An Algorithm for Burned Area Detection in the Brazilian Cerrado Using 4 µm MODIS Imagery

Libonati, Renata; DaCamara, Carlos C.; Setzer, Alberto; Morelli, Fabiano; Melchiori, Arturo E.

doi:10.3390/rs71115782

Cited by 80 publications

(110 citation statements)

References 58 publications

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“…This peculiar result then points out a potential bias in model developments based on BA observation from global remote sensing, and DGVMs/fire module benchmarking for this region when using the large fire dataset only. Recent studies actually pointed out the BA underestimation from these global products when compared to finer resolution Landsat-based remote sensing analysis [63,66,67].…”

Section: Sensitivity Of the Seasonal Fdi/ba Relationship To Ba Datasetsmentioning

confidence: 99%

Spatial Pattern of the Seasonal Drought/Burned Area Relationship across Brazilian Biomes: Sensitivity to Drought Metrics and Global Remote-Sensing Fire Products

Nogueira

Rambal

Barbosa

et al. 2017

Climate

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Fires are complex processes having important impacts on biosphere/atmosphere interactions. The spatial and temporal pattern of fire activity is determined by complex feedbacks between climate and plant functioning through and biomass desiccation, usually estimated by fire danger indices (FDI) in official fire risk prevention services. Contrasted vegetation types from fire-prone Brazilian biomes may respond differently to soil water deficit during the fire season. Then, we propose to evaluate the burned area (BA)/FDI relationship across Brazil using most common FDIs and the main BA products from global remote sensing. We computed 12 standard FDIs-at 0.5 • resolution from 2002 to 2011 and used the monthly BA from four BA datasets-from the MODIS sensor (MCD45A1), the MERIS sensor (MERIS FIRE_CCI), the Global Fire Emission Database version 4 (GFED4) and version 4s including small fires (GFED4s). We performed a Principal Component Analysis (PCA) on the coefficients of determination (R 2 ) of the FDI/BA relationship to investigate the biome specificities of Brazilian biomes and the sensitivity to BA datasets. Good relationships (R 2 > 0.8) were observed for all BA datasets, except SPEI (R 2 < 0.2). We showed that FDIs computed from empirical water balances considering a lower soil capacity are more correlated to the seasonal pattern of fire occurrence in the Cerrado biome with contrasted adjustments between the western (early drying) and eastern part (late drying), while the fine fuel moisture index is more correlated to the fire seasonal pattern in Amazonia. The biome specificities of the FDI/BA relationship was evaluated with a general linear model. High accuracies in the biome distribution according to the FDI/BA relationship (>50%, p < 0.001) was observed in Amazonia and Cerrado, with lower accuracy (<32%, p < 0.001) in the Atlantic Forest and Caatinga. These results suggest that the FDI/BA relationship are biome-specific to explain the seasonal course of burned in Brazilian biomes, independently of the global BA product used. Selected FDIs should be used for fire danger forecast in each Brazilian biome.

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Section: Sensitivity Of the Seasonal Fdi/ba Relationship To Ba Datasetsmentioning

confidence: 99%

Spatial Pattern of the Seasonal Drought/Burned Area Relationship across Brazilian Biomes: Sensitivity to Drought Metrics and Global Remote-Sensing Fire Products

Nogueira

Rambal

Barbosa

et al. 2017

Climate

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“…Several studies relied on the use of remote sensing to map burned areas at a global/regional scale [5][6][7][8][9][10][11]. However, the variable persistence of burn scars within different vegetation types, and the spectral confusion with other phenomena (e.g., cloud shadowing) are some of the problems that still hamper accurate burned area mapping [12].…”

Section: Introductionmentioning

confidence: 99%

Burned Area Mapping in the Brazilian Savanna Using a One-Class Support Vector Machine Trained by Active Fires

Pereira

Libonati

et al. 2017

Remote Sensing

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Abstract:We used the Visible Infrared Imaging Radiometer Suite (VIIRS) active fire data (375 m spatial resolution) to automatically extract multispectral samples and train a One-Class Support Vector Machine for burned area mapping, and applied the resulting classification algorithm to 300-m spatial resolution imagery from the Project for On-Board Autonomy-Vegetation (PROBA-V). The active fire data were screened to prevent extraction of unrepresentative burned area samples and combined with surface reflectance bi-weekly composites to produce burned area maps. The procedure was applied over the Brazilian Cerrado savanna, validated with reference maps obtained from Landsat images and compared with the Collection 6 Moderate Resolution Imaging Spectrometer (MODIS) Burned Area product (MCD64A1) Results show that the algorithm developed improved the detection of small-sized scars and displayed results more similar to the reference data than MCD64A1. Unlike active fire-based region growing algorithms, the proposed approach allows for the detection and mapping of burn scars without active fires, thus eliminating a potential source of omission error. The burned area mapping approach presented here should facilitate the development of operational-automated burned area algorithms, and is very straightforward for implementation with other sensors.

