Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems

© 2017 by the author. Arctic tundra ecosystems are a major source of methane (CH 4 ), 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 disconne...

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Published in:Remote Sensing
Main Authors: Davidson, S.J., Santos, M.J., Sloan, V.L., Reuss-Schmidt, K., Phoenix, G.K., Oechel, W.C., Zona, D.
Format: Article in Journal/Newspaper
Language:English
Published: MDPI 2017
Subjects:
Online Access:https://eprints.whiterose.ac.uk/125567/
https://eprints.whiterose.ac.uk/125567/1/Davidson_Upscaling_RemoteSensing_2017.pdf
https://doi.org/10.3390/rs9121227
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spelling ftleedsuniv:oai:eprints.whiterose.ac.uk:125567 2023-05-15T14:24:09+02:00 Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems Davidson, S.J. Santos, M.J. Sloan, V.L. Reuss-Schmidt, K. Phoenix, G.K. Oechel, W.C. Zona, D. 2017-12-01 text https://eprints.whiterose.ac.uk/125567/ https://eprints.whiterose.ac.uk/125567/1/Davidson_Upscaling_RemoteSensing_2017.pdf https://doi.org/10.3390/rs9121227 en eng MDPI https://eprints.whiterose.ac.uk/125567/1/Davidson_Upscaling_RemoteSensing_2017.pdf Davidson, S.J., Santos, M.J., Sloan, V.L. et al. (4 more authors) (2017) Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems. Remote Sensing, 9 (12). ISSN 2072-4292 cc_by_4 CC-BY Article PeerReviewed 2017 ftleedsuniv https://doi.org/10.3390/rs9121227 2023-01-30T22:02:17Z © 2017 by the author. Arctic tundra ecosystems are a major source of methane (CH 4 ), 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 CH 4 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 CH 4 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 CH 4 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 CH 4 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 Arctic Tundra White Rose Research Online (Universities of Leeds, Sheffield & York) Arctic Remote Sensing 9 12 1227
institution Open Polar
collection White Rose Research Online (Universities of Leeds, Sheffield & York)
op_collection_id ftleedsuniv
language English
description © 2017 by the author. Arctic tundra ecosystems are a major source of methane (CH 4 ), 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 CH 4 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 CH 4 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 CH 4 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 CH 4 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.
format Article in Journal/Newspaper
author Davidson, S.J.
Santos, M.J.
Sloan, V.L.
Reuss-Schmidt, K.
Phoenix, G.K.
Oechel, W.C.
Zona, D.
spellingShingle Davidson, S.J.
Santos, M.J.
Sloan, V.L.
Reuss-Schmidt, K.
Phoenix, G.K.
Oechel, W.C.
Zona, D.
Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems
author_facet Davidson, S.J.
Santos, M.J.
Sloan, V.L.
Reuss-Schmidt, K.
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
publisher MDPI
publishDate 2017
url https://eprints.whiterose.ac.uk/125567/
https://eprints.whiterose.ac.uk/125567/1/Davidson_Upscaling_RemoteSensing_2017.pdf
https://doi.org/10.3390/rs9121227
geographic Arctic
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genre Arctic
Arctic
Tundra
genre_facet Arctic
Arctic
Tundra
op_relation https://eprints.whiterose.ac.uk/125567/1/Davidson_Upscaling_RemoteSensing_2017.pdf
Davidson, S.J., Santos, M.J., Sloan, V.L. et al. (4 more authors) (2017) Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems. Remote Sensing, 9 (12). ISSN 2072-4292
op_rights cc_by_4
op_rightsnorm CC-BY
op_doi https://doi.org/10.3390/rs9121227
container_title Remote Sensing
container_volume 9
container_issue 12
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