Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data

Estimating aboveground biomass changes in tropical mountains is difficult due to the small-scale anthropogenic land use activities such as selective logging. This study examined how multitemporal airborne LiDAR data could estimate AGB changes in Borneo’s tropical montane forest. Using airborne LiDAR...

Full description

Saved in:
Bibliographic Details
Main Authors: Ho Yan Loh, Daniel James, Keiko Ioki, wilson vun Chiong wong, Satoshi Tsuyuki c, Mui-How Phua
Format: Article
Language:en
en
Published: Elsevier 2022
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/36202/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/36202/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/36202/
https://doi.org/10.1016/j.rsase.2022.100821
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1831795662905147392
author Ho Yan Loh
Daniel James
Keiko Ioki
wilson vun Chiong wong
Satoshi Tsuyuki c
Mui-How Phua
author_facet Ho Yan Loh
Daniel James
Keiko Ioki
wilson vun Chiong wong
Satoshi Tsuyuki c
Mui-How Phua
author_sort Ho Yan Loh
building UMS Library
collection Institutional Repository
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
continent Asia
country Malaysia
description Estimating aboveground biomass changes in tropical mountains is difficult due to the small-scale anthropogenic land use activities such as selective logging. This study examined how multitemporal airborne LiDAR data could estimate AGB changes in Borneo’s tropical montane forest. Using airborne LiDAR data acquired in 2012 and 2017, we compared direct and indirect approaches to estimating the AGB changes. The direct method predicts the AGB change directly based on differences in LiDAR variables between the two time points whereas, the indirect method first constructs a model for predicting the AGB for each time point and then estimates the changes. The direct approach produced a model with an adjusted R2 of 0.321 and a relatively high RMSE (6.37 Mg/ha/year; relative RMSE: 134.36%). On the other hand, annual AGB changes derived from the indirect approach had a low RMSE value (1.413 Mg/ha/year; relative RMSE: 29.80%) and were strongly correlated with the field AGB changes (R2 = 0.988). We estimated the AGB changes using the indirect approach to be − 7.49 Mg/ha/year for AGB loss and 8.91 Mg/ha/ year for AGB gain. We identified land use conversion as the primary driver of AGB changes in the montane forest since the rate of AGB decrease in state-land was higher than in the managed forest. The LiDAR-based approach provides high-resolution estimates of AGB changes by enlarging field plots to more extensive area coverage, facilitating the adoption of incentive-based carbon conservation mechanisms.
format Article
id my.ums.eprints-36202
institution Universiti Malaysia Sabah
language en
en
publishDate 2022
publisher Elsevier
record_format eprints
spelling my.ums.eprints-362022023-07-24T08:12:29Z https://eprints.ums.edu.my/id/eprint/36202/ Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data Ho Yan Loh Daniel James Keiko Ioki wilson vun Chiong wong Satoshi Tsuyuki c Mui-How Phua RA565-600 Environmental health Including sewage disposal, air pollution, nuisances, water supply SD388 Forestry machinery and engineering Estimating aboveground biomass changes in tropical mountains is difficult due to the small-scale anthropogenic land use activities such as selective logging. This study examined how multitemporal airborne LiDAR data could estimate AGB changes in Borneo’s tropical montane forest. Using airborne LiDAR data acquired in 2012 and 2017, we compared direct and indirect approaches to estimating the AGB changes. The direct method predicts the AGB change directly based on differences in LiDAR variables between the two time points whereas, the indirect method first constructs a model for predicting the AGB for each time point and then estimates the changes. The direct approach produced a model with an adjusted R2 of 0.321 and a relatively high RMSE (6.37 Mg/ha/year; relative RMSE: 134.36%). On the other hand, annual AGB changes derived from the indirect approach had a low RMSE value (1.413 Mg/ha/year; relative RMSE: 29.80%) and were strongly correlated with the field AGB changes (R2 = 0.988). We estimated the AGB changes using the indirect approach to be − 7.49 Mg/ha/year for AGB loss and 8.91 Mg/ha/ year for AGB gain. We identified land use conversion as the primary driver of AGB changes in the montane forest since the rate of AGB decrease in state-land was higher than in the managed forest. The LiDAR-based approach provides high-resolution estimates of AGB changes by enlarging field plots to more extensive area coverage, facilitating the adoption of incentive-based carbon conservation mechanisms. Elsevier 2022 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/36202/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/36202/2/FULL%20TEXT.pdf Ho Yan Loh and Daniel James and Keiko Ioki and wilson vun Chiong wong and Satoshi Tsuyuki c and Mui-How Phua (2022) Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data. Remote Sensing Applications: Society and Environment, 28. pp. 1-13. https://doi.org/10.1016/j.rsase.2022.100821
spellingShingle RA565-600 Environmental health Including sewage disposal, air pollution, nuisances, water supply
SD388 Forestry machinery and engineering
Ho Yan Loh
Daniel James
Keiko Ioki
wilson vun Chiong wong
Satoshi Tsuyuki c
Mui-How Phua
Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data
title Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data
title_full Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data
title_fullStr Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data
title_full_unstemmed Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data
title_short Estimating aboveground biomass changes in a human-modified tropical montane forest of Borneo using multi-temporal airborne LiDAR data
title_sort estimating aboveground biomass changes in a human-modified tropical montane forest of borneo using multi-temporal airborne lidar data
topic RA565-600 Environmental health Including sewage disposal, air pollution, nuisances, water supply
SD388 Forestry machinery and engineering
url https://eprints.ums.edu.my/id/eprint/36202/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/36202/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/36202/
https://doi.org/10.1016/j.rsase.2022.100821
url_provider http://eprints.ums.edu.my/