Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape

This is the author accepted manuscript. The final version is available from IOP Publishing via the DOI in this record Data accessibility: The data that support the findings of this study are openly available at the following DOI: https://doi.org/10.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9) Arctic l...

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Published in:Environmental Research Letters
Main Authors: Cunliffe, AM, Assmann, JJ, Daskalova, G, Kerby, JT, Myers-Smith, IH
Format: Article in Journal/Newspaper
Language:English
Published: IOP Publishing 2020
Subjects:
Online Access:http://hdl.handle.net/10871/123172
https://doi.org/10.1088/1748-9326/aba470
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author Cunliffe, AM
Assmann, JJ
Daskalova, G
Kerby, JT
Myers-Smith, IH
author_facet Cunliffe, AM
Assmann, JJ
Daskalova, G
Kerby, JT
Myers-Smith, IH
author_sort Cunliffe, AM
collection University of Exeter: Open Research Exeter (ORE)
container_issue 12
container_start_page 125004
container_title Environmental Research Letters
container_volume 15
description This is the author accepted manuscript. The final version is available from IOP Publishing via the DOI in this record Data accessibility: The data that support the findings of this study are openly available at the following DOI: https://doi.org/10.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9) Arctic landscapes are changing rapidly in response to warming, but future predictions are hindered by difficulties in scaling ecological relationships from plots to biomes. Unmanned aerial systems (UAS, hereafter 'drones') are increasingly used to observe Arctic ecosystems over broader extents than can be measured using ground-based approaches and facilitate the interpretation of coarse-grained remotely-sensed datasets. However, more information is needed about how drone-acquired remote sensing observations correspond with ecosystem attributes such as aboveground biomass. Working across a willow shrub-dominated alluvial fan at a focal study site in the Canadian Arctic, we conducted peak season drone surveys with a RGB camera and multispectral multi camera array to derive photogrammetric reconstructions of canopy and normalised difference vegetation index (NDVI) maps along with in situ point intercept measurements and biomass harvests from 36, 0.25 m2 plots. We found high correspondence between canopy height measured using in situ point intercept compared to drone-photogrammetry (concordance correlation coefficient = 0.808), although the photogrammetry heights were positively biased by 0.14 m relative to point intercept heights. Canopy height was strongly and linearly related to aboveground biomass, with similar coefficients of determination for point framing (R2 = 0.92) and drone-based methods (R2 = 0.90). NDVI was positively related to aboveground biomass, phytomass and leaf biomass. However, NDVI only explained a small proportion of the variance in biomass (R2 between 0.14 and 0.23 for logged total biomass) and we found moss cover influenced the NDVI-phytomass relationship. Biomass is challenging to infer from ...
format Article in Journal/Newspaper
genre Arctic
Tundra
genre_facet Arctic
Tundra
geographic Arctic
geographic_facet Arctic
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institution Open Polar
language English
op_collection_id ftunivexeter
op_doi https://doi.org/10.1088/1748-9326/aba47010.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9
op_relation https://doi.org/10.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9
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Environmental Research Letters
op_rights © 2020 The Author(s). Published by IOP Publishing Ltd. Open access under a CC BY 3.0 licence. Everyone is permitted to use all or part of the original content in this article, provided that they adhere to all the terms of the licence: https://creativecommons.org/licences/by/3.0. Although reasonable endeavours have been taken to obtain all necessary permissions from third parties to include their copyrighted content within this article, their full citation and copyright line may not be present in this Accepted Manuscript version. Before using any content from this article, please refer to the Version of Record on IOPscience once published for full citation and copyright details, as permissions may be required. All third party content is fully copyright protected and is not published on a gold open access basis under a CC BY licence, unless that is specifically stated in the figure caption in the Version of Record.
