Avaliação Geoecológica de Susceptibilidade à Ocorrência de Incêndios no Estado do Rio de Janeiro, Brasil

Fernandes, Manoel do Couto; Coura, Pedro Henrique Ferreira; Sousa, Gustavo Mota de; Avelar, André de Souza

doi:10.4322/floram.2011.050

Cited by 23 publications

(26 citation statements)

References 2 publications

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“…In 2001, Campos dos Goytacazes contributed with 79 fire foci (47 · 88%), and in the year 2013, there was a considerable increase of 265 foci (61 · 48%); according to Fernandes et al . (), this municipality lies in a region with high susceptibility to occurrence of annual fires, including drought and wet periods, predominance of pasture areas and slopes with high incidence of solar radiation and areas with significant water deficit, which feature the areas of greater susceptibility to occurrence of fires in the state. In addition, it is a large producer of sugarcane with burnt‐based handling.…”

Section: Resultsmentioning

confidence: 99%

“…The municipality of Teresópolis obtained 29 fire foci (19 · 10%), while the municipalities of Carmo and Duas Barras did not get any fire foci in the period. In 2001, Teresópolis contributed with 21 fire foci (22 · 64%), and in 2013, this number fell to 8 fire foci (9 · 09%) (Figure c) because the Serrana region has a lower susceptibility for having forested areas and slopes with lower incidence of solar radiation (Fernandes et al ., ). In Centro‐Sul Fluminense were accounted 95 fire foci (4 · 84%).…”

Section: Resultsmentioning

confidence: 99%

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Nonparametric Statistics Applied to Fire Foci Obtained by Meteorological Satellites and Their Relationship to the MCD12Q1 Product in the State of Rio de Janeiro, Southeast Brazil

et al. 2016

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This study shows the relationship between the fire foci and the MCD12Q1 product (MODIS) for the land use and occupation in the state of Rio de Janeiro (SRJ) and evaluates the growth and decay of trends fire foci through nonparametric tests, applied to the number of fire foci in the 2000–2012 period. The study period was divided into (1) 2001 to 2013 for assessment of the product MCD12Q1 back for the land use and occupation and application of nonparametric tests and (2) 2000 to 2012 for the descriptive statistics (total and percentage‐%) of fire foci geared for regional assessment. To evaluate growth trends and decay of fire foci, the nonparametric tests (Mann–Kendall and Pettitt) were utilized. Based on data obtained by Instituto Brasileiro de Geografia e Estatística (IBGE), the land use and occupation in the SRJ has been modified from the last two census years (1995 and 2006). The Mann–Kendall test was significant for the year 2001, with trends of 0 · 19 and 0 · 08 (Mann–Kendall). Fire foci for the years 2001 and 2013 grew with an increase of 0 · 05 and 0 · 01 per year, respectively. The Pettitt statistic test applied for the year 2001 showed that almost 70% of the studied municipalities were above the critical threshold, which has not occurred for the year 2013. The North Fluminense Region with 596 fire foci (30 · 35%) was the one with the largest number of fire foci, and the municipality of Campos dos Goytacazes was the largest contributor, with 344 fire foci (57 · 72%). The Pasturage class (MCD12Q1 product) had the biggest number of fire foci, with 354 foci (56 · 64%) in 2001 and 564 foci (42 · 28%) in 2013 and the largest amount in the north of the SRJ. The study indicated that there was a significant increase in average fire foci. Copyright © 2016 John Wiley & Sons, Ltd.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Nonparametric Statistics Applied to Fire Foci Obtained by Meteorological Satellites and Their Relationship to the MCD12Q1 Product in the State of Rio de Janeiro, Southeast Brazil

et al. 2016

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“…Therefore, the Markov chain can provide the likelihood of change increase or decrease in the vegetation, but can not present the spatial process of associated change dynamics (YANG et al, 2012). Pettitt's test showed the existence of no significant abrupt changes (NS), both of growth and decreasing vegetation to 5% probability into six regions of SRJ (Table 1) Serrana region is characterized by having serious constraints facing the urban occupation, given the slopes and complex topography (FERNANDES et al, 2011). Due to its physiography, much of the existing slopes in the region preserves the Atlantic Forest biome, such as the Parques Nacionais do Itatiaia (PNI), Serra da Bocaína, Serra dos Órgãos and Serra do Desengano (NUNES et al, 2015).…”

Section: Orbital Data From Enhanced Vegetation Index 2 (2001-2012)mentioning

confidence: 99%

EVI2 index trend applied to the vegetation of the state of Rio de Janeiro based on non-parametric tests and Markov chain

Góis¹,

Delgado²,

Oliveira‐Júnior³

et al. 2016

Biosci. J.

