Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Ciência Florestal (Online) |
Texto Completo: | https://periodicos.ufsm.br/cienciaflorestal/article/view/70195 |
Resumo: | The indiscriminate use of fire, every year has been causing an imbalance in nature, which can be perceived globally. The remote sensing represents the main technological alternative in detecting, dimensioning and understanding the dynamics of fire. Thus, the objective of this study was to analyze the spatio-temporal distribution of the burned areas of the Caatinga Biome using the MODIS MCD64A1 product, from 2001 to 2018. For this, the monthly subsets of the Burned Area MCD64A1 product were used for the period of study. The Canadian Forest Service classification was also adopted, which defines the burned areas in five different classes: I (0-0.09 ha); II (0.1-4.0 ha); III (4.1-40.0 ha); IV (40.1-200.0 ha); V (>200.0 ha). The results achieved in this study reveal that the state of Piauí has a statistically higher average of fire occurrences and burned area in the times series. The months that had the largest burned areas in the biome were September, August and October and the greatest recurrences of burned areas from May to December. The burned area size classes that presented the highest occurrences were III, IV e V. The biome undergoes systematic growth of degradation, which enhances its fragility in the face of fire. |
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Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor dataVariabilidade espaço-temporal de ocorrência e recorrência de fogo no Bioma Caatinga usando dados do sensor MODISIncêndios florestaisSensoriamento remotoEstatísticas do fogoMonitoramento ambientalForest firesRemote sensingFire statisticsEnvironmental monitoringThe indiscriminate use of fire, every year has been causing an imbalance in nature, which can be perceived globally. The remote sensing represents the main technological alternative in detecting, dimensioning and understanding the dynamics of fire. Thus, the objective of this study was to analyze the spatio-temporal distribution of the burned areas of the Caatinga Biome using the MODIS MCD64A1 product, from 2001 to 2018. For this, the monthly subsets of the Burned Area MCD64A1 product were used for the period of study. The Canadian Forest Service classification was also adopted, which defines the burned areas in five different classes: I (0-0.09 ha); II (0.1-4.0 ha); III (4.1-40.0 ha); IV (40.1-200.0 ha); V (>200.0 ha). The results achieved in this study reveal that the state of Piauí has a statistically higher average of fire occurrences and burned area in the times series. The months that had the largest burned areas in the biome were September, August and October and the greatest recurrences of burned areas from May to December. The burned area size classes that presented the highest occurrences were III, IV e V. The biome undergoes systematic growth of degradation, which enhances its fragility in the face of fire.O uso do fogo de forma indiscriminada, a cada ano vem causando um desequilíbrio na natureza, que pode ser percebido em âmbito global. O sensoriamento remoto, representa a principal alternativa tecnológica na detecção, dimensionamento e na compreensão da dinâmica do fogo. Assim, o objetivo desse estudo foi analisar a distribuição espaço-temporal das áreas queimadas do Bioma Caatinga por meio do produto MODIS MCD64A1, no período de 2001 a 2018. Para isso, foram utilizados os subconjuntos mensais do produto Burned Area MCD64A1. Adotou-se também a classificação do Canadian Forest Service, no qual define as áreas queimadas em cinco classes diferentes: I (0-0,09 ha); II (0,1-4,0 ha); III (4,1-40,0 ha); IV (40,1-200,0 ha); V(>200,0 ha). Os resultados alcançados nesse estudo revelam que o estado do Piauí apresenta estatisticamente maior média de ocorrências de incêndios e área queimada na série temporal. Os meses que tiveram as maiores áreas queimadas no bioma foram setembro, agosto e outubro e maior recorrência de maio a dezembro. As classes de tamanho de área queimada que apresentaram maiores ocorrências foram III, IV e V. O bioma sofre sistemático crescimento de degradação, o que potencializa sua fragilidade ante ao fogo.Universidade Federal de Santa Maria2023-04-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/cienciaflorestal/article/view/7019510.5902/1980509870195Ciência Florestal; Vol. 