Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia

Ojoatre Sadadi, Y.A. Hussin, H. Kloosterman, Mohd Hasmadi Ismail

Research output: Contribution to conferencePaperAcademicpeer-review

Abstract

Forests play a major role in climate change through their unique nature of carbon sequestration which regulates the global temperatures. Climate change is directly attributed to changes in global atmospheric conditions over a given period. This requires actions towards its mitigation and hence various bodies have come up with a number of initiatives geared towards comparting climate change, for example the UNFCCC with its REDD+ (Reducing Emissions from Deforestation and forest Degradation) program. REDD+ aims at accurately quantifying the sources and sinks of carbon, and therefore has designed Measurement Reporting and Verifications (MRVs) system for its implementing countries. The REDD+ MRVs require accurate measurements. This help in quantifying the biomass/carbon stock and establish the amount of carbon sequestered. The biomass estimation equations require tree parameters like Height and Diameter at Breast Height (DBH) as an input. Therefore, there is a need to measure tree height and diameter at breast height accurately. Studies have shown that, the tree height is one of the most difficult forest parameters to be measured, yet can be mapped and measured accurately using remote sensing most notably LiDAR Technology. There is no standard set for the height measurement using the hypsometers. However, the data collected using the hypsometers are considered as the data for validation of the remotely sensed data. This possibly leads to errors which must be minimized. The error is then transferred in to the AGB biomass/carbon estimation. This study is therefore aimed at establishing methods that ensure reasonable accuracy of tree height measurement using both Airborne LiDAR and Terrestrial Laser Scanner.

Original languageEnglish
Pages925-934
Number of pages10
Publication statusPublished - 1 Jan 2016
Event37th Asian Conference on Remote Sensing, ACRS 2016: Spatial Data Infrastructure for Sustainable Development - Colombo, Sri Lanka
Duration: 17 Oct 201621 Oct 2016
Conference number: 37
http://www.acrs2016.org/

Conference

Conference37th Asian Conference on Remote Sensing, ACRS 2016
Abbreviated titleACRS
CountrySri Lanka
CityColombo
Period17/10/1621/10/16
Internet address

Fingerprint

Rain
Biomass
Carbon
Climate change
Deforestation
Remote sensing
Degradation
Lasers
Temperature

Keywords

  • Airborne LiDAR
  • Carbon stock
  • Terrestrial Laser Scanner
  • Tree height
  • Tropical forest

Cite this

Sadadi, O., Hussin, Y. A., Kloosterman, H., & Ismail, M. H. (2016). Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia. 925-934. Paper presented at 37th Asian Conference on Remote Sensing, ACRS 2016, Colombo, Sri Lanka.
Sadadi, Ojoatre ; Hussin, Y.A. ; Kloosterman, H. ; Ismail, Mohd Hasmadi. / Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia. Paper presented at 37th Asian Conference on Remote Sensing, ACRS 2016, Colombo, Sri Lanka.10 p.
@conference{46eeb70530c14c2192d4c0d7898d9a2c,
title = "Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia",
abstract = "Forests play a major role in climate change through their unique nature of carbon sequestration which regulates the global temperatures. Climate change is directly attributed to changes in global atmospheric conditions over a given period. This requires actions towards its mitigation and hence various bodies have come up with a number of initiatives geared towards comparting climate change, for example the UNFCCC with its REDD+ (Reducing Emissions from Deforestation and forest Degradation) program. REDD+ aims at accurately quantifying the sources and sinks of carbon, and therefore has designed Measurement Reporting and Verifications (MRVs) system for its implementing countries. The REDD+ MRVs require accurate measurements. This help in quantifying the biomass/carbon stock and establish the amount of carbon sequestered. The biomass estimation equations require tree parameters like Height and Diameter at Breast Height (DBH) as an input. Therefore, there is a need to measure tree height and diameter at breast height accurately. Studies have shown that, the tree height is one of the most difficult forest parameters to be measured, yet can be mapped and measured accurately using remote sensing most notably LiDAR Technology. There is no standard set for the height measurement using the hypsometers. However, the data collected using the hypsometers are considered as the data for validation of the remotely sensed data. This possibly leads to errors which must be minimized. The error is then transferred in to the AGB biomass/carbon estimation. This study is therefore aimed at establishing methods that ensure reasonable accuracy of tree height measurement using both Airborne LiDAR and Terrestrial Laser Scanner.",
keywords = "Airborne LiDAR, Carbon stock, Terrestrial Laser Scanner, Tree height, Tropical forest",
author = "Ojoatre Sadadi and Y.A. Hussin and H. Kloosterman and Ismail, {Mohd Hasmadi}",
year = "2016",
month = "1",
day = "1",
language = "English",
pages = "925--934",
note = "37th Asian Conference on Remote Sensing, ACRS 2016 : Spatial Data Infrastructure for Sustainable Development, ACRS ; Conference date: 17-10-2016 Through 21-10-2016",
url = "http://www.acrs2016.org/",

}

Sadadi, O, Hussin, YA, Kloosterman, H & Ismail, MH 2016, 'Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia' Paper presented at 37th Asian Conference on Remote Sensing, ACRS 2016, Colombo, Sri Lanka, 17/10/16 - 21/10/16, pp. 925-934.

Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia. / Sadadi, Ojoatre; Hussin, Y.A.; Kloosterman, H.; Ismail, Mohd Hasmadi.

2016. 925-934 Paper presented at 37th Asian Conference on Remote Sensing, ACRS 2016, Colombo, Sri Lanka.

Research output: Contribution to conferencePaperAcademicpeer-review

TY - CONF

T1 - Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia

AU - Sadadi, Ojoatre

AU - Hussin, Y.A.

AU - Kloosterman, H.

AU - Ismail, Mohd Hasmadi

PY - 2016/1/1

Y1 - 2016/1/1

N2 - Forests play a major role in climate change through their unique nature of carbon sequestration which regulates the global temperatures. Climate change is directly attributed to changes in global atmospheric conditions over a given period. This requires actions towards its mitigation and hence various bodies have come up with a number of initiatives geared towards comparting climate change, for example the UNFCCC with its REDD+ (Reducing Emissions from Deforestation and forest Degradation) program. REDD+ aims at accurately quantifying the sources and sinks of carbon, and therefore has designed Measurement Reporting and Verifications (MRVs) system for its implementing countries. The REDD+ MRVs require accurate measurements. This help in quantifying the biomass/carbon stock and establish the amount of carbon sequestered. The biomass estimation equations require tree parameters like Height and Diameter at Breast Height (DBH) as an input. Therefore, there is a need to measure tree height and diameter at breast height accurately. Studies have shown that, the tree height is one of the most difficult forest parameters to be measured, yet can be mapped and measured accurately using remote sensing most notably LiDAR Technology. There is no standard set for the height measurement using the hypsometers. However, the data collected using the hypsometers are considered as the data for validation of the remotely sensed data. This possibly leads to errors which must be minimized. The error is then transferred in to the AGB biomass/carbon estimation. This study is therefore aimed at establishing methods that ensure reasonable accuracy of tree height measurement using both Airborne LiDAR and Terrestrial Laser Scanner.

AB - Forests play a major role in climate change through their unique nature of carbon sequestration which regulates the global temperatures. Climate change is directly attributed to changes in global atmospheric conditions over a given period. This requires actions towards its mitigation and hence various bodies have come up with a number of initiatives geared towards comparting climate change, for example the UNFCCC with its REDD+ (Reducing Emissions from Deforestation and forest Degradation) program. REDD+ aims at accurately quantifying the sources and sinks of carbon, and therefore has designed Measurement Reporting and Verifications (MRVs) system for its implementing countries. The REDD+ MRVs require accurate measurements. This help in quantifying the biomass/carbon stock and establish the amount of carbon sequestered. The biomass estimation equations require tree parameters like Height and Diameter at Breast Height (DBH) as an input. Therefore, there is a need to measure tree height and diameter at breast height accurately. Studies have shown that, the tree height is one of the most difficult forest parameters to be measured, yet can be mapped and measured accurately using remote sensing most notably LiDAR Technology. There is no standard set for the height measurement using the hypsometers. However, the data collected using the hypsometers are considered as the data for validation of the remotely sensed data. This possibly leads to errors which must be minimized. The error is then transferred in to the AGB biomass/carbon estimation. This study is therefore aimed at establishing methods that ensure reasonable accuracy of tree height measurement using both Airborne LiDAR and Terrestrial Laser Scanner.

KW - Airborne LiDAR

KW - Carbon stock

KW - Terrestrial Laser Scanner

KW - Tree height

KW - Tropical forest

UR - http://www.scopus.com/inward/record.url?scp=85018414479&partnerID=8YFLogxK

UR - https://ezproxy2.utwente.nl/login?url=https://library.itc.utwente.nl/login/2016/conf/hussin_tro.pdf

M3 - Paper

SP - 925

EP - 934

ER -

Sadadi O, Hussin YA, Kloosterman H, Ismail MH. Tropical rain forest tree height measurement using ALS and TLS for estimating forest biomass and carbon stock in Ayer Hitam Forest, Malaysia. 2016. Paper presented at 37th Asian Conference on Remote Sensing, ACRS 2016, Colombo, Sri Lanka.