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Near-real time aboveground carbon emissions in Peru

Monitoring aboveground carbon stocks and fluxes from tropical deforestation and forest degradation is important for mitigating climate change and improving forest management. However, high temporal and spatial resolution analyses are rare. This study presents the most detailed tracking of abovegroun...

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Detalles Bibliográficos
Autores principales: Csillik, Ovidiu, Asner, Gregory P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605693/
https://www.ncbi.nlm.nih.gov/pubmed/33137140
http://dx.doi.org/10.1371/journal.pone.0241418
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author Csillik, Ovidiu
Asner, Gregory P.
author_facet Csillik, Ovidiu
Asner, Gregory P.
author_sort Csillik, Ovidiu
collection PubMed
description Monitoring aboveground carbon stocks and fluxes from tropical deforestation and forest degradation is important for mitigating climate change and improving forest management. However, high temporal and spatial resolution analyses are rare. This study presents the most detailed tracking of aboveground carbon over time, with yearly, quarterly and monthly estimations of emissions using the stock-difference approach and masked by the forest loss layer of Global Forest Watch. We generated high spatial resolution (1-ha) monitoring of aboveground carbon density (ACD) and emissions (ACE) in Peru by incorporating hundreds of thousands of Planet Dove satellite images, Sentinel-1 radar, topography and airborne LiDAR, embedded into a deep learning regression workflow using high-performance computing. Consistent ACD results were obtained for all quarters and months analyzed, with R(2) values of 0.75–0.78, and root mean square errors (RMSE) between 20.6 and 22.0 Mg C ha(-1). A total of 7.138 Pg C was estimated for Peru with annual ACE of 20.08 Tg C between the third quarters of 2017 and 2018, respectively, or 23.4% higher than estimates from the FAO Global Forest Resources Assessment. Analyzed quarterly, the spatial evolution of ACE revealed 11.5 Tg C, 6.6 Tg C, 8.6 Tg C, and 10.1 Tg C lost between the third quarters of 2017 and 2018. Moreover, our monthly analysis for the dry season reveals the evolution of ACE at unprecedented temporal detail. We discuss environmental controls over ACE and provide a spatially explicit tool for enhanced forest carbon management at scale.
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spelling pubmed-76056932020-11-05 Near-real time aboveground carbon emissions in Peru Csillik, Ovidiu Asner, Gregory P. PLoS One Research Article Monitoring aboveground carbon stocks and fluxes from tropical deforestation and forest degradation is important for mitigating climate change and improving forest management. However, high temporal and spatial resolution analyses are rare. This study presents the most detailed tracking of aboveground carbon over time, with yearly, quarterly and monthly estimations of emissions using the stock-difference approach and masked by the forest loss layer of Global Forest Watch. We generated high spatial resolution (1-ha) monitoring of aboveground carbon density (ACD) and emissions (ACE) in Peru by incorporating hundreds of thousands of Planet Dove satellite images, Sentinel-1 radar, topography and airborne LiDAR, embedded into a deep learning regression workflow using high-performance computing. Consistent ACD results were obtained for all quarters and months analyzed, with R(2) values of 0.75–0.78, and root mean square errors (RMSE) between 20.6 and 22.0 Mg C ha(-1). A total of 7.138 Pg C was estimated for Peru with annual ACE of 20.08 Tg C between the third quarters of 2017 and 2018, respectively, or 23.4% higher than estimates from the FAO Global Forest Resources Assessment. Analyzed quarterly, the spatial evolution of ACE revealed 11.5 Tg C, 6.6 Tg C, 8.6 Tg C, and 10.1 Tg C lost between the third quarters of 2017 and 2018. Moreover, our monthly analysis for the dry season reveals the evolution of ACE at unprecedented temporal detail. We discuss environmental controls over ACE and provide a spatially explicit tool for enhanced forest carbon management at scale. Public Library of Science 2020-11-02 /pmc/articles/PMC7605693/ /pubmed/33137140 http://dx.doi.org/10.1371/journal.pone.0241418 Text en © 2020 Csillik, Asner http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Csillik, Ovidiu
Asner, Gregory P.
Near-real time aboveground carbon emissions in Peru
title Near-real time aboveground carbon emissions in Peru
title_full Near-real time aboveground carbon emissions in Peru
title_fullStr Near-real time aboveground carbon emissions in Peru
title_full_unstemmed Near-real time aboveground carbon emissions in Peru
title_short Near-real time aboveground carbon emissions in Peru
title_sort near-real time aboveground carbon emissions in peru
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605693/
https://www.ncbi.nlm.nih.gov/pubmed/33137140
http://dx.doi.org/10.1371/journal.pone.0241418
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