Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data
The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases...
Published in: | Environmental Research Letters |
---|---|
Main Authors: | , , , , , , , , , , , , , , , , , , , |
Other Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
IOP Publishing
2021
|
Subjects: | |
Online Access: | http://hdl.handle.net/10138/329942 |
id |
ftunivhelsihelda:oai:helda.helsinki.fi:10138/329942 |
---|---|
record_format |
openpolar |
spelling |
ftunivhelsihelda:oai:helda.helsinki.fi:10138/329942 2024-01-07T09:40:42+01:00 Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data Thomson, Eleanor R. Spiegel, Marcus P. Althuizen, Inge H. J. Bass, Polly Chen, Shuli Chmurzynski, Adam Halbritter, Aud H. Henn, Jonathan J. Jonsdottir, Ingibjorg S. Klanderud, Kari Li, Yaoqi Maitner, Brian S. Michaletz, Sean T. Niittynen, Pekka Roos, Ruben E. Telford, Richard J. Enquist, Brian J. Vandvik, Vigdis Macias-Fauria, Marc Malhi, Yadvinder Department of Geosciences and Geography Helsinki Institute of Sustainability Science (HELSUS) BioGeoClimate Modelling Lab Geology (-2014) 2021-05-14T09:29:02Z 20 application/pdf http://hdl.handle.net/10138/329942 eng eng IOP Publishing 10.1088/1748-9326/abf464 The data collection was funded by a Norwegian Research Council INTPART Grant (Project Number: 274831), two SIU-foundation projects (UTF2013/10074 and HNP-2015/10037) and a Research Council of Norway Arctic Field Grant (Project Number: 282611, RiS: 10935). E R T is funded by NERC DTP award (NE/L002612/1). Y M is supported by the Jackson Foundation. M M-F was supported by a NERC IRF (NE/L011859/1). Thomson , E R , Spiegel , M P , Althuizen , I H J , Bass , P , Chen , S , Chmurzynski , A , Halbritter , A H , Henn , J J , Jonsdottir , I S , Klanderud , K , Li , Y , Maitner , B S , Michaletz , S T , Niittynen , P , Roos , R E , Telford , R J , Enquist , B J , Vandvik , V , Macias-Fauria , M & Malhi , Y 2021 , ' Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data ' , Environmental Research Letters , vol. 16 , no. 5 , 055006 . https://doi.org/10.1088/1748-9326/abf464 ORCID: /0000-0002-7290-029X/work/93851829 9022c984-1b5c-439a-a8d7-f704db11437e http://hdl.handle.net/10138/329942 000642202900001 cc_by openAccess info:eu-repo/semantics/openAccess 1172 Environmental sciences Article publishedVersion 2021 ftunivhelsihelda 2023-12-14T00:08:15Z The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400-2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r (2) = 0.61-0.88, RMSEmean = 12%-64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic. Peer reviewed Article in Journal/Newspaper Arctic Arctic Longyearbyen Svalbard Tundra HELDA – University of Helsinki Open Repository Arctic Longyearbyen Svalbard Environmental Research Letters 16 5 055006 |
institution |
Open Polar |
collection |
HELDA – University of Helsinki Open Repository |
op_collection_id |
ftunivhelsihelda |
language |
English |
topic |
1172 Environmental sciences |
spellingShingle |
1172 Environmental sciences Thomson, Eleanor R. Spiegel, Marcus P. Althuizen, Inge H. J. Bass, Polly Chen, Shuli Chmurzynski, Adam Halbritter, Aud H. Henn, Jonathan J. Jonsdottir, Ingibjorg S. Klanderud, Kari Li, Yaoqi Maitner, Brian S. Michaletz, Sean T. Niittynen, Pekka Roos, Ruben E. Telford, Richard J. Enquist, Brian J. Vandvik, Vigdis Macias-Fauria, Marc Malhi, Yadvinder Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data |
topic_facet |
1172 Environmental sciences |
description |
The Arctic is warming twice as fast as the rest of the planet, leading to rapid changes in species composition and plant functional trait variation. Landscape-level maps of vegetation composition and trait distributions are required to expand spatially-limited plot studies, overcome sampling biases associated with the most accessible research areas, and create baselines from which to monitor environmental change. Unmanned aerial vehicles (UAVs) have emerged as a low-cost method to generate high-resolution imagery and bridge the gap between fine-scale field studies and lower resolution satellite analyses. Here we used field spectroscopy data (400-2500 nm) and UAV multispectral imagery to test spectral methods of