Correlações de longo alcance em séries temporais de focos de calor no Brasil
Autor(a) principal: | |
---|---|
Data de Publicação: | 2009 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da UFRPE |
Texto Completo: | http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5157 |
Resumo: | Vegetation fires represent a natural hazard with severe ecological, social, health and economic consequences. Every year fires burn millions of hectares of forest worldwide and their number have been increasing, principally because of the increase in population and combustion material. The preservation of the environment depends on global and regional policies and methods of prevention and suppression of fires. To establish these methods it is necessarily to know the profile of fires: spatial location, time of occurrence, burned area, why they occur, and how they initiate and propagate. Recently, various methods of Statistical Physics (including data analysis and computational models) have been applied to provide additional information about spatial and temporal distribution of fire sequences, which is crucial for assessing various consequences of burning, such as emissions of gasses and particulates to the atmosphere, loss of biodiversity, loss of wildlife habitat, soil erosion etc. Several satellite systems (with different capabilities in terms of spatial resolution, sensitivity, spectral bands, and times and frequency of overpasses) are currently available for monitoring different fire characteristics: dry areas that are susceptible to wild fire outbreak, actively flaming fires, burned area and smoke, and trace gas emissions. Hotspots are satellite image pixels with infrared intensity corresponding to burning vegetation. A hotspot may represent one fire, or be one of several hotspots representing a larger fire. Together with other satellite data, thenumber of hot-spots can be used to estimate the burned area. In this work we study the dynamics of hotspots using the Detrended Fluctuation Analysis (DFA) method, which serves to quantify correlations in non stationary time series. We analyze daily hotspot temporal series detected in Brazil by various satellites during the period 1998-2008. The results show the existence of power-law long-range correlations that represent an important property of the underlying stochastic process. This property, also found in climatic phenomena, should be incorporated in theoretical models and computer simulations of the fire dynamics. |
id |
URPE_4cf9b503a8912473d36d7a3b4093939b |
---|---|
oai_identifier_str |
oai:tede2:tede2/5157 |
network_acronym_str |
URPE |
network_name_str |
Biblioteca Digital de Teses e Dissertações da UFRPE |
repository_id_str |
|
spelling |
STOSIC, TatijanaSTOSIC, BorkoOLIVEIRA JÚNIOR, Wilson Rosa deFIGUEIRÊDO, Pedro Hugo dehttp://lattes.cnpq.br/0143286914678076SILVA, Luciano Rodrigues da2016-08-02T15:32:53Z2009-10-20SILVA, Luciano Rodrigues da. Correlações de longo alcance em séries temporais de focos de calor no Brasil. 2009. 57 f. Dissertação (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife.http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5157Vegetation fires represent a natural hazard with severe ecological, social, health and economic consequences. Every year fires burn millions of hectares of forest worldwide and their number have been increasing, principally because of the increase in population and combustion material. The preservation of the environment depends on global and regional policies and methods of prevention and suppression of fires. To establish these methods it is necessarily to know the profile of fires: spatial location, time of occurrence, burned area, why they occur, and how they initiate and propagate. Recently, various methods of Statistical Physics (including data analysis and computational models) have been applied to provide additional information about spatial and temporal distribution of fire sequences, which is crucial for assessing various consequences of burning, such as emissions of gasses and particulates to the atmosphere, loss of biodiversity, loss of wildlife habitat, soil erosion etc. Several satellite systems (with different capabilities in terms of spatial resolution, sensitivity, spectral bands, and times and frequency of overpasses) are currently available for monitoring different fire characteristics: dry areas that are susceptible to wild fire outbreak, actively flaming fires, burned area and smoke, and trace gas emissions. Hotspots are satellite image pixels with infrared intensity corresponding to burning vegetation. A hotspot may represent one fire, or be one of several hotspots representing a larger fire. Together with other satellite data, thenumber of hot-spots can be used to estimate the burned area. In this work we study the dynamics of hotspots using the Detrended Fluctuation Analysis (DFA) method, which serves to quantify correlations in non stationary time series. We analyze daily hotspot temporal series detected in Brazil by various satellites during the period 1998-2008. The results show the existence of power-law long-range correlations that represent an important property of the underlying stochastic process. This property, also found in climatic phenomena, should be incorporated in theoretical models and computer simulations of the fire