Cargando…
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...
Autores principales: | , , , , , , , |
---|---|
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 |
_version_ | 1782385898679173120 |
---|---|
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. |
format | Online Article Text |
id | pubmed-4537504 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT huangwenli localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT swatantrananu localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT johnsonkristofer localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT duncansonlaura localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT tanghao localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT oneildunnejarlath localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT hurttgeorge localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa AT dubayahralph localdiscrepanciesincontinentalscalebiomassmapsacasestudyoverforestedandnonforestedlandscapesinmarylandusa |