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ABSTRACT:The study aimed to assess the growth and decrease in vegetation trend by Enhanced Vegetation Index (EVI2) through the application of statistical tests and Markov's chain in the state of Rio de Janeiro (SRJ). Monthly data from EVI2 were calculated for the vegetations of the State of Rio de Janeiro (SRJ) from 2001 to 2012. Mann-Kendall (MK), Pettitt (P) and Estimator of Curvature Slope Sen (Se) tests assessed EVI2 trend, while the future scenarios were evaluated by Markov chain. Overall, there is an insignificant trend in vegetation growth in 75%, followed by a significant trend of decreasing in 25% of the regions. Pettitt's test showed that there is not significant (NS) abrupt changes, both growth and decreasing vegetation, and significant (

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“…Nos últimos 20 anos, o interesse por eventos de incêndios florestais aumentou consideravelmente, devido às consequências ambientais provocadas por sua ocorrência, principalmente em Áreas de Preservação Ambiental (APA) e nas Unidades de Conservação (UC) (Fernandes et al, 2001;Nunes et al, 2015). Os incêndios florestais podem ser de origem antrópica ou natural e aumentou significativamente por causa dos efeitos do Aquecimento Global e das alterações do clima provocados pelo modo de variabilidade climática El Niño -Oscilação Sul (ENOS) (Gutman et al, 2000;Hessl et al, 2004).…”

Section: Introductionunclassified

Relação Entre o Standardized Precipitation Index (SPI) e os Relatórios de Ocorrência de Incêndios (ROI) no Parque Nacional do Itatiaia

et al. 2017

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RESUMODados de focos de calor via satélites ambientais, de Sistemas Frontais (SF) e Zona de Convergência do Atlântico Sul (ZCAS), juntamente com o Standardized Precipitation Index (SPI) e os Relatórios de Ocorrência de Incêndios (ROI) no Parque Nacional do Itatiaia (PNI) foram avaliados. O SPI foi calculado com dados pluviométricos de três estações no PNI. Os dados dos SF e ZCAS foram obtidos via Climanálise. A regressão múltipla foi aplicada a ROI, SPI, SF e ZCAS de forma independente. A maior categoria do ROI ocorreu na classe C (81%), sendo os maiores percentuais no inverno (57,2%) e primavera (35,1%). Os meses críticos de focos de calor foram julho (17%), setembro (23,2%) e agosto (31,9%). Independente da estação, o SF (R2 = 0,75) se sobressaiu em relação a ZCAS (R2 = 0,43). O SF condiciona 80% das variações entre ROI e índice SPI anual, enquanto a ZCAS em apenas 40%.Palavras-chaves: sistemas produtores de chuva, incêndios florestais, índice de seca. Relationship Between Standardized Precipitation Index (SPI) and the FireOccurrence Reports (FOR) in Itatiaia National Park ABSTRACTWe evaluated fire foci data via environmental satellites, from Frontal Systems (FS) and South Atlantic Convergence Zone (SACZ) together with Standardized Precipitation Index (SPI) and Fire Occurrence Reports (FOR) in Itatiaia National Park (INP). SPI were computed with rainfall data from three stations in INP. SF and SACZ data were obtained via Climanálise. We applied independent multiple regression to FOR, SPI, SF and SACZ. Largest FOR occurred category in C class (81%), highest percentages during winter (57.2%) and spring (35.1%). The critical months to fire foci were July (17%), September (23.2%) and August (31.9%). Regardless of the season, FS (R 2 = 0.75) were highlighted to SACZ (R 2 = 0.43). SF conditioned 80% of variations between FOR and annual SPI index, while only 40% were due to SACZ.

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Avaliação Geoecológica de Susceptibilidade à Ocorrência de Incêndios no Estado do Rio de Janeiro, Brasil

Cited by 23 publications

References 2 publications

Nonparametric Statistics Applied to Fire Foci Obtained by Meteorological Satellites and Their Relationship to the MCD12Q1 Product in the State of Rio de Janeiro, Southeast Brazil

Nonparametric Statistics Applied to Fire Foci Obtained by Meteorological Satellites and Their Relationship to the MCD12Q1 Product in the State of Rio de Janeiro, Southeast Brazil

EVI2 index trend applied to the vegetation of the state of Rio de Janeiro based on non-parametric tests and Markov chain

Relação Entre o Standardized Precipitation Index (SPI) e os Relatórios de Ocorrência de Incêndios (ROI) no Parque Nacional do Itatiaia

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