Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil

Bibliographic Details
Main Author: Silva Filho, Rivaildo da
Publication Date: 2020
Other Authors: Vasconcelos, Rochele Sheila, Galvão, Carlos de Oliveira, Cunha, John Elton de Brito leite, Rufino, Iana Alexandra Alves
Format: Article
Language: por
Source: Ciência Florestal (Online)
Download full: https://periodicos.ufsm.br/cienciaflorestal/article/view/37279
Summary: Vegetation indexes from remote sensing images are often used for land-cover monitoring and identification of biomass changes. They are also very useful to describe the relationships between the phenological cycle and the carbon sequestration, which are climate change indicators. The Caatinga land-cover is very heterogeneous, making hard the understanding of the land cover processes in different scales (spatial and temporal), due to seasonalities and human actions. The Landsat series products usually can describe spatial land-cover variations, with a low temporal scale, so far. This study aims to improve the temporal representation of the land cover by Landsat images for a Caatinga area. This article presents an evaluation, using a mathematical approach of three-parameter functions to describe the Normalized Difference Vegetation Index (NDVI). Each function performance was evaluated by the reduced chi-square (χ²) and determination coefficient (R2) parameters. The analysis is performed for an annual period and considers land-cover changes by anthropic action. The Cauchy function seems the best option and presented an adjust up to 83% of the total (years and places), with an R² (average) of 0.82. The parameters of this function can be a valuable source for environmental studies in the Caatinga biome, supporting temporal analysis of the vegetation.
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spelling Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, BrazilRepresentação matemática do comportamento intra-anual do NDVI no Bioma CaatingaSemi-aridVegetation IndexCauchy functionGap series fillingSemiáridoÍndice de VegetaçãoCauchyPreenchimento de falhasVegetation indexes from remote sensing images are often used for land-cover monitoring and identification of biomass changes. They are also very useful to describe the relationships between the phenological cycle and the carbon sequestration, which are climate change indicators. The Caatinga land-cover is very heterogeneous, making hard the understanding of the land cover processes in different scales (spatial and temporal), due to seasonalities and human actions. The Landsat series products usually can describe spatial land-cover variations, with a low temporal scale, so far. This study aims to improve the temporal representation of the land cover by Landsat images for a Caatinga area. This article presents an evaluation, using a mathematical approach of three-parameter functions to describe the Normalized Difference Vegetation Index (NDVI). Each function performance was evaluated by the reduced chi-square (χ²) and determination coefficient (R2) parameters. The analysis is performed for an annual period and considers land-cover changes by anthropic action. The Cauchy function seems the best option and presented an adjust up to 83% of the total (years and places), with an R² (average) of 0.82. The parameters of this function can be a valuable source for environmental studies in the Caatinga biome, supporting temporal analysis of the vegetation.Os índices de vegetação obtidos por modelos, aplicados em imagens orbitais, são comumente utilizados para o monitoramento da cobertura do solo, sendo importantes para registrar alterações na biomassa, identificação do ciclo fenológico, relação com o sequestro de carbono e indicadores de mudanças climáticas. Na região do bioma Caatinga, a compreensão em escalas local e diária dos fenômenos que ocorrem na cobertura do solo é muito importante devido à sua heterogeneidade, sazonalidades e às múltiplas ações humanas. Neste ambiente, cresce a importância da representação temporal e espacial. Os satélites da série Landsat apresentam características adequadas para representar as variações espaciais, mas têm uma baixa amostragem temporal. Nesse sentido, o presente estudo tem como objetivo melhorar a representação temporal dos dados capturados pelos satélites Landsat para uma região do bioma Caatinga. Funções de três parâmetros são avaliadas para representação temporal matemática do Índice de Vegetação por Diferença Normalizada (NDVI), tendo a sua avaliação de desempenho realizada a partir dos parâmetros estatísticos qui-quadrado reduzido (χ²) e coeficiente de determinação (R2). A análise considera o estado de alteração da cobertura do solo pela ação antrópica e o regime pluviométrico anual. A função Cauchy apresentou melhor desempenho, ajustando-se bem a 83% dos anos e locais analisados, obtendo um R² médio de 0,82. Os parâmetros da função de melhor desempenho identificada neste estudo podem