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Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

BACKGROUND: Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this e...

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Autores principales: Huang, Wenli, Swatantran, Anu, Johnson, Kristofer, Duncanson, Laura, Tang, Hao, O’Neil Dunne, Jarlath, Hurtt, George, Dubayah, Ralph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537504/
https://www.ncbi.nlm.nih.gov/pubmed/26294932
http://dx.doi.org/10.1186/s13021-015-0030-9
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author Huang, Wenli
Swatantran, Anu
Johnson, Kristofer
Duncanson, Laura
Tang, Hao
O’Neil Dunne, Jarlath
Hurtt, George
Dubayah, Ralph
author_facet Huang, Wenli
Swatantran, Anu
Johnson, Kristofer
Duncanson, Laura
Tang, Hao
O’Neil Dunne, Jarlath
Hurtt, George
Dubayah, Ralph
author_sort Huang, Wenli
collection PubMed
description BACKGROUND: Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level. RESULTS: Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5–92.7 Mg ha(−1)). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0–54.6 Mg ha(−1)) and total biomass (3.5–5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30–80 Tg in forested and 40–50 Tg in non-forested areas. CONCLUSIONS: Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, forest/non-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13021-015-0030-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-45375042015-08-18 Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA Huang, Wenli Swatantran, Anu Johnson, Kristofer Duncanson, Laura Tang, Hao O’Neil Dunne, Jarlath Hurtt, George Dubayah, Ralph Carbon Balance Manag Research BACKGROUND: Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-derived biomass map over Maryland, USA. We conduct detailed comparisons at pixel-, county-, and state-level. RESULTS: Spatial patterns of biomass are broadly consistent in all maps, but there are large differences at fine scales (RMSD 48.5–92.7 Mg ha(−1)). Discrepancies reduce with aggregation and the agreement among products improves at the county level. However, continental scale maps exhibit residual negative biases in mean (33.0–54.6 Mg ha(−1)) and total biomass (3.5–5.8 Tg) when compared to the high-resolution lidar biomass map. Three of the four continental scale maps reach near-perfect agreement at ~4 km and onward but do not converge with the high-resolution biomass map even at county scale. At the State level, these maps underestimate biomass by 30–80 Tg in forested and 40–50 Tg in non-forested areas. CONCLUSIONS: Local discrepancies in continental scale biomass maps are caused by factors including data inputs, modeling approaches, forest/non-forest definitions and time lags. There is a net underestimation over high biomass forests and non-forested areas that could impact carbon accounting at all levels. Local, high-resolution lidar-derived biomass maps provide a valuable bottom-up reference to improve the analysis and interpretation of large-scale maps produced in carbon monitoring systems. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13021-015-0030-9) contains supplementary material, which is available to authorized users. Springer International Publishing 2015-08-16 /pmc/articles/PMC4537504/ /pubmed/26294932 http://dx.doi.org/10.1186/s13021-015-0030-9 Text en © Huang et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Huang, Wenli
Swatantran, Anu
Johnson, Kristofer
Duncanson, Laura
Tang, Hao
O’Neil Dunne, Jarlath
Hurtt, George
Dubayah, Ralph
Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
title Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
title_full Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
title_fullStr Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
title_full_unstemmed Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
title_short Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA
title_sort local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in maryland, usa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537504/
https://www.ncbi.nlm.nih.gov/pubmed/26294932
http://dx.doi.org/10.1186/s13021-015-0030-9
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