dynamics.Incêndios em vegetação é um tipo de desastre natural com conseqüências ambientais, sociais econômicas, etc. Todos os anos incêndios destroem milhões de hectares das florestas e aumentam em número como conseqüência de vários fatores, principalmente de crescimento populacional e acúmulo de material combustível. A preservação de meio ambiente depende das políticas protecionistas globais e regionais adequadas às características de cada região. Para estabelecer essas políticas de controle e prevenção é necessário conhecer o perfil dos incêndios florestais: onde, quando e porque ocorrem. Além das estatísticas de ocorrências de incêndios os métodos emergentes da Física Estatística incluindo análise de dados e modelos computacionais, providenciam as informações adicionais sobre a distribuição e agrupamento espaço-temporal dos incêndios, que são cruciais para o estudo de várias conseqüências de fogo, como emissão de gases e partículas em atmosfera, perda de biodiversidade, erosão de solo, etc. Vários satélites (com características diferentes em termos de resolução espacial, bandas espectrais, tempo e freqüência de escaneamento) são disponíveis para monitoramento das varias características de fogos: áreas de risco, incêndios atualmente ativos, área queimada, fumaça, emissão de poluentes etc. Focos de calor são pixels na imagem de satélite com intensidade infravermelha correspondente a vegetação queimada. Um foco pode representar uma queimada, parte de um incêndio maior ou outras fontes de calor como, por exemplo, a reflexão de luz da superfície de um lago. O número de focos junto com outras informações providenciadas pelos satélites podem ser usados para estimar a área queimada, para detecção e monitoramento dos incêndios florestais, estimação de risco de fogo, e para avaliação da influencia de outros fatores ambientais. Neste trabalho estudamos a dinâmica de focos de calor no Brasil usando o método Detrended Fluctuation Analysis (DFA), desenvolvido para quantificar as correlações em séries temporais não estacionárias. Analisamos séries temporais diárias de focos de calor detectados no Brasil pelo vários satélites, durante o período 1998-2008. Os resultados mostram a existência de correlações de longo alcance persistentes, que representa uma propriedade importante dos processos estocásticos geradores desse fenômeno. Esta propriedade, também presente em fenômenos climáticos deveria ser incorporada em modelos teóricos e simulações computacionais de dinâmica de incêndios.Submitted by (ana.araujo@ufrpe.br) on 2016-08-02T15:32:53Z No. of bitstreams: 1 Luciano Rodrigues da Silva.pdf: 1477739 bytes, checksum: e1ea61981eacbff2c9319865f5504f91 (MD5)Made available in DSpace on 2016-08-02T15:32:53Z (GMT). No. of bitstreams: 1 Luciano Rodrigues da Silva.pdf: 1477739 bytes, checksum: e1ea61981eacbff2c9319865f5504f91 (MD5) Previous issue date: 2009-10-20application/pdfporUniversidade Federal Rural de PernambucoPrograma de Pós-Graduação em Biometria e Estatística AplicadaUFRPEBrasilDepartamento de Estatística e InformáticaDinâmica de focos de calorCorrelações de longo alcanceCorrelações de longo alcanceDynamics of hotspotsDetrended Fluctuation AnalysisLong-range correlationsCIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICACorrelações de longo alcance em séries temporais de focos de calor no Brasilinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis768382242446187918600600600-6774555140396120501-5836407828185143517info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFRPEinstname:Universidade Federal Rural de Pernambuco (UFRPE)instacron:UFRPELICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/5157/1/license.txtbd3efa91386c1718a7f26a329fdcb468MD51ORIGINALLuciano Rodrigues da Silva.pdfLuciano Rodrigues da Silva.pdfapplication/pdf1477739http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/5157/2/Luciano+Rodrigues+da+Silva.pdfe1ea61981eacbff2c9319865f5504f91MD52tede2/51572016-08-12 12:57:00.672oai:tede2: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Biblioteca Digital de Teses e Dissertaçõeshttp://www.tede2.ufrpe.br:8080/tede/PUBhttp://www.tede2.ufrpe.br:8080/oai/requestbdtd@ufrpe.br ||bdtd@ufrpe.bropendoar:2024-05-28T12:32:41.128068Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE)false |
dc.title.por.fl_str_mv |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
title |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
spellingShingle |
Correlações de longo alcance em séries temporais de focos de calor no Brasil SILVA, Luciano Rodrigues da Dinâmica de focos de calor Correlações de longo alcance Correlações de longo alcance Dynamics of hotspots Detrended Fluctuation Analysis Long-range correlations CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
title_short |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
title_full |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
title_fullStr |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
title_full_unstemmed |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
title_sort |
Correlações de longo alcance em séries temporais de focos de calor no Brasil |
author |
SILVA, Luciano Rodrigues da |
author_facet |
SILVA, Luciano Rodrigues da |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
STOSIC, Tatijana |
dc.contributor.advisor-co1.fl_str_mv |
STOSIC, Borko |
