Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation
Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the...
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ftubpotsdam:oai:kobv.de-opus4-uni-potsdam:42592 2023-12-03T10:16:06+01:00 Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation Hyperspektrale Fernerkundung der räumlichen und zeitlichen Heterogenität niedriger arktischer Vegetation Beamish, Alison Leslie (M. Sc.) 2019 application/pdf https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42592 https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-425922 https://doi.org/10.25932/publishup-42592 https://publishup.uni-potsdam.de/files/42592/beamish_diss.pdf eng eng https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42592 urn:nbn:de:kobv:517-opus4-425922 https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-425922 https://doi.org/10.25932/publishup-42592 https://publishup.uni-potsdam.de/files/42592/beamish_diss.pdf http://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess ddc:550 Institut für Geowissenschaften Extern doctoralthesis doc-type:doctoralThesis 2019 ftubpotsdam https://doi.org/10.25932/publishup-42592 2023-11-05T23:35:04Z Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the global carbon and energy balance. Optical remote sensing is an effective tool for monitoring ecosystem functioning in this remote biome. However, limited field-based spectral characterization of the spatial and temporal heterogeneity limits the accuracy of quantitative optical remote sensing at landscape scales. To address this research gap and support current and future satellite missions, three central research questions were posed: • Does canopy-level spectral variability differ between dominant low Arctic vegetation communities and does this variability change between major phenological phases? • How does canopy-level vegetation colour images recorded with high and low spectral resolution devices relate to phenological changes in leaf-level photosynthetic pigment concentrations? • How does spatial aggregation of high spectral resolution data from the ground to satellite scale influence low Arctic tundra vegetation signatures and thereby what is the potential of upcoming hyperspectral spaceborne systems for low Arctic vegetation characterization? To answer these questions a unique and detailed database was assembled. Field-based canopy-level spectral reflectance measurements, nadir digital photographs, and photosynthetic pigment concentrations of dominant low Arctic vegetation communities were acquired at three major phenological phases representing early, peak and late season. Data were collected in 2015 and 2016 in the Toolik Lake Research Natural Area located in north central Alaska on the North Slope of the Brooks Range. In addition to field data an aerial AISA hyperspectral image was acquired in the late season of 2016. Simulations of broadband Sentinel-2 and hyperspectral Environmental and Mapping Analysis ... Doctoral or Postdoctoral Thesis Arctic Arktis* Brooks Range north slope Tundra Alaska University of Potsdam: publish.UP Arctic |
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Open Polar |
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University of Potsdam: publish.UP |
op_collection_id |
ftubpotsdam |
language |
English |
topic |
ddc:550 Institut für Geowissenschaften Extern |
spellingShingle |
ddc:550 Institut für Geowissenschaften Extern Beamish, Alison Leslie (M. Sc.) Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation |
topic_facet |
ddc:550 Institut für Geowissenschaften Extern |
description |
Arctic tundra ecosystems are experiencing warming twice the global average and Arctic vegetation is responding in complex and heterogeneous ways. Shifting productivity, growth, species composition, and phenology at local and regional scales have implications for ecosystem functioning as well as the global carbon and energy balance. Optical remote sensing is an effective tool for monitoring ecosystem functioning in this remote biome. However, limited field-based spectral characterization of the spatial and temporal heterogeneity limits the accuracy of quantitative optical remote sensing at landscape scales. To address this research gap and support current and future satellite missions, three central research questions were posed: • Does canopy-level spectral variability differ between dominant low Arctic vegetation communities and does this variability change between major phenological phases? • How does canopy-level vegetation colour images recorded with high and low spectral resolution devices relate to phenological changes in leaf-level photosynthetic pigment concentrations? • How does spatial aggregation of high spectral resolution data from the ground to satellite scale influence low Arctic tundra vegetation signatures and thereby what is the potential of upcoming hyperspectral spaceborne systems for low Arctic vegetation characterization? To answer these questions a unique and detailed database was assembled. Field-based canopy-level spectral reflectance measurements, nadir digital photographs, and photosynthetic pigment concentrations of dominant low Arctic vegetation communities were acquired at three major phenological phases representing early, peak and late season. Data were collected in 2015 and 2016 in the Toolik Lake Research Natural Area located in north central Alaska on the North Slope of the Brooks Range. In addition to field data an aerial AISA hyperspectral image was acquired in the late season of 2016. Simulations of broadband Sentinel-2 and hyperspectral Environmental and Mapping Analysis ... |
format |
Doctoral or Postdoctoral Thesis |
author |
Beamish, Alison Leslie (M. Sc.) |
author_facet |
Beamish, Alison Leslie (M. Sc.) |
author_sort |
Beamish, Alison Leslie (M. Sc.) |
title |
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation |
title_short |
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation |
title_full |
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation |
title_fullStr |
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation |
title_full_unstemmed |
Hyperspectral remote sensing of the spatial and temporal heterogeneity of low Arctic vegetation |
title_sort |
hyperspectral remote sensing of the spatial and temporal heterogeneity of low arctic vegetation |
publishDate |
2019 |
url |
https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42592 https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-425922 https://doi.org/10.25932/publishup-42592 https://publishup.uni-potsdam.de/files/42592/beamish_diss.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arktis* Brooks Range north slope Tundra Alaska |
genre_facet |
Arctic Arktis* Brooks Range north slope Tundra Alaska |
op_relation |
https://publishup.uni-potsdam.de/frontdoor/index/index/docId/42592 urn:nbn:de:kobv:517-opus4-425922 https://nbn-resolving.org/urn:nbn:de:kobv:517-opus4-425922 https://doi.org/10.25932/publishup-42592 https://publishup.uni-potsdam.de/files/42592/beamish_diss.pdf |
op_rights |
http://creativecommons.org/licenses/by-nc/4.0/ info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.25932/publishup-42592 |
_version_ |
1784262998152445952 |