| Registro completo |
| Provedor de dados: |
ArchiMer
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| País: |
France
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| Título: |
The DIARS toolbox: a spatially explicit approach to monitor alien plant invasions through remote sensing
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| Autores: |
Garzon-lopez, Carol X.
Hattab, Tarek
Skowronek, Sandra
Aerts, Raf
Ewald, Michael
Feilhauer, Hannes
Honnay, Olivier
Decocq, Guillaume
Van De Kerchove, Ruben
Somers, Ben
Schmidtlein, Sebastian
Rocchini, Duccio
Lenoir, Jonathan
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| Data: |
2018-03
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| Ano: |
2018
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| Palavras-chave: |
Biological invasions
Ecosystem impact
Hyperspectral images
LiDAR
Species detection and mapping
Species distribution models
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| Resumo: |
The synergies between remote sensing technologies and ecological research have opened new avenues for the study of alien plant invasions worldwide. Such scientific advances have greatly improved our capacity to issue warnings, develop early-response systems and assess the impacts of alien plant invasions on biodiversity and ecosystem functioning. Hitherto, practical applications of remote sensing approaches to support nature conservation actions are lagging far behind scientific advances. Yet, for some of these technologies, knowledge transfer is difficult due to the complexity of the different data handling procedures and the huge amounts of data it involves per spatial unit. In this context, the next logical step is to develop clear guidelines for the application of remote sensing data to monitor and assess the impacts of alien plant invasions, that enable scientists, landscape managers and policy makers to fully exploit the tools which are currently available. It is desirable to have such guidelines accompanied by freely available remote sensing data and generated in a free and open source environment that increases the availability and affordability of these new technologies. Here we present a toolbox that provides an easy-to-use, flexible, transparent and open source set of tools to sample, map, model and assess the impact of alien plant invasions using two high-resolution remote sensing products (hyperspectral and LiDAR images). This online toolbox includes a real case dataset designed to facilitate testing and training in any computer system and processing capacity.
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| Tipo: |
Text
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| Idioma: |
Inglês
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| Identificador: |
https://archimer.ifremer.fr/doc/00435/54645/56071.pdf
DOI:10.3897/rio.4.e25301
https://archimer.ifremer.fr/doc/00435/54645/
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| Editor: |
Pensoft Publishers
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| Relação: |
info:eu-repo/grantAgreement/EC/FP7/517836/EU//BIODIVERSA
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| Formato: |
application/pdf
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| Fonte: |
Research Ideas and Outcomes (2367-7163) (Pensoft Publishers), 2018-03 , Vol. 4 , P. e25301 (12p.)
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| Direitos: |
Garzon-Lopez CX et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
info:eu-repo/semantics/openAccess
restricted use
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