dc.contributor.referee1.fl_str_mv |
OLIVEIRA JÚNIOR, Wilson Rosa de |
dc.contributor.referee2.fl_str_mv |
FIGUEIRÊDO, Pedro Hugo de |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/0143286914678076 |
dc.contributor.author.fl_str_mv |
SILVA, Luciano Rodrigues da |
contributor_str_mv |
STOSIC, Tatijana STOSIC, Borko OLIVEIRA JÚNIOR, Wilson Rosa de FIGUEIRÊDO, Pedro Hugo de |
dc.subject.por.fl_str_mv |
Dinâmica de focos de calor Correlações de longo alcance Correlações de longo alcance |
topic |
Dinâmica de focos de calor Correlações de longo alcance Correlações de longo alcance Dynamics of hotspots Detrended Fluctuation Analysis Long-range correlations CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
dc.subject.eng.fl_str_mv |
Dynamics of hotspots Detrended Fluctuation Analysis Long-range correlations |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA |
description |
Vegetation fires represent a natural hazard with severe ecological, social, health and economic consequences. Every year fires burn millions of hectares of forest worldwide and their number have been increasing, principally because of the increase in population and combustion material. The preservation of the environment depends on global and regional policies and methods of prevention and suppression of fires. To establish these methods it is necessarily to know the profile of fires: spatial location, time of occurrence, burned area, why they occur, and how they initiate and propagate. Recently, various methods of Statistical Physics (including data analysis and computational models) have been applied to provide additional information about spatial and temporal distribution of fire sequences, which is crucial for assessing various consequences of burning, such as emissions of gasses and particulates to the atmosphere, loss of biodiversity, loss of wildlife habitat, soil erosion etc. Several satellite systems (with different capabilities in terms of spatial resolution, sensitivity, spectral bands, and times and frequency of overpasses) are currently available for monitoring different fire characteristics: dry areas that are susceptible to wild fire outbreak, actively flaming fires, burned area and smoke, and trace gas emissions. Hotspots are satellite image pixels with infrared intensity corresponding to burning vegetation. A hotspot may represent one fire, or be one of several hotspots representing a larger fire. Together with other satellite data, thenumber of hot-spots can be used to estimate the burned area. In this work we study the dynamics of hotspots using the Detrended Fluctuation Analysis (DFA) method, which serves to quantify correlations in non stationary time series. We analyze daily hotspot temporal series detected in Brazil by various satellites during the period 1998-2008. The results show the existence of power-law long-range correlations that represent an important property of the underlying stochastic process. This property, also found in climatic phenomena, should be incorporated in theoretical models and computer simulations of the fire dynamics. |
publishDate |
2009 |
dc.date.issued.fl_str_mv |
2009-10-20 |
dc.date.accessioned.fl_str_mv |
2016-08-02T15:32:53Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SILVA, Luciano Rodrigues da. Correlações de longo alcance em séries temporais de focos de calor no Brasil. 2009. 57 f. Dissertação (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife. |
dc.identifier.uri.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5157 |
identifier_str_mv |
SILVA, Luciano Rodrigues da. Correlações de longo alcance em séries temporais de focos de calor no Brasil. 2009. 57 f. Dissertação (Programa de Pós-Graduação em Biometria e Estatística Aplicada) - Universidade Federal Rural de Pernambuco, Recife. |
url |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/5157 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.program.fl_str_mv |
768382242446187918 |
dc.relation.confidence.fl_str_mv |
600 600 600 |
dc.relation.department.fl_str_mv |
-6774555140396120501 |
dc.relation.cnpq.fl_str_mv |
-5836407828185143517 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural de Pernambuco |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Biometria e Estatística Aplicada |
dc.publisher.initials.fl_str_mv |
UFRPE |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Departamento de Estatística e Informática |
publisher.none.fl_str_mv |
Universidade Federal Rural de Pernambuco |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da UFRPE instname:Universidade Federal Rural de Pernambuco (UFRPE) instacron:UFRPE |
instname_str |
Universidade Federal Rural de Pernambuco (UFRPE) |
instacron_str |
UFRPE |
institution |
UFRPE |
reponame_str |
Biblioteca Digital de Teses e Dissertações da UFRPE |
collection |
Biblioteca Digital de Teses e Dissertações da UFRPE |
bitstream.url.fl_str_mv |
http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/5157/1/license.txt http://www.tede2.ufrpe.br:8080/tede2/bitstream/tede2/5157/2/Luciano+Rodrigues+da+Silva.pdf |
bitstream.checksum.fl_str_mv |
bd3efa91386c1718a7f26a329fdcb468 e1ea61981eacbff2c9319865f5504f91 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da UFRPE - Universidade Federal Rural de Pernambuco (UFRPE) |
repository.mail.fl_str_mv |
bdtd@ufrpe.br ||bdtd@ufrpe.br |
_version_ |
1810102222665547776 |