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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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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1774716190543839232 |