ser uma valiosa fonte de informações para estudos ambientais na Caatinga que precisem avaliar o comportamento temporal da vegetação.Universidade Federal de Santa Maria2020-06-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/3727910.5902/1980509837279Ciência Florestal; Vol. 30 No. 2 (2020); 473-488Ciência Florestal; v. 30 n. 2 (2020); 473-4881980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/37279/37279Copyright (c) 2020 Ciência Florestalinfo:eu-repo/semantics/openAccessSilva Filho, Rivaildo daVasconcelos, Rochele SheilaGalvão, Carlos de OliveiraCunha, John Elton de Brito leiteRufino, Iana Alexandra Alves2021-05-20T04:00:46Zoai:ojs.pkp.sfu.ca:article/37279Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2021-05-20T04:00:46Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false
dc.title.none.fl_str_mv Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
Representação matemática do comportamento intra-anual do NDVI no Bioma Caatinga
title Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
spellingShingle Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
Silva Filho, Rivaildo da
Semi-arid
Vegetation Index
Cauchy function
Gap series filling
Semiárido
Índice de Vegetação
Cauchy
Preenchimento de falhas
title_short Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
title_full Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
title_fullStr Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
title_full_unstemmed Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
title_sort Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
author Silva Filho, Rivaildo da
author_facet Silva Filho, Rivaildo da
Vasconcelos, Rochele Sheila
Galvão, Carlos de Oliveira
Cunha, John Elton de Brito leite
Rufino, Iana Alexandra Alves
author_role author
author2 Vasconcelos, Rochele Sheila
Galvão, Carlos de Oliveira
Cunha, John Elton de Brito leite
Rufino, Iana Alexandra Alves
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Silva Filho, Rivaildo da
Vasconcelos, Rochele Sheila
Galvão, Carlos de Oliveira
Cunha, John Elton de Brito leite
Rufino, Iana Alexandra Alves
dc.subject.por.fl_str_mv Semi-arid
Vegetation Index
Cauchy function
Gap series filling
Semiárido
Índice de Vegetação
Cauchy
Preenchimento de falhas
topic Semi-arid
Vegetation Index
Cauchy function
Gap series filling
Semiárido
Índice de Vegetação
Cauchy
Preenchimento de falhas
description Vegetation indexes from remote sensing images are often used for land-cover monitoring and identification of biomass changes. They are also very useful to describe the relationships between the phenological cycle and the carbon sequestration, which are climate change indicators. The Caatinga land-cover is very heterogeneous, making hard the understanding of the land cover processes in different scales (spatial and temporal), due to seasonalities and human actions. The Landsat series products usually can describe spatial land-cover variations, with a low temporal scale, so far. This study aims to improve the temporal representation of the land cover by Landsat images for a Caatinga area. This article presents an evaluation, using a mathematical approach of three-parameter functions to describe the Normalized Difference Vegetation Index (NDVI). Each function performance was evaluated by the reduced chi-square (χ²) and determination coefficient (R2) parameters. The analysis is performed for an annual period and considers land-cover changes by anthropic action. The Cauchy function seems the best option and presented an adjust up to 83% of the total (years and places), with an R² (average) of 0.82. The parameters of this function can be a valuable source for environmental studies in the Caatinga biome, supporting temporal analysis of the vegetation.
publishDate 2020
dc.date.none.fl_str_mv 2020-06-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/37279
10.5902/1980509837279
url https://periodicos.ufsm.br/cienciaflorestal/article/view/37279
identifier_str_mv 10.5902/1980509837279
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ufsm.br/cienciaflorestal/article/view/37279/37279
dc.rights.driver.fl_str_mv Copyright (c) 2020 Ciência Florestal
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 Ciência Florestal
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Santa Maria
publisher.none.fl_str_mv Universidade Federal de Santa Maria
dc.source.none.fl_str_mv Ciência Florestal; Vol. 30 No. 2 (2020); 473-488
Ciência Florestal; v. 30 n. 2 (2020); 473-488
1980-5098
0103-9954
reponame:Ciência Florestal (Online)
instname:Universidade Federal de Santa Maria (UFSM)
instacron:UFSM
instname_str Universidade Federal de Santa Maria (UFSM)
instacron_str UFSM
institution UFSM
reponame_str Ciência Florestal (Online)
collection Ciência Florestal (Online)
repository.name.fl_str_mv Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)
repository.mail.fl_str_mv ||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br
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