Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul

Detalhes bibliográficos
Autor(a) principal: Mantovani, José Roberto
Data de Publicação: 2023
Outros Autores: Lelis , Leandro Reginaldo Maximino
Tipo de documento: Artigo
Idioma: por
Título da fonte: Revista Cerrados (Montes Claros. Online)
Texto Completo: https://www.periodicos.unimontes.br/index.php/cerrados/article/view/5068
Resumo: A methodology is proposed that uses mathematical concepts of the theory of cluster formation, the K-means, to automatically obtain the clusters of the NDVI values, to determine the use and occupation of the land. The implementations of the K- means method existing in specific software require the predefinition of the number of clusters, and the contribution of this methodology is the determination of the number of clusters automatically, without the need for interference of the decision maker, which may vary according to time and space from one image to another, as well as from one sensor to the next. Different sensors were selected to generalize this index classification: Thematic Mapper (TM) on board the Landsat-5 satellite; Operational Terra Imager (OLI) aboard the Landsat-8 satellite; MultiSpectral Instrument (MSI) aboard the Sentinel, level-2A satellite. The mapping and validation of algorithm are carried out in the northeast region of state of Mato Grosso do Sul, which, over 37 years (1984-2021) shows changes in its vegetation cover. The results obtained for the three periods, provided by the algorithm, better distinguished the spectral behavior of pixels referring to water classes, exposed soil and urban areas; on the other hand, the JENKS method generalized these classes, on the other hand, it better distinguished low-sized vegetation, natural vegetation and planted forests.
id UNIMONTES_a14d4f5e67217840d3b30cb93adf8def
oai_identifier_str oai:ojs2.periodicos.unimontes.br:article/5068
network_acronym_str UNIMONTES
network_name_str Revista Cerrados (Montes Claros. Online)
repository_id_str
spelling Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do SulAlgoritmo para mapeo de usos de suelo y cobertura vegetal, a partir del uso de NDVI aplicado en el noreste de Mato Grosso do SulAlgoritmo para mapeamento dos usos do solo e cobertura vegetal a partir do uso do NDVI: um estudo aplicado no nordeste de Mato Grosso Do SulClusterK-MeansComportamento espectralJenksClusterK-meansSpectral behaviorJenksClusterK-meansComportamiento espectralJenksA methodology is proposed that uses mathematical concepts of the theory of cluster formation, the K-means, to automatically obtain the clusters of the NDVI values, to determine the use and occupation of the land. The implementations of the K- means method existing in specific software require the predefinition of the number of clusters, and the contribution of this methodology is the determination of the number of clusters automatically, without the need for interference of the decision maker, which may vary according to time and space from one image to another, as well as from one sensor to the next. Different sensors were selected to generalize this index classification: Thematic Mapper (TM) on board the Landsat-5 satellite; Operational Terra Imager (OLI) aboard the Landsat-8 satellite; MultiSpectral Instrument (MSI) aboard the Sentinel, level-2A satellite. The mapping and validation of algorithm are carried out in the northeast region of state of Mato Grosso do Sul, which, over 37 years (1984-2021) shows changes in its vegetation cover. The results obtained for the three periods, provided by the algorithm, better distinguished the spectral behavior of pixels referring to water classes, exposed soil and urban areas; on the other hand, the JENKS method generalized these classes, on the other hand, it better distinguished low-sized vegetation, natural vegetation and planted forests.Se propone una metodología que utiliza conceptos matemáticos de la teoría de formación de clusters, K-means, para obtener automaticamente los clusters de los valores del NDVI. Las implementaciones del método K-means existentes em software específico requieren la predefinición del número de clusters, y el aporte de esta metodología es la determinación del número de forma automática, sin necesidad de interferencia del decisor, que puede variar según el tempo y el espacio de uma imagen a outra, así como de um sensor al siguiente. Se seleccionaron diferentes sensores para generalizar esta clasificación del índice: Thematic Mapper (TM) a bordo del satélite Landsat-5; Operational Terra Imager (OLI) a bordo del satélite Landsat-8; MultiSpectral Instrument (MSI) a bordo del satélite Sentinel, nivel-2. El mapeo y la validación del algoritmo se realizan en la región noreste del estado de Mato Grosso do Sul, que, a lo largo de 37 años (1984-2021), muestra cambios en su cobertura vegetal. Los resultados para los tres períodos, proporcionados por el algoritmo, distinguieron mejor el comportamiento espectral de los píxeles referidos a clases de agua, suelo expuesto y áreas urbanas; por otro lado, JENKS generalizó estas clases, pero distinguió con mayor precisión la vegetación de porte bajo, la vegetación natural y los bosques plantados.Propõe-se uma metodologia que utiliza conceitos matemáticos da teoria de formação de clusters, o K-means, para obter de forma automática os clusters dos valores do NDVI. As implementações do método K-means existentes em softwares específicos exige a predefinição no número de clusters, sendo a contribuição desta metodologia a determinação do número de clusters automaticamente, sem a necessidade da interferência do tomador de decisões que, pode variar de acordo com o tempo e o espaço de uma imagem para outra, bem como de um sensor para o outro. Foram selecionados diferentes sensores para generalizar essa classificação do índice: Thematic Mapper (TM) a bordo do satélite Landsat-5; Operational Terra Imager (OLI) a bordo do satélite Landsat-8; MultiSpectral Instrument (MSI) a bordo do satélite