species identification and plant water and chemistry retrieval near Longyearbyen, Svalbard. Using the field spectroscopy data and Random Forest analysis, we were able to distinguish eight common High Arctic plant tundra species with 74% accuracy. Using partial least squares regression (PLSR), we were able to predict corresponding water, nitrogen, phosphorus and C:N values (r (2) = 0.61-0.88, RMSEmean = 12%-64%). We developed analogous models using UAV imagery (five bands: Blue, Green, Red, Red Edge and Near-Infrared) and scaled up the results across a 450 m long nutrient gradient located underneath a seabird colony. At the UAV level, we were able to map three plant functional groups (mosses, graminoids and dwarf shrubs) at 72% accuracy and generate maps of plant chemistry. Our maps show a clear marine-derived fertility gradient, mediated by geomorphology. We used the UAV results to explore two methods of upscaling plant water content to the wider landscape using Sentinel-2A imagery. Our results are pertinent for high resolution, low-cost mapping of the Arctic. Peer reviewed |
author2 |
Department of Geosciences and Geography Helsinki Institute of Sustainability Science (HELSUS) BioGeoClimate Modelling Lab Geology (-2014) |
format |
Article in Journal/Newspaper |
author |
Thomson, Eleanor R. Spiegel, Marcus P. Althuizen, Inge H. J. Bass, Polly Chen, Shuli Chmurzynski, Adam Halbritter, Aud H. Henn, Jonathan J. Jonsdottir, Ingibjorg S. Klanderud, Kari Li, Yaoqi Maitner, Brian S. Michaletz, Sean T. Niittynen, Pekka Roos, Ruben E. Telford, Richard J. Enquist, Brian J. Vandvik, Vigdis Macias-Fauria, Marc Malhi, Yadvinder |
author_facet |
Thomson, Eleanor R. Spiegel, Marcus P. Althuizen, Inge H. J. Bass, Polly Chen, Shuli Chmurzynski, Adam Halbritter, Aud H. Henn, Jonathan J. Jonsdottir, Ingibjorg S. Klanderud, Kari Li, Yaoqi Maitner, Brian S. Michaletz, Sean T. Niittynen, Pekka Roos, Ruben E. Telford, Richard J. Enquist, Brian J. Vandvik, Vigdis Macias-Fauria, Marc Malhi, Yadvinder |
author_sort |
Thomson, Eleanor R. |
title |
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data |
title_short |
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data |
title_full |
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data |
title_fullStr |
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data |
title_full_unstemmed |
Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data |
title_sort |
multiscale mapping of plant functional groups and plant traits in the high arctic using field spectroscopy, uav imagery and sentinel-2a data |
publisher |
IOP Publishing |
publishDate |
2021 |
url |
http://hdl.handle.net/10138/329942 |
geographic |
Arctic Longyearbyen Svalbard |
geographic_facet |
Arctic Longyearbyen Svalbard |
genre |
Arctic Arctic Longyearbyen Svalbard Tundra |
genre_facet |
Arctic Arctic Longyearbyen Svalbard Tundra |
op_relation |
10.1088/1748-9326/abf464 The data collection was funded by a Norwegian Research Council INTPART Grant (Project Number: 274831), two SIU-foundation projects (UTF2013/10074 and HNP-2015/10037) and a Research Council of Norway Arctic Field Grant (Project Number: 282611, RiS: 10935). E R T is funded by NERC DTP award (NE/L002612/1). Y M is supported by the Jackson Foundation. M M-F was supported by a NERC IRF (NE/L011859/1). Thomson , E R , Spiegel , M P , Althuizen , I H J , Bass , P , Chen , S , Chmurzynski , A , Halbritter , A H , Henn , J J , Jonsdottir , I S , Klanderud , K , Li , Y , Maitner , B S , Michaletz , S T , Niittynen , P , Roos , R E , Telford , R J , Enquist , B J , Vandvik , V , Macias-Fauria , M & Malhi , Y 2021 , ' Multiscale mapping of plant functional groups and plant traits in the High Arctic using field spectroscopy, UAV imagery and Sentinel-2A data ' , Environmental Research Letters , vol. 16 , no. 5 , 055006 . https://doi.org/10.1088/1748-9326/abf464 ORCID: /0000-0002-7290-029X/work/93851829 9022c984-1b5c-439a-a8d7-f704db11437e http://hdl.handle.net/10138/329942 000642202900001 |
op_rights |
cc_by openAccess info:eu-repo/semantics/openAccess |
container_title |
Environmental Research Letters |
container_volume |
16 |
container_issue |
5 |
container_start_page |
055006 |
_version_ |
1787421521454563328 |