Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference

Due to climate change, treelines are moving to higher elevations and latitudes. The estimation of biomass of trees and shrubs advancing into alpine areas is necessary for carbon reporting. Remotely sensed (RS) data have previously been utilised extensively for the estimation of forest variables such...

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Published in:Remote Sensing
Main Authors: Ritwika Mukhopadhyay, Erik Næsset, Terje Gobakken, Ida Marielle Mienna, Jaime Candelas Bielza, Gunnar Austrheim, Henrik Jan Persson, Hans Ole Ørka, Bjørn-Eirik Roald, Ole Martin Bollandsås
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
Q
Online Access:https://doi.org/10.3390/rs15143508
https://doaj.org/article/c693e44190674130b673e05b29631927
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spelling ftdoajarticles:oai:doaj.org/article:c693e44190674130b673e05b29631927 2023-08-20T04:05:37+02:00 Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference Ritwika Mukhopadhyay Erik Næsset Terje Gobakken Ida Marielle Mienna Jaime Candelas Bielza Gunnar Austrheim Henrik Jan Persson Hans Ole Ørka Bjørn-Eirik Roald Ole Martin Bollandsås 2023-07-01T00:00:00Z https://doi.org/10.3390/rs15143508 https://doaj.org/article/c693e44190674130b673e05b29631927 EN eng MDPI AG https://www.mdpi.com/2072-4292/15/14/3508 https://doaj.org/toc/2072-4292 doi:10.3390/rs15143508 2072-4292 https://doaj.org/article/c693e44190674130b673e05b29631927 Remote Sensing, Vol 15, Iss 3508, p 3508 (2023) aboveground biomass airborne laser scanning image matching model-based inference treeline vegetation uncertainty estimation Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs15143508 2023-07-30T00:34:47Z Due to climate change, treelines are moving to higher elevations and latitudes. The estimation of biomass of trees and shrubs advancing into alpine areas is necessary for carbon reporting. Remotely sensed (RS) data have previously been utilised extensively for the estimation of forest variables such as tree height, volume, basal area, and aboveground biomass (AGB) in various forest types. Model-based inference is found to be efficient for the estimation of forest attributes using auxiliary RS data, and this study focused on testing model-based estimations of AGB in the treeline ecotone using an area-based approach. Shrubs ( Salix spp., Betula nana ) and trees ( Betula pubescens ssp. czerepanovii , Sorbus aucuparia , Populus tremula , Pinus sylvestris , Picea abies ) with heights up to about five meters constituted the AGB components. The study was carried out in a treeline ecotone in Hol, southern Norway, using field plots and point cloud data obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP). The field data were acquired for two different strata: tall and short vegetation. Two separate models for predicting the AGB were constructed for each stratum based on metrics calculated from ALS and DAP point clouds, respectively. From the stratified predictions, mean AGB was estimated for the entire study area. Despite the prediction models showing a weak fit, as indicated by their R 2 -values, the 95% CIs were relatively narrow, indicating adequate precision of the AGB estimates. No significant difference was found between the mean AGB estimates for the ALS and DAP models for either of the strata. Our results imply that RS data from ALS and DAP can be used for the estimation of AGB in treeline ecotones. Article in Journal/Newspaper Betula nana Directory of Open Access Journals: DOAJ Articles Norway Remote Sensing 15 14 3508
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic aboveground biomass
airborne laser scanning
image matching
model-based inference
treeline vegetation
uncertainty estimation
Science
Q
spellingShingle aboveground biomass
airborne laser scanning
image matching
model-based inference
treeline vegetation
uncertainty estimation
Science
Q
Ritwika Mukhopadhyay
Erik Næsset
Terje Gobakken
Ida Marielle Mienna
Jaime Candelas Bielza
Gunnar Austrheim
Henrik Jan Persson
Hans Ole Ørka
Bjørn-Eirik Roald
Ole Martin Bollandsås
Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
topic_facet aboveground biomass
airborne laser scanning
image matching
model-based inference
treeline vegetation
uncertainty estimation
Science
Q
description Due to climate change, treelines are moving to higher elevations and latitudes. The estimation of biomass of trees and shrubs advancing into alpine areas is necessary for carbon reporting. Remotely sensed (RS) data have previously been utilised extensively for the estimation of forest variables such as tree height, volume, basal area, and aboveground biomass (AGB) in various forest types. Model-based inference is found to be efficient for the estimation of forest attributes using auxiliary RS data, and this study focused on testing model-based estimations of AGB in the treeline ecotone using an area-based approach. Shrubs ( Salix spp., Betula nana ) and trees ( Betula pubescens ssp. czerepanovii , Sorbus aucuparia , Populus tremula , Pinus sylvestris , Picea abies ) with heights up to about five meters constituted the AGB components. The study was carried out in a treeline ecotone in Hol, southern Norway, using field plots and point cloud data obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP). The field data were acquired for two different strata: tall and short vegetation. Two separate models for predicting the AGB were constructed for each stratum based on metrics calculated from ALS and DAP point clouds, respectively. From the stratified predictions, mean AGB was estimated for the entire study area. Despite the prediction models showing a weak fit, as indicated by their R 2 -values, the 95% CIs were relatively narrow, indicating adequate precision of the AGB estimates. No significant difference was found between the mean AGB estimates for the ALS and DAP models for either of the strata. Our results imply that RS data from ALS and DAP can be used for the estimation of AGB in treeline ecotones.
format Article in Journal/Newspaper
author Ritwika Mukhopadhyay
Erik Næsset
Terje Gobakken
Ida Marielle Mienna
Jaime Candelas Bielza
Gunnar Austrheim
Henrik Jan Persson
Hans Ole Ørka
Bjørn-Eirik Roald
Ole Martin Bollandsås
author_facet Ritwika Mukhopadhyay
Erik Næsset
Terje Gobakken
Ida Marielle Mienna
Jaime Candelas Bielza
Gunnar Austrheim
Henrik Jan Persson
Hans Ole Ørka
Bjørn-Eirik Roald
Ole Martin Bollandsås
author_sort Ritwika Mukhopadhyay
title Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
title_short Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
title_full Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
title_fullStr Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
title_full_unstemmed Mapping and Estimating Aboveground Biomass in an Alpine Treeline Ecotone under Model-Based Inference
title_sort mapping and estimating aboveground biomass in an alpine treeline ecotone under model-based inference
publisher MDPI AG
publishDate 2023
url https://doi.org/10.3390/rs15143508
https://doaj.org/article/c693e44190674130b673e05b29631927
geographic Norway
geographic_facet Norway
genre Betula nana
genre_facet Betula nana
op_source Remote Sensing, Vol 15, Iss 3508, p 3508 (2023)
op_relation https://www.mdpi.com/2072-4292/15/14/3508
https://doaj.org/toc/2072-4292
doi:10.3390/rs15143508
2072-4292
https://doaj.org/article/c693e44190674130b673e05b29631927
op_doi https://doi.org/10.3390/rs15143508
container_title Remote Sensing
container_volume 15
container_issue 14
container_start_page 3508
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