33 No. 1 (2023): Publicação Contínua; e70195Ciência Florestal; v. 33 n. 1 (2023): Publicação Contínua; e701951980-50980103-9954reponame:Ciência Florestal (Online)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMporhttps://periodicos.ufsm.br/cienciaflorestal/article/view/70195/52354Copyright (c) 2022 Ciência Florestalhttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessSilva, Amanda Cavalcante daJuvanhol, Ronie SilvaMiranda, Jonathan da Rocha2023-06-07T17:40:37Zoai:ojs.pkp.sfu.ca:article/70195Revistahttp://www.ufsm.br/cienciaflorestal/ONGhttps://old.scielo.br/oai/scielo-oai.php||cienciaflorestal@ufsm.br|| cienciaflorestal@gmail.com|| cf@smail.ufsm.br1980-50980103-9954opendoar:2023-06-07T17:40:37Ciência Florestal (Online) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data Variabilidade espaço-temporal de ocorrência e recorrência de fogo no Bioma Caatinga usando dados do sensor MODIS |
title |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data |
spellingShingle |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data Silva, Amanda Cavalcante da Incêndios florestais Sensoriamento remoto Estatísticas do fogo Monitoramento ambiental Forest fires Remote sensing Fire statistics Environmental monitoring |
title_short |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data |
title_full |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data |
title_fullStr |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data |
title_full_unstemmed |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data |
title_sort |
Spatio-temporal variability of fire occurrence and recurrence in the Caatinga Biome using MODIS sensor data |
author |
Silva, Amanda Cavalcante da |
author_facet |
Silva, Amanda Cavalcante da Juvanhol, Ronie Silva Miranda, Jonathan da Rocha |
author_role |
author |
author2 |
Juvanhol, Ronie Silva Miranda, Jonathan da Rocha |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Silva, Amanda Cavalcante da Juvanhol, Ronie Silva Miranda, Jonathan da Rocha |
dc.subject.por.fl_str_mv |
Incêndios florestais Sensoriamento remoto Estatísticas do fogo Monitoramento ambiental Forest fires Remote sensing Fire statistics Environmental monitoring |
topic |
Incêndios florestais Sensoriamento remoto Estatísticas do fogo Monitoramento ambiental Forest fires Remote sensing Fire statistics Environmental monitoring |
description |
The indiscriminate use of fire, every year has been causing an imbalance in nature, which can be perceived globally. The remote sensing represents the main technological alternative in detecting, dimensioning and understanding the dynamics of fire. Thus, the objective of this study was to analyze the spatio-temporal distribution of the burned areas of the Caatinga Biome using the MODIS MCD64A1 product, from 2001 to 2018. For this, the monthly subsets of the Burned Area MCD64A1 product were used for the period of study. The Canadian Forest Service classification was also adopted, which defines the burned areas in five different classes: I (0-0.09 ha); II (0.1-4.0 ha); III (4.1-40.0 ha); IV (40.1-200.0 ha); V (>200.0 ha). The results achieved in this study reveal that the state of Piauí has a statistically higher average of fire occurrences and burned area in the times series. The months that had the largest burned areas in the biome were September, August and October and the greatest recurrences of burned areas from May to December. The burned area size classes that presented the highest occurrences were III, IV e V. The biome undergoes systematic growth of degradation, which enhances its fragility in the face of fire. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-04-10 |
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/70195 10.5902/1980509870195 |
url |
https://periodicos.ufsm.br/cienciaflorestal/article/view/70195 |
identifier_str_mv |
10.5902/1980509870195 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/cienciaflorestal/article/view/70195/52354 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2022 Ciência Florestal http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2022 Ciência Florestal http://creativecommons.org/licenses/by-nc/4.0 |
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. 33 No. 1 (2023): Publicação Contínua; e70195 Ciência Florestal; v. 33 n. 1 (2023): Publicação Contínua; e70195 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 |
_version_ |
1799944124301836288 |