CatLC: Catalonia Multiresolution Land Cover Dataset

The availability of large annotated image datasets represented one of the tipping points in the progress of object recognition in the realm of natural images, but other important visual spaces are still lacking this asset. In the case of remote sensing, only a few richly annotated datasets covering...

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Autores: García Rodríguez, Carlos, Mora Sacristán, Oscar, Pérez-Aragüés, Fernando, Vitrià i Marca, Jordi
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/188901
Acesso em linha:https://hdl.handle.net/2445/188901
Access Level:acceso abierto
Palavra-chave:Teledetecció
Imatges satel·litàries
Aprenentatge automàtic
Cartografia ambiental
Dades massives
Remote sensing
Remote-sensing images
Machine learning
Environmental mapping
Big data
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spelling CatLC: Catalonia Multiresolution Land Cover DatasetGarcía Rodríguez, CarlosMora Sacristán, OscarPérez-Aragüés, FernandoVitrià i Marca, JordiTeledeteccióImatges satel·litàriesAprenentatge automàticCartografia ambientalDades massivesRemote sensingRemote-sensing imagesMachine learningEnvironmental mappingBig dataThe availability of large annotated image datasets represented one of the tipping points in the progress of object recognition in the realm of natural images, but other important visual spaces are still lacking this asset. In the case of remote sensing, only a few richly annotated datasets covering small areas are available. In this paper, we present the Catalonia Multiresolution Land Cover Dataset (CatLC), a remote sensing dataset corresponding to a mid-size geographical area which has been carefully annotated with a large variety of land cover classes. The dataset includes pre-processed images from the Cartographic and Geological Institute of Catalonia (ICGC) (https://www.icgc.cat/en/Downloads) and the European Space Agency (ESA) (https://scihub.copernicus.eu) catalogs, captured from both aircraft and satellites. Detailed topographic layers inferred from other sensors are also included. CatLC is a multiresolution, multimodal, multitemporal dataset, that can be readily used by the machine learning community to explore new classification techniques for land cover mapping in different scenarios such as area estimation in forest inventories, hydrologic studies involving microclimatic variables or geologic hazards identification and assessment. Moreover, remote sensing data present some specific characteristics that are not shared by natural images and that have been seldom explored. In this vein, CatLC dataset aims to engage with computer vision experts interested in remote sensing and also stimulate new research and development in the field of machine learning.Nature Publishing Group2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/188901Articles publicats en revistes (Matemàtiques i Informàtica)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.1038/S41597-022-01674-YScientific Reports, 2022https://doi.org/10.1038/S41597-022-01674-Ycc-by (c) García Rodríguez, Carlos et al., 2022https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1889012026-05-27T06:46:51Z
dc.title.none.fl_str_mv CatLC: Catalonia Multiresolution Land Cover Dataset
title CatLC: Catalonia Multiresolution Land Cover Dataset
spellingShingle CatLC: Catalonia Multiresolution Land Cover Dataset
García Rodríguez, Carlos
Teledetecció
Imatges satel·litàries
Aprenentatge automàtic
Cartografia ambiental
Dades massives
Remote sensing
Remote-sensing images
Machine learning
Environmental mapping
Big data
title_short CatLC: Catalonia Multiresolution Land Cover Dataset
title_full CatLC: Catalonia Multiresolution Land Cover Dataset
title_fullStr CatLC: Catalonia Multiresolution Land Cover Dataset
title_full_unstemmed CatLC: Catalonia Multiresolution Land Cover Dataset
title_sort CatLC: Catalonia Multiresolution Land Cover Dataset
dc.creator.none.fl_str_mv García Rodríguez, Carlos
Mora Sacristán, Oscar
Pérez-Aragüés, Fernando
Vitrià i Marca, Jordi
author García Rodríguez, Carlos
author_facet García Rodríguez, Carlos
Mora Sacristán, Oscar
Pérez-Aragüés, Fernando
Vitrià i Marca, Jordi
author_role author
author2 Mora Sacristán, Oscar
Pérez-Aragüés, Fernando
Vitrià i Marca, Jordi
author2_role author
author
author
dc.subject.none.fl_str_mv Teledetecció
Imatges satel·litàries
Aprenentatge automàtic
Cartografia ambiental
Dades massives
Remote sensing
Remote-sensing images
Machine learning
Environmental mapping
Big data
topic Teledetecció
Imatges satel·litàries
Aprenentatge automàtic
Cartografia ambiental
Dades massives
Remote sensing
Remote-sensing images
Machine learning
Environmental mapping
Big data
description The availability of large annotated image datasets represented one of the tipping points in the progress of object recognition in the realm of natural images, but other important visual spaces are still lacking this asset. In the case of remote sensing, only a few richly annotated datasets covering small areas are available. In this paper, we present the Catalonia Multiresolution Land Cover Dataset (CatLC), a remote sensing dataset corresponding to a mid-size geographical area which has been carefully annotated with a large variety of land cover classes. The dataset includes pre-processed images from the Cartographic and Geological Institute of Catalonia (ICGC) (https://www.icgc.cat/en/Downloads) and the European Space Agency (ESA) (https://scihub.copernicus.eu) catalogs, captured from both aircraft and satellites. Detailed topographic layers inferred from other sensors are also included. CatLC is a multiresolution, multimodal, multitemporal dataset, that can be readily used by the machine learning community to explore new classification techniques for land cover mapping in different scenarios such as area estimation in forest inventories, hydrologic studies involving microclimatic variables or geologic hazards identification and assessment. Moreover, remote sensing data present some specific characteristics that are not shared by natural images and that have been seldom explored. In this vein, CatLC dataset aims to engage with computer vision experts interested in remote sensing and also stimulate new research and development in the field of machine learning.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/188901
url https://hdl.handle.net/2445/188901
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1038/S41597-022-01674-Y
Scientific Reports, 2022
https://doi.org/10.1038/S41597-022-01674-Y
dc.rights.none.fl_str_mv cc-by (c) García Rodríguez, Carlos et al., 2022
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) García Rodríguez, Carlos et al., 2022
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Nature Publishing Group
publisher.none.fl_str_mv Nature Publishing Group
dc.source.none.fl_str_mv Articles publicats en revistes (Matemàtiques i Informàtica)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,198674

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