Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems
Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measureme...
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ftunivutrecht:oai:dspace.library.uu.nl:1874/362462 2023-07-23T04:16:49+02:00 Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems Davidson, S.J. Ferreira Dos Santos, M.J. Sloan, V.L. Watts, J. Phoenix, G.K. Oechel, W.C. Zona, D. Environmental Sciences 2017 image/pdf https://dspace.library.uu.nl/handle/1874/362462 en eng 2072-4292 https://dspace.library.uu.nl/handle/1874/362462 info:eu-repo/semantics/OpenAccess Remonte sensing Tundra Methane Valorisation Arctic methane flux vegetation communities upscaling footprint modelling multispectral imagery Alaska Article 2017 ftunivutrecht 2023-07-02T02:24:10Z Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100–1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales Article in Journal/Newspaper arctic methane Arctic Tundra Alaska Utrecht University Repository Arctic |
institution |
Open Polar |
collection |
Utrecht University Repository |
op_collection_id |
ftunivutrecht |
language |
English |
topic |
Remonte sensing Tundra Methane Valorisation Arctic methane flux vegetation communities upscaling footprint modelling multispectral imagery Alaska |
spellingShingle |
Remonte sensing Tundra Methane Valorisation Arctic methane flux vegetation communities upscaling footprint modelling multispectral imagery Alaska Davidson, S.J. Ferreira Dos Santos, M.J. Sloan, V.L. Watts, J. Phoenix, G.K. Oechel, W.C. Zona, D. Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems |
topic_facet |
Remonte sensing Tundra Methane Valorisation Arctic methane flux vegetation communities upscaling footprint modelling multispectral imagery Alaska |
description |
Arctic tundra ecosystems are a major source of methane (CH4), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100–1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales |
author2 |
Environmental Sciences |
format |
Article in Journal/Newspaper |
author |
Davidson, S.J. Ferreira Dos Santos, M.J. Sloan, V.L. Watts, J. Phoenix, G.K. Oechel, W.C. Zona, D. |
author_facet |
Davidson, S.J. Ferreira Dos Santos, M.J. Sloan, V.L. Watts, J. Phoenix, G.K. Oechel, W.C. Zona, D. |
author_sort |
Davidson, S.J. |
title |
Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems |
title_short |
Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems |
title_full |
Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems |
title_fullStr |
Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems |
title_full_unstemmed |
Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems |
title_sort |
upscaling ch4 fluxes using high-resolution imagery in arctic tundra ecosystems |
publishDate |
2017 |
url |
https://dspace.library.uu.nl/handle/1874/362462 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
arctic methane Arctic Tundra Alaska |
genre_facet |
arctic methane Arctic Tundra Alaska |
op_relation |
2072-4292 https://dspace.library.uu.nl/handle/1874/362462 |
op_rights |
info:eu-repo/semantics/OpenAccess |
_version_ |
1772177931021320192 |