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Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis

Understanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring...

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Autores principales: Monteiro, João Gama, Jiménez, Jesús L., Gizzi, Francesca, Přikryl, Petr, Lefcheck, Jonathan S., Santos, Ricardo S., Canning-Clode, João
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804263/
https://www.ncbi.nlm.nih.gov/pubmed/33436894
http://dx.doi.org/10.1038/s41598-020-80612-7
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author Monteiro, João Gama
Jiménez, Jesús L.
Gizzi, Francesca
Přikryl, Petr
Lefcheck, Jonathan S.
Santos, Ricardo S.
Canning-Clode, João
author_facet Monteiro, João Gama
Jiménez, Jesús L.
Gizzi, Francesca
Přikryl, Petr
Lefcheck, Jonathan S.
Santos, Ricardo S.
Canning-Clode, João
author_sort Monteiro, João Gama
collection PubMed
description Understanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring programs and studies must deliver information on a range of variables and factors, from taxonomic/functional diversity and spatial distribution of habitats, to anthropogenic stress indicators such as land use, fisheries use, and pollution. Effective monitoring programs must therefore integrate observations from different sources and spatial scales to provide a comprehensive view to managers. Here we explore integrating aerial surveys from a low-cost Remotely Piloted Aircraft System (RPAS) with concurrent underwater surveys to deliver a novel approach to coastal monitoring. We: (i) map depth and substrate of shallow rocky habitats, and; (ii) classify the major biotopes associated with these environmental axes; and (iii) combine data from i and ii to assess the likely distribution of common sessile organismal assemblages over the survey area. Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce spatially-explicit biotope maps.
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spelling pubmed-78042632021-01-13 Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis Monteiro, João Gama Jiménez, Jesús L. Gizzi, Francesca Přikryl, Petr Lefcheck, Jonathan S. Santos, Ricardo S. Canning-Clode, João Sci Rep Article Understanding the complex factors and mechanisms driving the functioning of coastal ecosystems is vital towards assessing how organisms, ecosystems, and ultimately human populations will cope with the ecological consequences of natural and anthropogenic impacts. Towards this goal, coastal monitoring programs and studies must deliver information on a range of variables and factors, from taxonomic/functional diversity and spatial distribution of habitats, to anthropogenic stress indicators such as land use, fisheries use, and pollution. Effective monitoring programs must therefore integrate observations from different sources and spatial scales to provide a comprehensive view to managers. Here we explore integrating aerial surveys from a low-cost Remotely Piloted Aircraft System (RPAS) with concurrent underwater surveys to deliver a novel approach to coastal monitoring. We: (i) map depth and substrate of shallow rocky habitats, and; (ii) classify the major biotopes associated with these environmental axes; and (iii) combine data from i and ii to assess the likely distribution of common sessile organismal assemblages over the survey area. Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce spatially-explicit biotope maps. Nature Publishing Group UK 2021-01-12 /pmc/articles/PMC7804263/ /pubmed/33436894 http://dx.doi.org/10.1038/s41598-020-80612-7 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Monteiro, João Gama
Jiménez, Jesús L.
Gizzi, Francesca
Přikryl, Petr
Lefcheck, Jonathan S.
Santos, Ricardo S.
Canning-Clode, João
Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
title Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
title_full Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
title_fullStr Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
title_full_unstemmed Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
title_short Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
title_sort novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804263/
https://www.ncbi.nlm.nih.gov/pubmed/33436894
http://dx.doi.org/10.1038/s41598-020-80612-7
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