High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests

Remote sensing is a highly effective technological tool used in sustainable natural resources management with the capability to assess large forest areas in different periods of time. These capabilities permit the development of a monitoring system for certain forestry purposes such as aboveground b...

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Main Authors: Wilson Wong, Satoshi Tsuyuki
Format: Book Chapter
Language:English
Published: Elsevier 2017
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/20030/1/High%20resolution%20of%20three.pdf
https://eprints.ums.edu.my/id/eprint/20030/
https://doi.org/10.1016/B978-0-12-805454-3.00007-4
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Institution: Universiti Malaysia Sabah
Language: English
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spelling my.ums.eprints.200302018-05-17T01:29:52Z https://eprints.ums.edu.my/id/eprint/20030/ High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests Wilson Wong Satoshi Tsuyuki SD Forestry Remote sensing is a highly effective technological tool used in sustainable natural resources management with the capability to assess large forest areas in different periods of time. These capabilities permit the development of a monitoring system for certain forestry purposes such as aboveground biomass (AGB) estimation, where regular updating is essential under the measurement, reporting, and verification (MRV) system of reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries (REDD+) scheme. The development of high-resolution three-dimensional data sets of digital photogrammetry and airborne laser scanning (ALS) have enhanced the estimation accuracy for height-related forest variables such as AGB. In this chapter, we discuss the elements of the methodology using a combination of remote sensing data sets and ground-based inventory for AGB estimation. Then, we demonstrate the capability of using aerial photographs and ALS data sets in estimating AGB from a case study conducted in the tropical montane forest environment of Northern Borneo, Malaysia. We also discuss the use of other remote sensing data for the same purpose of AGB estimation, including the potential and limitation in the context of the Southeast Asia region. In the case where there is an existing regular flight campaign of aerial photographs acquisition, it is cost-effective way using an aerial photographs data set in updating and monitoring AGB on a national or subnational scale once a detailed ALS-digital terrain model is available. The research implication of this study demonstrates the capability of using high-resolution three-dimensional data sets with a combination of a ground data set to estimate AGB for the MRV system. Elsevier 2017 Book Chapter NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/20030/1/High%20resolution%20of%20three.pdf Wilson Wong and Satoshi Tsuyuki (2017) High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests. Redefining Diversity and Dynamics of Natural Resources Management in Asia. pp. 115-130. https://doi.org/10.1016/B978-0-12-805454-3.00007-4
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
topic SD Forestry
spellingShingle SD Forestry
Wilson Wong
Satoshi Tsuyuki
High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
description Remote sensing is a highly effective technological tool used in sustainable natural resources management with the capability to assess large forest areas in different periods of time. These capabilities permit the development of a monitoring system for certain forestry purposes such as aboveground biomass (AGB) estimation, where regular updating is essential under the measurement, reporting, and verification (MRV) system of reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests, and enhancement of forest carbon stocks in developing countries (REDD+) scheme. The development of high-resolution three-dimensional data sets of digital photogrammetry and airborne laser scanning (ALS) have enhanced the estimation accuracy for height-related forest variables such as AGB. In this chapter, we discuss the elements of the methodology using a combination of remote sensing data sets and ground-based inventory for AGB estimation. Then, we demonstrate the capability of using aerial photographs and ALS data sets in estimating AGB from a case study conducted in the tropical montane forest environment of Northern Borneo, Malaysia. We also discuss the use of other remote sensing data for the same purpose of AGB estimation, including the potential and limitation in the context of the Southeast Asia region. In the case where there is an existing regular flight campaign of aerial photographs acquisition, it is cost-effective way using an aerial photographs data set in updating and monitoring AGB on a national or subnational scale once a detailed ALS-digital terrain model is available. The research implication of this study demonstrates the capability of using high-resolution three-dimensional data sets with a combination of a ground data set to estimate AGB for the MRV system.
format Book Chapter
author Wilson Wong
Satoshi Tsuyuki
author_facet Wilson Wong
Satoshi Tsuyuki
author_sort Wilson Wong
title High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
title_short High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
title_full High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
title_fullStr High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
title_full_unstemmed High resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
title_sort high resolution of three-dimensional dataset for aboveground biomass estimation in tropical rainforests
publisher Elsevier
publishDate 2017
url https://eprints.ums.edu.my/id/eprint/20030/1/High%20resolution%20of%20three.pdf
https://eprints.ums.edu.my/id/eprint/20030/
https://doi.org/10.1016/B978-0-12-805454-3.00007-4
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