Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data

Schroeder, Wilfrid; Prins, E. M.; Giglio, L.; Csiszar, Ivan; Schmidt, Christopher C.; Morisette, Jeffrey T.; Morton, Douglas C.

doi:10.1016/j.rse.2008.01.005

Cited by 282 publications

(204 citation statements)

References 29 publications

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“…First, the near-nadir detection performance of MODIS Terra has been comprehensively validated over a global range of biomes, fire regimes, and atmospheric conditions using coincident 30 m Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) observations [16,[44][45][46]. Second, the MODIS active fire products have previously been used to evaluate alternative SEVIRI active fire detection algorithms (e.g., [17,33,47,48]).…”

Section: Selection Of the Datasets And The Car As A Study Sitementioning

confidence: 99%

“…Within this central portion of the MODIS swath, where the MODIS active fire detection performance has been well characterised using co-incident ASTER observations [16,[44][45][46], SEVIRI's omission and commission rates in ROIs 1, 2, 3, and 4 were recalculated as 34%, 52%, 70%, and 82%, and 4%, 11%, 14%, and 10%, respectively. If accumulated over all ROIs, then SEVIRI's overall omission and commission rates in the CAR evaluated near MODIS nadir were 59% and 9%, respectively, which agree quite well with previously reported monthly values ranging between 54%-57% and 6%-8%, respectively [33].…”

Section: Impacts Of Viewing Geometry On Seviri's Detection Performancementioning

confidence: 99%

“…A larger IGFOV subtends a larger ground area and effectively reduces the fraction of a pixel occupied by fire. This in turn diminishes the ability of a geostationary sensor to discriminate smaller and/or lower intensity fires from the non-fire surroundings (e.g., [16]). In addition to this "low spatial resolution detection bias", cloud cover also prohibits geostationary sensors from acquiring near-continuous observations of fire activity by either completely obscuring the land surface or, at the very least, confounding the background temperature statistics required to define contextual thresholds [17,18].…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

et al. 2014

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Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI's omission rate can be attributed to a coupling between SEVIRI's low spatial resolution detection bias (i.e., the inability to detect fires below a OPEN ACCESSRemote Sens. 2014, 6 1891 certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI's commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring.

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Section: Selection Of the Datasets And The Car As A Study Sitementioning

confidence: 99%

Section: Impacts Of Viewing Geometry On Seviri's Detection Performancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

et al. 2014

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“…The MODIS sensor passes over Mato Grosso four times a day (on board TERRA and AQUA satellites). Although rather large omission and commission errors have been reported for the MODIS active fire detection in Southern America (Schroeder et al 2008), the dataset has still been widely considered to provide reliable information on the general spatio-temporal distribution of fire activity in the region. The 2000 burning season could not be covered with these data since the MODIS hotspots (TERRA satellite) are only available from November 2000 onwards.…”

Section: Mod/myd14 Active Fire Datasetmentioning

confidence: 99%

On the extent of fire-induced forest degradation in Mato Grosso, Brazilian Amazon, in 2000, 2005 and 2010

Miettinen

Shimabukuro

Beuchle

et al. 2016

Int. J. Wildland Fire

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Abstract. In this paper we analyse the extent of fire-induced forest degradation in Mato Grosso State, Brazil. We utilise a sample based approach used in a previous pan-tropical deforestation survey to derive information on land cover and burned areas in the two major biomes of Mato Grosso: Amazon and Cerrado. Land cover and burned area are mapped for three years (2000-2005-2010) over 77 sample sites (10 000 ha each) distributed systematically throughout the state which covers 90.337 Mha. Our results indicate continuing forest degradation by fires in the state and potentially increasing fire susceptibility of the Amazon forests, regardless of the decrease in deforestation. 2010 witnessed the most extensive fireinduced forest degradation (,300 000 ha) in the forests of the Amazon biome among the study years, regardless of the fact that the fire season was less severe than in 2005. Deforestation in the Amazon biome in Mato Grosso dropped from 590 000 ha year À1 in the 2000-2005 period to 190 000 ha year À1 in the second half of the decade. The findings of this study advocate the inclusion of forest fire effects into carbon accounting initiatives.

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“…A área de estudo abrange todo o território do estado de Minas Gerais, localizado na região sudeste do Brasil, com (SCHROEDER et al, 2008). A resolução espacial desses sensores no nadir é de 1,10 km 2 e a revisita ao mesmo ponto ocorre a cada 12 horas (LIU, 2007).…”

Section: áRea De Estudounclassified

Frequência espaço-temporal dos focos ativos em Minas Gerais durante o período de 1999 a 2009

Pereira

Barros

Pereira

et al. 2014

CERNE

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RESUMO:Neste estudo, objetivou-se resgatar o histórico de focos ativos no estado de Minas Gerais, durante os anos de 1999 e 2009 para uma análise exploratória dos dados. Por meio de análise temporal, procedeu-se a uma análise dos meses e anos em que os focos foram mais frequentes, e do período crítico de ocorrência de focos ativos. Já, a análise espacial considerou a frequência e a densidade de focos ativos nos Núcleos do Instituto Estadual de Florestas (IEF focos. O mês de maior frequência foi outubro com 24.149 focos registrados. As áreas com maior frequência, maior densidade e maior recorrência de focos ativos (neste último caso só em unidades de conservação), são consideradas mais críticas quanto aos focos ativos. Porém, a baixa frequência de focos e a alta densidade também são apontamentos de áreas críticas. Nas áreas de maior frequência de focos e baixa densidade, o tamanho da área influenciou diretamente na elevada ocorrência de focos ativos. Nessas áreas, sugerese uma análise de distribuição espacial para verificar se os focos ativos estão concentrados ou esparsos. O melhor cenário aqui apresentado é baixa frequência e densidade de focos ativos. SPACE-TIME FREQUENCY OF HOTSPOTS IN MINAS GERAIS FROM 1999 TO 2009ABSTRACT: The aim of this study was to rescue the history of hotspots in the state of Minas Gerais during the years of 1999 to 2009 for an exploratory data analysis. Through temporal analysis, we proceeded an analysis of the months and years where foci have been more frequent and of the critical period of occurrence of hotspots. The analysis considered the spatial frequency and the density of hotspots in the State Forestry Institute (IEF) nuclei. In the case of conservation units, it was also analyzed the annual recurrence. In total, 67,334 hotspots were detected in MG during the period from 1999 to 2009. Temporal analysis revealed that the year 2003 had the highest frequency, totaling 10,929 hotspots; the year 2009, in turn, had only 2,378 spots. October was the month with the largest frequency, with 24,149 of hotspots recorded. Nuclei with higher frequency, higher density and higher recurrence of hotspots in the case of conservation units, present the worst scenario, being considered as the most critical hotspots. However, low frequency of hotspots and high density are also indicatives of critical areas. In areas of high frequency of hotspots and low density, the size of the area directly influenced the high incidence of active hotspots. In these areas it is suggested an analysis of spatial distribution to check if hotspots are concentrated or sparse. The best scenario presented here is low frequency and low density of hotspots.

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Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data

Cited by 282 publications

References 29 publications

Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

Evaluating the SEVIRI Fire Thermal Anomaly Detection Algorithm across the Central African Republic Using the MODIS Active Fire Product

On the extent of fire-induced forest degradation in Mato Grosso, Brazilian Amazon, in 2000, 2005 and 2010

Frequência espaço-temporal dos focos ativos em Minas Gerais durante o período de 1999 a 2009

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