Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices.
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/33883 |
Resumo: | Given the continuous increase in the global population, the food manufacturers are advocated to either intensify the use of cropland or expand the farmland, making land cover and land usage dynamics mapping vital in the area of remote sensing. In this regard, identifying and classifying a high-resolution satellite imagery scene is a prime challenge. Several approaches have been proposed either by using static rule-based thresholds (with limitation of diversity) or neural network (with data-dependent limitations). This paper adopts an inductive approach to build classifiers from spectral reflectances, comparing usefulness of the various spectral indices to raw bands information. More specifically, it considers Sentinel2 data for six classes Scene Classification (Water, Shadow, Cirrus, Cloud, Snow and Other). The experimental results show that using raw bands performs equally well, claiming that raw bands information can be used as a replacement of the spectral indices. |
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Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices.Given the continuous increase in the global population, the food manufacturers are advocated to either intensify the use of cropland or expand the farmland, making land cover and land usage dynamics mapping vital in the area of remote sensing. In this regard, identifying and classifying a high-resolution satellite imagery scene is a prime challenge. Several approaches have been proposed either by using static rule-based thresholds (with limitation of diversity) or neural network (with data-dependent limitations). This paper adopts an inductive approach to build classifiers from spectral reflectances, comparing usefulness of the various spectral indices to raw bands information. More specifically, it considers Sentinel2 data for six classes Scene Classification (Water, Shadow, Cirrus, Cloud, Snow and Other). The experimental results show that using raw bands performs equally well, claiming that raw bands information can be used as a replacement of the spectral indices.2023-02-03T16:00:14Z2023-02-032021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/33883http://hdl.handle.net/10174/33883porKashyap Raiyani, Teresa Gonçalves, and Luı́s Rato. Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. In Proceedings of the 27th Portuguese Conference on Pattern Recognition, RECPAD 2021, 2021.ndtcg@uevora.ptndRaiyani, KashyapGonçalves, TeresaRato, Luisinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:35:56Zoai:dspace.uevora.pt:10174/33883Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:22:35.140494Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
title |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
spellingShingle |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. Raiyani, Kashyap |
title_short |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
title_full |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
title_fullStr |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
title_full_unstemmed |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
title_sort |
Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. |
author |
Raiyani, Kashyap |
author_facet |
Raiyani, Kashyap Gonçalves, Teresa Rato, Luis |
author_role |
author |
author2 |
Gonçalves, Teresa Rato, Luis |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Raiyani, Kashyap Gonçalves, Teresa Rato, Luis |
description |
Given the continuous increase in the global population, the food manufacturers are advocated to either intensify the use of cropland or expand the farmland, making land cover and land usage dynamics mapping vital in the area of remote sensing. In this regard, identifying and classifying a high-resolution satellite imagery scene is a prime challenge. Several approaches have been proposed either by using static rule-based thresholds (with limitation of diversity) or neural network (with data-dependent limitations). This paper adopts an inductive approach to build classifiers from spectral reflectances, comparing usefulness of the various spectral indices to raw bands information. More specifically, it considers Sentinel2 data for six classes Scene Classification (Water, Shadow, Cirrus, Cloud, Snow and Other). The experimental results show that using raw bands performs equally well, claiming that raw bands information can be used as a replacement of the spectral indices. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-01T00:00:00Z 2023-02-03T16:00:14Z 2023-02-03 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/33883 http://hdl.handle.net/10174/33883 |
url |
http://hdl.handle.net/10174/33883 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
Kashyap Raiyani, Teresa Gonçalves, and Luı́s Rato. Sentinel 2 Image Scene Classifica- tion: A Comparison Between Bands and Spectral Indices. In Proceedings of the 27th Portuguese Conference on Pattern Recognition, RECPAD 2021, 2021. nd tcg@uevora.pt nd |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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