Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis

Ecosystem complexity is among the important drivers of biodiversity and ecosystem functioning, and unmanned aerial systems (UASs) are becoming an important tool for characterizing vegetation patterns and processes. The variety of UASs applications is immense, and so are the procedures to process UAS...

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Autores principales:	Jana Müllerová, Xurxo Gago, Martynas Bučas, Jaume Company, Joan Estrany, Josep Fortesa, Salvatore Manfreda, Adrien Michez, Martin Mokroš, Gernot Paulus, Edvinas Tiškus, Maria A. Tsiafouli, Rafi Kent
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Biodiversity Drones Heterogeneity Methodology Phenology Plant composition Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/8085f71811dc41ab849c438fd1de0a58
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spelling	oai:doaj.org-article:8085f71811dc41ab849c438fd1de0a582021-12-01T04:59:47ZCharacterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis1470-160X10.1016/j.ecolind.2021.108156https://doaj.org/article/8085f71811dc41ab849c438fd1de0a582021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21008219https://doaj.org/toc/1470-160XEcosystem complexity is among the important drivers of biodiversity and ecosystem functioning, and unmanned aerial systems (UASs) are becoming an important tool for characterizing vegetation patterns and processes. The variety of UASs applications is immense, and so are the procedures to process UASs data described in the literature. Optimizing the workflow is still a matter of discussion. Here, we present a comprehensive synthesis aiming to identify common rules that shape workflows applied in UAS-based studies facing complexity in ecosystems. Analysing the studies, we found similarities irrespective of the ecosystem, according to the character of the property addressed, such as species composition (biodiversity), ecosystem structure (stand volume/complexity), plant status (phenology and stress levels), and dynamics (disturbances and regeneration). We propose a general framework allowing to design UAS-based vegetation surveys according to its purpose and the component of ecosystem complexity addressed. We support the framework by detailed schemes as well as examples of best practices of UAS studies covering each of the vegetation properties (i.e. composition, structure, status and dynamics) and related applications. For an efficient UAS survey, the following points are crucial: knowledge of the phenomenon, choice of platform, sensor, resolution (temporal, spatial and spectral), model and classification algorithm according to the phenomenon, as well as careful interpretation of the results. The simpler the procedure, the more robust, repeatable, applicable and cost effective it is. Therefore, the proper design can minimize the efforts while maximizing the quality of the results.Jana MüllerováXurxo GagoMartynas BučasJaume CompanyJoan EstranyJosep FortesaSalvatore ManfredaAdrien MichezMartin MokrošGernot PaulusEdvinas TiškusMaria A. TsiafouliRafi KentElsevierarticleBiodiversityDronesHeterogeneityMethodologyPhenologyPlant compositionEcologyQH540-549.5ENEcological Indicators, Vol 131, Iss , Pp 108156- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biodiversity Drones Heterogeneity Methodology Phenology Plant composition Ecology QH540-549.5
spellingShingle	Biodiversity Drones Heterogeneity Methodology Phenology Plant composition Ecology QH540-549.5 Jana Müllerová Xurxo Gago Martynas Bučas Jaume Company Joan Estrany Josep Fortesa Salvatore Manfreda Adrien Michez Martin Mokroš Gernot Paulus Edvinas Tiškus Maria A. Tsiafouli Rafi Kent Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
description	Ecosystem complexity is among the important drivers of biodiversity and ecosystem functioning, and unmanned aerial systems (UASs) are becoming an important tool for characterizing vegetation patterns and processes. The variety of UASs applications is immense, and so are the procedures to process UASs data described in the literature. Optimizing the workflow is still a matter of discussion. Here, we present a comprehensive synthesis aiming to identify common rules that shape workflows applied in UAS-based studies facing complexity in ecosystems. Analysing the studies, we found similarities irrespective of the ecosystem, according to the character of the property addressed, such as species composition (biodiversity), ecosystem structure (stand volume/complexity), plant status (phenology and stress levels), and dynamics (disturbances and regeneration). We propose a general framework allowing to design UAS-based vegetation surveys according to its purpose and the component of ecosystem complexity addressed. We support the framework by detailed schemes as well as examples of best practices of UAS studies covering each of the vegetation properties (i.e. composition, structure, status and dynamics) and related applications. For an efficient UAS survey, the following points are crucial: knowledge of the phenomenon, choice of platform, sensor, resolution (temporal, spatial and spectral), model and classification algorithm according to the phenomenon, as well as careful interpretation of the results. The simpler the procedure, the more robust, repeatable, applicable and cost effective it is. Therefore, the proper design can minimize the efforts while maximizing the quality of the results.
format	article
author	Jana Müllerová Xurxo Gago Martynas Bučas Jaume Company Joan Estrany Josep Fortesa Salvatore Manfreda Adrien Michez Martin Mokroš Gernot Paulus Edvinas Tiškus Maria A. Tsiafouli Rafi Kent
author_facet	Jana Müllerová Xurxo Gago Martynas Bučas Jaume Company Joan Estrany Josep Fortesa Salvatore Manfreda Adrien Michez Martin Mokroš Gernot Paulus Edvinas Tiškus Maria A. Tsiafouli Rafi Kent
author_sort	Jana Müllerová
title	Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
title_short	Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
title_full	Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
title_fullStr	Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
title_full_unstemmed	Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis
title_sort	characterizing vegetation complexity with unmanned aerial systems (uas) – a framework and synthesis
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/8085f71811dc41ab849c438fd1de0a58
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Characterizing vegetation complexity with unmanned aerial systems (UAS) – A framework and synthesis

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