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Please use this identifier to cite or link to this item: https://rima.ufrrj.br/jspui/handle/20.500.14407/11291
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dc.contributor.authorJesus, Carolina Souza Leite de
dc.date.accessioned2023-12-22T01:49:45Z-
dc.date.available2023-12-22T01:49:45Z-
dc.date.issued2022-01-28
dc.identifier.citationJESUS, Carolina Souza Leite de. Risco de incêndios associado a mudanças da paisagem e eventos climáticos na Mata Atlântica. 2022. 41 f. Dissertação (Mestrado em Ciências Ambientais e Florestais) - Instituto de Florestas, Universidade Federal Rural do Rio de Janeiro, Seropédica, 2022.por
dc.identifier.urihttps://rima.ufrrj.br/jspui/handle/20.500.14407/11291-
dc.description.abstractA influência humana nas mudanças climáticas aumentou a ocorrência de eventos extremos e tornou ondas de calor e secas mais frequentes e severas, o que leva ao aumento do número de incêndios florestais. Esse trabalho tem o objetivo de desenvolver um modelo com o uso da estatística Autoregressive Integrated Moving Average Model (ARIMA) para avaliar o perigo de ocorrência de incêndios florestais para periodos climáticos passado e futuro, em função da mudança da paisagem e eventos climáticos, no Estado do Rio de Janeiro no futuro; a fim de prover informações que sirvam de subsídio para criação de políticas que visem evitar ou minimizar sua ocorrência. Foram utilizadas imagens do sensor Thematic Mapper e o sensor Enhanced Thematic Mapper no período de 1985 a 2015 com o objetivo de classificá-las em área antropizada e floresta. Foi utilizado um conjunto de variáveis meteorológicas em escala diária e mensal para o período de 1985 a 2015 para cálculo do índice F em escala mensal. O ARIMA foi utilizado para simular os dados observados e futuros do índice F até o ano de 2030. Os resultados mostram maiores valores de Normalized Difference Fraction Index (NDFI) em áreas ao sul e sudoeste do estado, coincidindo com as áreas de maior predominância de Mata Atlântica. As regiões mais degradadas estão a nordeste e norte e o ano de 2000 apresentou maior área de floresta degradada. Por meio da análise do índice F para o passado foi possível observar aumento gradativo de incêndios, que foram associados à ocorrência de eventos extremos, principalmente a La Niña. O uso da modelagem ARIMA permitiu identificar que houve mudança de classe de alto para muito alto quanto ao perigo de incêndio do passado e futuro. Em 2030 o valor mínimo do índice F atingiu 2.98, sendo considerado muito alto em maio e junho. Analisando todo o período futuro mensalmente, os maiores valores de perigo de incêndio foram encontrados nos meses de agosto e setembro. É importante que sejam tomadas medidas para minimizar os efeitos das mudanças climáticas, já que tais mudanças provocam maior ocorrência de eventos extremos, que por sua vez causam mais incêndios.por
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superiorpor
dc.formatapplication/pdf*
dc.languageporpor
dc.publisherUniversidade Federal Rural do Rio de Janeiropor
dc.rightsAcesso Abertopor
dc.subjectUso e cobertura da terrapor
dc.subjectAntropizaçãopor
dc.subjectModelos de previsãopor
dc.subjectMudanças climáticaspor
dc.subjectIncêndios florestaispor
dc.subjectLand use and cover changeeng
dc.subjectAnthropizationeng
dc.subjectForecastingeng
dc.subjectClimate changeseng
dc.subjectForest firespor
dc.titleRisco de incêndios associado a mudanças da paisagem e eventos climáticos na Mata Atlânticapor
dc.title.alternativeFire risk associated with landscape changes and weather events in the Atlantic Foresteng
dc.typeDissertaçãopor
dc.description.abstractOtherHuman influence on climate change has increased the occurrence of extreme events and made heat waves and droughts more frequent and severe, which leads to an increase in the number of forest fires. This work aims to develop a model using the Autoregressive Integrated Moving Average Model (ARIMA) to assess the danger of forest fires occurring for past and future climatic periods, as a function of landscape change and climatic events in the State of Rio de Janeiro in the future; to provide information that serve as subsidy for the creation of policies that aim to prevent or minimize its occurrence. Images from the Thematic Mapper sensor and the Enhanced Thematic Mapper sensor were used in the period from 1985 to 2015 in order to classify them as anthropogenic area and forest. A set of meteorological variables on daily and monthly scale for the period from 1985 to 2015 was used to calculate the F index on a monthly scale. ARIMA was used to simulate observed and future F index data up to the year 2030. The results show higher values of the Normalized Difference Fraction Index (NDFI) in areas to the south and southwest of the state, coinciding with the areas with the greatest predominance of Atlantic Forest. The most degraded regions are in the northeast and north and the year 2000 had the largest area of degraded forest. By analyzing the F index for the past, it was possible to observe a gradual increase in fires, which were associated with the occurrence of extreme events, mainly La Niña. The use of ARIMA modeling allowed us to identify that there was a change from high to very high class regarding the fire hazard of the past and future. In 2030, the minimum value of the F index reached 2.98, being considered very high in May and June. Analyzing the entire future period monthly, the highest fire hazard values were found in the months of August and September. It is important that measures are taken to minimize the effects of climate change, as such changes cause more extreme events to occur, which in turn cause more fires.eng
dc.contributor.advisor1Delgado, Rafael Coll
dc.contributor.advisor1ID001.729.560-21por
dc.contributor.advisor1IDhttps://orcid.org/0000-0002-3157-2277por
dc.contributor.advisor1Latteshttp://lattes.cnpq.br/1178948690201659por
dc.contributor.advisor-co1Silva Junior, Carlos Antonio da
dc.contributor.advisor-co1ID024.966.381-32por
dc.contributor.referee1Delgado, Rafael Coll
dc.contributor.referee1ID001.729.560-21por
dc.contributor.referee1IDhttps://orcid.org/0000-0002-3157-2277por
dc.contributor.referee1Latteshttp://lattes.cnpq.br/1178948690201659por
dc.contributor.referee2Wanderley, Henderson Silva
dc.contributor.referee2IDhttps://orcid.org/0000-0002-4031-3509por
dc.contributor.referee2Latteshttp://lattes.cnpq.br/9838743472295687por
dc.contributor.referee3Pereira, Marcos Gervasio
dc.contributor.referee3IDhttps://orcid.org/0000-0002-1402-3612por
dc.contributor.referee3Latteshttp://lattes.cnpq.br/3657759682534978por
dc.contributor.referee4Rodrigues, Rafael de Ávila
dc.contributor.referee4ID053.648.536-40por
dc.contributor.referee4Latteshttp://lattes.cnpq.br/8062645091909175por
dc.creator.ID137.716.787-90por
dc.creator.IDhttps://orcid.org/0000-0002-8637-3531por
dc.creator.Latteshttp://lattes.cnpq.br/8250781086495193por
dc.publisher.countryBrasilpor
dc.publisher.departmentInstituto de Florestaspor
dc.publisher.initialsUFRRJpor
dc.publisher.programPrograma de Pós-Graduação em Ciências Ambientais e Florestaispor
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dc.subject.cnpqRecursos Florestais e Engenharia Florestalpor
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