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“…Com relação à região do Jalapão, Libonati et al (2015), que relatam a ocorrência de estação seca dos meses de maio a setembro, concluíram que anos com menores precipitações foram os que apresentaram maiores áreas queimadas, como também observado por Araújo e Ferreira (2015), com relação aos meses do ano. No entanto, Libonati et al (2015) destacam que além do clima, o fator humano exerce influência no regime do fogo.…”

Section: Discussionunclassified

“…No entanto, Libonati et al (2015) destacam que além do clima, o fator humano exerce influência no regime do fogo.…”

Section: Discussionunclassified

“…3,jul (IBGE, 2016). Libonati et al (2015) relatam que o regime do fogo no Cerrado brasileiro está principalmente relacionado com a interação do clima com atividades antrópicas e Nepstad et al (2008) destacam que a ocorrência de longos períodos de seca na região associada a avanço da fronteira agrícola são fatores que contribuem para o aumento de incêndios florestais e queimadas.…”

Section: Discussionunclassified

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Caracterização De Áreas Queimadas No Estado Do Tocantins No Ano De 2014

Carvalho

Batista

Coelho

et al. 2017

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ResumoO objetivo desta pesquisa foi caracterizar áreas queimadas no Tocantins, no ano de 2014, por meio de análise exploratória e de componentes principais, com uso de imagens de satélite dos meses de julho a outubro. Foram utilizadas bandas captadas por sensores do satélite Landsat-8: infravermelho médio (1,57-1,65 µm), infravermelho próximo (0,85-0,88 µm) e vermelho (0,64-0,67 µm), na composição RGB, com resolução espacial de 30 m. Foi realizado o processamento e interpretação visual das imagens para vetorização das áreas queimadas, que foi cruzada com bases de dados (precipitação média anual, pedologia, temperatura média anual, bacia hidrográfica, declividade, áreas protegidas, uso da terra e limites municipais), disponibilizadas pela Secretaria de Planejamento e Orçamento do Tocantins, e dados territoriais e socioeconômicos dos municípios tocantinenses. Estes últimos foram utilizados na análise de Componentes Principais (CP) que extraiu cinco CP que explicam 81,74% da variância dos dados. Esta análise indicou que a área queimada apresentou maior relação positiva com a área do município, quantidade de focos de calor, área de pastagens naturais e florestas. Pelas análises espaciais, nos locais de maior ocorrência de queimadas (regiões do Jalapão e da Ilha do Bananal), bem como no estado todo, a ocorrência de queimadas não pôde ser considerada aleatória. Foi possível concluir que além das condições ambientais intrínsecas do Cerrado, municípios com maiores áreas queimadas estiveram associados com maior Produto Interno Bruto (PIB) da agropecuária e menor PIB de serviços e indústria e menor número de habitantes. Palavras-chave: Cerrado; distribuição espacial; fogo; imagens Landsat. AbstractCharacterization of wildfires in Tocantins State on 2014 season. This aim of this research was to characterize the burned areas in the Tocantins, 2014 season, by the exploratory and principal component analysis, with use of satellite images between July and October. They were used the bands of sensors of Landsat-8 satellite: shortwave infrared (1.57-1.65 µm), near infrared (0.85-0.88 µm) and red (0.64-0.67 µm), in the RGB composition, with a spatial resolution of 30 meters. It was conducted the processing and visual interpretation of the images, for the vectorization of the burned area. These data were crossed with seven databases (annual average precipitation, pedology, annual average temperature, watershed, slope, protected area, land use and municipal boundaries), available on Secretaria de Planejamento e Orçamento do Tocantins, and with the territory and socioeconomic data of the Tocantins cities. These last data were used in principal component analysis (PCA) that were extracted five PC (data variance explained was 81.74%). These analyses revealed that burned area had shown highest positive relationship with city area, number of heat spots, natural pasture and forest areas. By the spatial analysis the burned area occurrence, in the Tocantins State (include regions with highest burned area, as Jalapão e Bannal island), canno...

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An Algorithm for Burned Area Detection in the Brazilian Cerrado Using 4 µm MODIS Imagery

Cited by 80 publications

References 58 publications

Spatial Pattern of the Seasonal Drought/Burned Area Relationship across Brazilian Biomes: Sensitivity to Drought Metrics and Global Remote-Sensing Fire Products

Spatial Pattern of the Seasonal Drought/Burned Area Relationship across Brazilian Biomes: Sensitivity to Drought Metrics and Global Remote-Sensing Fire Products

Burned Area Mapping in the Brazilian Savanna Using a One-Class Support Vector Machine Trained by Active Fires

Caracterização De Áreas Queimadas No Estado Do Tocantins No Ano De 2014

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