ekhzarizal
Format:	Thesis
Language:	English
Published:	2017
Subjects:	Mangrove forests - Malaysia - Perak Remote sensing
Online Access:	http://psasir.upm.edu.my/id/eprint/70903/1/FH%202017%2011%20IR.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-upm-ir.70903
record_format	uketd_dc
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Mangrove forests - Malaysia - Perak Remote sensing
spellingShingle	Mangrove forests - Malaysia - Perak Remote sensing Mohamed Eusop, Muhammad Ekhzarizal Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique
description	Among other forest types, mangrove forest is one of the most important ecosystems. Being able to act as a “sponge” for carbon pools is one of the biological services provided by mangrove forest. Tree biomass estimates and analyses are essential for carbon accounting and other feasibility studies including bioenergy. Mangrove plays an important role in ecosystems which could mitigate the climate change through biomass and carbon storage. Due to concerns on global climate change and carbon sequestration a reasonable method for estimating tree biomass and carbon stocks are highly demanded. Thus, this study was design to estimate the aboveground biomass (AGB) of mangrove trees using allometry model and remote sensing technique. A total of 150 plots from 17 compartments were sampled in 2014. Based on remote sensing technique, SPOT-5 data were used to estimate and mapping aboveground biomass and carbon stocks. Four types of vegetation indices (VI’s) were selected and tested in this study. The estimation of AGB was further refined using integration analysis from direct method data. To achieve the objective of this study, optical image and sampling data had been processed and analysed, and validated by using regression model. By using non-destructive method and allometry model, the results shown that average AGB per plot was about 168.93 ton ha-1. The maximum value was 462.40 ton ha-1 and the minimum was 24.35 ton ha-1 respectively. While average value of carbon storage was 84.47 tonC ha-1. Then, exponential regression model had performed to estimate the AGB along with optical image. The findings demonstrate a good relationship between measured AGB and selected vegetation indices (NDVI and GEMI-NDVI). The others two like SAVI and GNDVI had proved weak relationship with measured AGB. However, the results indicate that there were slightly increase for about 3% with the using multi-exponential regression analysis. Study had further refined by using multi-exponential of integration method from incorporating both predicted NDVI and GEMI-NDVI with coefficient of determination (R2 = 0.74) which had proved that the increment of 1% compared with multi-exponential of direct method and the overall result for RMS error was 85.24 ton ha-1. This shows that the average estimation of AGB was 130.36 ton ha-1. Therefore, total amount of AGB for the whole study area in Kuala Sepetang (South) (9,884 ha) approximately of 1.3 million tonnes. The amount of AGB was 1.80% slightly overestimated compared with previous study by using destructive sampling. Thus, the studies had suggested that the non-destructive sampling by using common allometric equation is still effective and reasonable to be used for the estimation on AGB in mangroves forest. The correlation and regression analysis were done separately between AGB and vegetation indices by using direct method and integration method. Results had shown that the multi-exponential integration method is highly in accuracy and strongly correlated with the field data among the others correlation. In conclusion, the study indicates that the common allometric equation for calculating AGB was applicable for all mangrove species instead of species-specific equation. With the using of remote sensing technique and multi-exponential integration analysis, the estimated biomass and carbon stocks were slightly increased for about 1%. The regression model developed may be useful for estimating the AGB of areas that are not reachable and in low cost. The study using satellite imagery data was an attempt to improve the estimates by integration method as a final outcome for better conversion of biomass to carbon stock content.
format	Thesis
qualification_level	Master's degree
author	Mohamed Eusop, Muhammad Ekhzarizal
author_facet	Mohamed Eusop, Muhammad Ekhzarizal
author_sort	Mohamed Eusop, Muhammad Ekhzarizal
title	Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique
title_short	Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique
title_full	Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique
title_fullStr	Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique
title_full_unstemmed	Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique
title_sort	estimation of aboveground biomass and carbon stocks in matang mangrove forest reserve using allometry model and remote sensing technique
granting_institution	Universiti Putra Malaysia
publishDate	2017
url	http://psasir.upm.edu.my/id/eprint/70903/1/FH%202017%2011%20IR.pdf
_version_	1747812932717117440
spelling	my-upm-ir.709032019-08-29T07:19:02Z Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique 2017-07 Mohamed Eusop, Muhammad Ekhzarizal Among other forest types, mangrove forest is one of the most important ecosystems. Being able to act as a “sponge” for carbon pools is one of the biological services provided by mangrove forest. Tree biomass estimates and analyses are essential for carbon accounting and other feasibility studies including bioenergy. Mangrove plays an important role in ecosystems which could mitigate the climate change through biomass and carbon storage. Due to concerns on global climate change and carbon sequestration a reasonable method for estimating tree biomass and carbon stocks are highly demanded. Thus, this study was design to estimate the aboveground biomass (AGB) of mangrove trees using allometry model and remote sensing technique. A total of 150 plots from 17 compartments were sampled in 2014. Based on remote sensing technique, SPOT-5 data were used to estimate and mapping aboveground biomass and carbon stocks. Four types of vegetation indices (VI’s) were selected and tested in this study. The estimation of AGB was further refined using integration analysis from direct method data. To achieve the objective of this study, optical image and sampling data had been processed and analysed, and validated by using regression model. By using non-destructive method and allometry model, the results shown that average AGB per plot was about 168.93 ton ha-1. The maximum value was 462.40 ton ha-1 and the minimum was 24.35 ton ha-1 respectively. While average value of carbon storage was 84.47 tonC ha-1. Then, exponential regression model had performed to estimate the AGB along with optical image. The findings demonstrate a good relationship between measured AGB and selected vegetation indices (NDVI and GEMI-NDVI). The others two like SAVI and GNDVI had proved weak relationship with measured AGB. However, the results indicate that there were slightly increase for about 3% with the using multi-exponential regression analysis. Study had further refined by using multi-exponential of integration method from incorporating both predicted NDVI and GEMI-NDVI with coefficient of determination (R2 = 0.74) which had proved that the increment of 1% compared with multi-exponential of direct method and the overall result for RMS error was 85.24 ton ha-1. This shows that the average estimation of AGB was 130.36 ton ha-1. Therefore, total amount of AGB for the whole study area in Kuala Sepetang (South) (9,884 ha) approximately of 1.3 million tonnes. The amount of AGB was 1.80% slightly overestimated compared with previous study by using destructive sampling. Thus, the studies had suggested that the non-destructive sampling by using common allometric equation is still effective and reasonable to be used for the estimation on AGB in mangroves forest. The correlation and regression analysis were done separately between AGB and vegetation indices by using direct method and integration method. Results had shown that the multi-exponential integration method is highly in accuracy and strongly correlated with the field data among the others correlation. In conclusion, the study indicates that the common allometric equation for calculating AGB was applicable for all mangrove species instead of species-specific equation. With the using of remote sensing technique and multi-exponential integration analysis, the estimated biomass and carbon stocks were slightly increased for about 1%. The regression model developed may be useful for estimating the AGB of areas that are not reachable and in low cost. The study using satellite imagery data was an attempt to improve the estimates by integration method as a final outcome for better conversion of biomass to carbon stock content. Mangrove forests - Malaysia - Perak Remote sensing 2017-07 Thesis http://psasir.upm.edu.my/id/eprint/70903/ http://psasir.upm.edu.my/id/eprint/70903/1/FH%202017%2011%20IR.pdf text en public masters Universiti Putra Malaysia Mangrove forests - Malaysia - Perak Remote sensing

Estimation of aboveground biomass and carbon stocks in Matang Mangrove Forest Reserve using allometry model and remote sensing technique

Similar Items