Sentinel, nível-2A. O mapeamento e a validação do algoritmo são efetuados na região nordeste do estado de Mato Grosso do Sul, a qual, apresenta ao longo de 37 anos (1984- 2021) alterações em sua cobertura vegetal. Os resultados para os três períodos, fornecidos pelo algoritmo distinguiu melhor o comportamento espectral dos pixels referentes às classes de água, solo exposto e áreas urbanas; já o JENKS generalizou essas classes, por outro lado, distinguiu com melhor precisão vegetação de baixo porte, vegetação natural e florestas plantadas.Editora Unimontes2023-07-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtigoapplication/pdfhttps://www.periodicos.unimontes.br/index.php/cerrados/article/view/506810.46551/rc24482692202317Revista Cerrados; v. 21 n. 02 (2023): Revista Cerrados; 03-342448-26921678-8346reponame:Revista Cerrados (Montes Claros. Online)instname:Universidade Estadual de Montes Claros (UNIMONTES)instacron:UNIMONTESporhttps://www.periodicos.unimontes.br/index.php/cerrados/article/view/5068/6556Copyright (c) 2023 Revista Cerradoshttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessMantovani, José RobertoLelis , Leandro Reginaldo Maximino2023-12-24T23:32:02Zoai:ojs2.periodicos.unimontes.br:article/5068Revistahttps://www.periodicos.unimontes.br/index.php/cerradosPUBhttps://www.periodicos.unimontes.br/index.php/cerrados/oairevista.cerrados@unimontes.br||portal.periodicos@unimontes.br.2448-26921678-8346opendoar:2023-12-24T23:32:02Revista Cerrados (Montes Claros. Online) - Universidade Estadual de Montes Claros (UNIMONTES)false
dc.title.none.fl_str_mv Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
Algoritmo para mapeo de usos de suelo y cobertura vegetal, a partir del uso de NDVI aplicado en el noreste de Mato Grosso do Sul
Algoritmo para mapeamento dos usos do solo e cobertura vegetal a partir do uso do NDVI: um estudo aplicado no nordeste de Mato Grosso Do Sul
title Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
spellingShingle Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
Mantovani, José Roberto
Cluster
K-Means
Comportamento espectral
Jenks
Cluster
K-means
Spectral behavior
Jenks
Cluster
K-means
Comportamiento espectral
Jenks
title_short Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
title_full Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
title_fullStr Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
title_full_unstemmed Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
title_sort Algorithm for mapping land uses and vegetable coverage, from the use of NDVI applied in the northeastern of Mato Grosso Do Sul
author Mantovani, José Roberto
author_facet Mantovani, José Roberto
Lelis , Leandro Reginaldo Maximino
author_role author
author2 Lelis , Leandro Reginaldo Maximino
author2_role author
dc.contributor.author.fl_str_mv Mantovani, José Roberto
Lelis , Leandro Reginaldo Maximino
dc.subject.por.fl_str_mv Cluster
K-Means
Comportamento espectral
Jenks
Cluster
K-means
Spectral behavior
Jenks
Cluster
K-means
Comportamiento espectral
Jenks
topic Cluster
K-Means
Comportamento espectral
Jenks
Cluster
K-means
Spectral behavior
Jenks
Cluster
K-means
Comportamiento espectral
Jenks
description A methodology is proposed that uses mathematical concepts of the theory of cluster formation, the K-means, to automatically obtain the clusters of the NDVI values, to determine the use and occupation of the land. The implementations of the K- means method existing in specific software require the predefinition of the number of clusters, and the contribution of this methodology is the determination of the number of clusters automatically, without the need for interference of the decision maker, which may vary according to time and space from one image to another, as well as from one sensor to the next. Different sensors were selected to generalize this index classification: Thematic Mapper (TM) on board the Landsat-5 satellite; Operational Terra Imager (OLI) aboard the Landsat-8 satellite; MultiSpectral Instrument (MSI) aboard the Sentinel, level-2A satellite. The mapping and validation of algorithm are carried out in the northeast region of state of Mato Grosso do Sul, which, over 37 years (1984-2021) shows changes in its vegetation cover. The results obtained for the three periods, provided by the algorithm, better distinguished the spectral behavior of pixels referring to water classes, exposed soil and urban areas; on the other hand, the JENKS method generalized these classes, on the other hand, it better distinguished low-sized vegetation, natural vegetation and planted forests.
publishDate 2023
dc.date.none.fl_str_mv 2023-07-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artigo
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.periodicos.unimontes.br/index.php/cerrados/article/view/5068
10.46551/rc24482692202317
url https://www.periodicos.unimontes.br/index.php/cerrados/article/view/5068
identifier_str_mv 10.46551/rc24482692202317
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://www.periodicos.unimontes.br/index.php/cerrados/article/view/5068/6556
dc.rights.driver.fl_str_mv Copyright (c) 2023 Revista Cerrados
https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Revista Cerrados
https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora Unimontes
publisher.none.fl_str_mv Editora Unimontes
dc.source.none.fl_str_mv Revista Cerrados; v. 21 n. 02 (2023): Revista Cerrados; 03-34
2448-2692
1678-8346
reponame:Revista Cerrados (Montes Claros. Online)
instname:Universidade Estadual de Montes Claros (UNIMONTES)
instacron:UNIMONTES
instname_str Universidade Estadual de Montes Claros (UNIMONTES)
instacron_str UNIMONTES
institution UNIMONTES
reponame_str Revista Cerrados (Montes Claros. Online)
collection Revista Cerrados (Montes Claros. Online)
repository.name.fl_str_mv Revista Cerrados (Montes Claros. Online) - Universidade Estadual de Montes Claros (UNIMONTES)
repository.mail.fl_str_mv revista.cerrados@unimontes.br||portal.periodicos@unimontes.br.
_version_ 1809391650967912448