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spelling ftunivexeter:oai:ore.exeter.ac.uk:10871/123172 2025-04-06T14:44:15+00:00 Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape Cunliffe, AM Assmann, JJ Daskalova, G Kerby, JT Myers-Smith, IH 2020 http://hdl.handle.net/10871/123172 https://doi.org/10.1088/1748-9326/aba470 en eng IOP Publishing https://doi.org/10.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9 NE/M016323/1 754513 http://hdl.handle.net/10871/123172 Environmental Research Letters © 2020 The Author(s). Published by IOP Publishing Ltd. Open access under a CC BY 3.0 licence. Everyone is permitted to use all or part of the original content in this article, provided that they adhere to all the terms of the licence: https://creativecommons.org/licences/by/3.0. Although reasonable endeavours have been taken to obtain all necessary permissions from third parties to include their copyrighted content within this article, their full citation and copyright line may not be present in this Accepted Manuscript version. Before using any content from this article, please refer to the Version of Record on IOPscience once published for full citation and copyright details, as permissions may be required. All third party content is fully copyright protected and is not published on a gold open access basis under a CC BY licence, unless that is specifically stated in the figure caption in the Version of Record. https://creativecommons.org/licenses/by/3.0 Vegetation Change Aboveground Vascular Biomass Vegetation greenness Normalised Difference Vegetation Index (NDVI) Drones Arctic Tundra Ecosystems Structure-from-Motion Photogrammetry Article 2020 ftunivexeter https://doi.org/10.1088/1748-9326/aba47010.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9 2025-03-11T01:39:58Z This is the author accepted manuscript. The final version is available from IOP Publishing via the DOI in this record Data accessibility: The data that support the findings of this study are openly available at the following DOI: https://doi.org/10.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9) Arctic landscapes are changing rapidly in response to warming, but future predictions are hindered by difficulties in scaling ecological relationships from plots to biomes. Unmanned aerial systems (UAS, hereafter 'drones') are increasingly used to observe Arctic ecosystems over broader extents than can be measured using ground-based approaches and facilitate the interpretation of coarse-grained remotely-sensed datasets. However, more information is needed about how drone-acquired remote sensing observations correspond with ecosystem attributes such as aboveground biomass. Working across a willow shrub-dominated alluvial fan at a focal study site in the Canadian Arctic, we conducted peak season drone surveys with a RGB camera and multispectral multi camera array to derive photogrammetric reconstructions of canopy and normalised difference vegetation index (NDVI) maps along with in situ point intercept measurements and biomass harvests from 36, 0.25 m2 plots. We found high correspondence between canopy height measured using in situ point intercept compared to drone-photogrammetry (concordance correlation coefficient = 0.808), although the photogrammetry heights were positively biased by 0.14 m relative to point intercept heights. Canopy height was strongly and linearly related to aboveground biomass, with similar coefficients of determination for point framing (R2 = 0.92) and drone-based methods (R2 = 0.90). NDVI was positively related to aboveground biomass, phytomass and leaf biomass. However, NDVI only explained a small proportion of the variance in biomass (R2 between 0.14 and 0.23 for logged total biomass) and we found moss cover influenced the NDVI-phytomass relationship. Biomass is challenging to infer from ... Article in Journal/Newspaper Arctic Tundra University of Exeter: Open Research Exeter (ORE) Arctic Environmental Research Letters 15 12 125004
spellingShingle Vegetation Change
Aboveground Vascular Biomass
Vegetation greenness
Normalised Difference Vegetation Index (NDVI)
Drones
Arctic Tundra Ecosystems
Structure-from-Motion Photogrammetry
Cunliffe, AM
Assmann, JJ
Daskalova, G
Kerby, JT
Myers-Smith, IH
Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
title Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
title_full Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
title_fullStr Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
title_full_unstemmed Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
title_short Aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (NDVI) in a shrub tundra landscape
title_sort aboveground biomass corresponds strongly with drone-derived canopy height but weakly with greenness (ndvi) in a shrub tundra landscape
topic Vegetation Change
Aboveground Vascular Biomass
Vegetation greenness
Normalised Difference Vegetation Index (NDVI)
Drones
Arctic Tundra Ecosystems
Structure-from-Motion Photogrammetry
topic_facet Vegetation Change
Aboveground Vascular Biomass
Vegetation greenness
Normalised Difference Vegetation Index (NDVI)
Drones
Arctic Tundra Ecosystems
Structure-from-Motion Photogrammetry
url http://hdl.handle.net/10871/123172
https://doi.org/10.1088/1748-9326/aba470