Mathematical modelling of the intra-annual behaviour of NDVI in the Caatinga Biome, Brazil
Main Author: | |
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Publication Date: | 2020 |
Other Authors: | , , , |
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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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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1799944134699515904 |