UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest

Bibliographic Details
Published in:Ecological Informatics
Main Authors: Sotille, Maria E., Bremer, Ulisses F., Vieira, Gonçalo, Velho, Luiz F., Petsch, Carina, Auger, Jeffrey D., Simões, Jefferson C.
Other Authors: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier BV 2022
Subjects:
Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
Antarc*
Antarctic
Online Access:http://dx.doi.org/10.1016/j.ecoinf.2022.101768
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spelling crelsevierbv:10.1016/j.ecoinf.2022.101768 2024-05-19T07:32:32+00:00 UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest Sotille, Maria E. Bremer, Ulisses F. Vieira, Gonçalo Velho, Luiz F. Petsch, Carina Auger, Jeffrey D. Simões, Jefferson C. Coordenação de Aperfeiçoamento de Pessoal de Nível Superior Conselho Nacional de Desenvolvimento Cientifico e Tecnologico 2022 http://dx.doi.org/10.1016/j.ecoinf.2022.101768 https://api.elsevier.com/content/article/PII:S1574954122002187?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S1574954122002187?httpAccept=text/plain en eng Elsevier BV https://www.elsevier.com/tdm/userlicense/1.0/ https://doi.org/10.15223/policy-017 https://doi.org/10.15223/policy-037 https://doi.org/10.15223/policy-012 https://doi.org/10.15223/policy-029 https://doi.org/10.15223/policy-004 Ecological Informatics volume 71, page 101768 ISSN 1574-9541 Applied Mathematics Computational Theory and Mathematics Computer Science Applications Ecological Modeling Modeling and Simulation Ecology Ecology, Evolution, Behavior and Systematics journal-article 2022 crelsevierbv https://doi.org/10.1016/j.ecoinf.2022.101768 2024-04-22T06:51:15Z Article in Journal/Newspaper Antarc* Antarctic ScienceDirect (Elsevier) Ecological Informatics 71 101768
institution Open Polar
collection ScienceDirect (Elsevier)
op_collection_id crelsevierbv
language English
topic Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
spellingShingle Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
Sotille, Maria E.
Bremer, Ulisses F.
Vieira, Gonçalo
Velho, Luiz F.
Petsch, Carina
Auger, Jeffrey D.
Simões, Jefferson C.
UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest
topic_facet Applied Mathematics
Computational Theory and Mathematics
Computer Science Applications
Ecological Modeling
Modeling and Simulation
Ecology
Ecology, Evolution, Behavior and Systematics
author2 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
format Article in Journal/Newspaper
author Sotille, Maria E.
Bremer, Ulisses F.
Vieira, Gonçalo
Velho, Luiz F.
Petsch, Carina
Auger, Jeffrey D.
Simões, Jefferson C.
author_facet Sotille, Maria E.
Bremer, Ulisses F.
Vieira, Gonçalo
Velho, Luiz F.
Petsch, Carina
Auger, Jeffrey D.
Simões, Jefferson C.
author_sort Sotille, Maria E.
title UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest
title_short UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest
title_full UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest
title_fullStr UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest
title_full_unstemmed UAV-based classification of maritime Antarctic vegetation types using GEOBIA and random forest
title_sort uav-based classification of maritime antarctic vegetation types using geobia and random forest
publisher Elsevier BV
publishDate 2022
url http://dx.doi.org/10.1016/j.ecoinf.2022.101768
https://api.elsevier.com/content/article/PII:S1574954122002187?httpAccept=text/xml
https://api.elsevier.com/content/article/PII:S1574954122002187?httpAccept=text/plain
genre Antarc*
Antarctic
genre_facet Antarc*
Antarctic
op_source Ecological Informatics
volume 71, page 101768
ISSN 1574-9541
op_rights https://www.elsevier.com/tdm/userlicense/1.0/
https://doi.org/10.15223/policy-017
https://doi.org/10.15223/policy-037
https://doi.org/10.15223/policy-012
https://doi.org/10.15223/policy-029
https://doi.org/10.15223/policy-004
op_doi https://doi.org/10.1016/j.ecoinf.2022.101768
container_title Ecological Informatics
container_volume 71
container_start_page 101768
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