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Pixel-based accuracy assessment curve for Siberia with thc 95% exact confidence intervals The probability of omission error as a function of minimum firc size exprcssed as the number of ASTER fire pixels within the MODIS footprint.
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This paper discusses the process of validating active fire "yes/no" binary fire detection products from moderate-resolution satellite sensors. General concepts and practical issues are illustrated by the validation of the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product in Siberia. Coincident Advanced Spaceborne Thermal Emi...
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Citations
... As described by [49][50][51][52], the detection algorithm of active fire uses native (i.e., unprojected swath) 4-, 11-, and 12-μm brightness temperatures derived from the corresponding 1-km MODIS channels, denoted by T4, T11, and T12, respectively. And, for daytime observations, 0.65-, 0.86-, and 2.1-μm reflectance (denoted by ρ0. ...
The estimation of the danger of fire is a way to quantify the potential or capacity of a fire to start, spread and cause damage. The relationships between the Canadian Fire Weather Index (FWI) System components and the monthly burned area as well as the number of active fire which has taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua/TERRA were investigated in 32 Guinean stations between 2003 and 2013. A statistical analysis based on a multi-linear regression model was used to estimate the skills of FWI components on the predictability of burned area and active fire. The goal of the detection algorithm is to identify "fire pixels" that contain one or more active burning fires at the time of the satellite overpass. This statistical analysis gave performances explaining between 16 to 79% of the variance for the burned areas and between 29 and 82% of the variance for the number of fires (P<0.0001) at lag 0. Respectively 16 to 79 % and 29 to 82 % of the variance of the burned areas and variance for the number of fires (P<0.0001) at lag0 can be explained based on the same statistical analysis. All the combinations used gave significant performances to predict the burned areas and active fire on the monthly timescale in all stations excepted Fria and Yomou where the predictability of the burned areas was not obvious. We obtained a significant correlation between the average over all of the stations of burned areas, active fires and FWI composites with percentage of variance between (75 to 84% and 29 to 77%) for active fires 35 and burned areas at lag0 respectively. While for burned area peak (January), the skill of the predictability remains significant only one month in advance, for the active fires, the model remains skilful 1 to 3 months in advance. The results show strong performances of the linear model in the sites with a homogeneous distribution of the vegetation cover like the case of the regions of Upper Guinea where one finds vast expanses of Savannah. Results also showed that active fires are more related to fire behavior indices while the burned areas are related to the fine fuel moisture codes. These outcomes have implications for seasonal forecasting of active fire events and burned areas based on FWI components, as significant predictability is found from 1 to 3 months and one month before respectively. These results also open up perspectives on the possibility of using forecasting models to project future and past events in order to better understand the long-term effects of bush fire on ecosystems, biodiversity and on the pollution of the environment.
... Since the early 2000s, National Aeronautics and Space Administration (NASA) has provided active fire products derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images (Giglio et al., 2003;Justice et al., 2002) that are based on an absolute and contextual threshold algorithm that considers the thermal characteristics of satellite pixels affected by wildfires (Giglio et al., 2003;Justice et al., 2002). Active fire products based on the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite images have been provided since the 2010s (Csiszar et al., 2006;Schroeder et al., 2014). Nearly real-time MODIS and VIIRS active fire products are available in Fire Information for Resource Management System (FIRMS) and are replaced by standard science quality data after the lag time of two to three months (Davies et al., 2012;Davies et al., 2008). ...
... Over the past two decades, MODIS products have been recognized as the most widely used and reliable satellite-based active fire products (Freeborn et al., 2014;Giglio et al., 2003;Morisette et al., 2005;Schroeder et al., 2008a). Multiple updates to the MODIS algorithm have been applied in various regions (Cheng et al., 2013;Csiszar et al., 2006;Hawbaker et al., 2008;Morisette et al., 2005;Schroeder et al., 2008a). Both products provide a confidence level, which is given in a percentage for the MODIS product, and in three categorical confidence levels of low, medium, and high for the VIIRS one. ...
... One is referred to as active fire detection, where binary fire maps ("yes/no") are derived using flagging pixels. The other group is where satellite pixels are partitioned into smouldering, flaming and unburned areas by assigning temperature values [115]. Csiszar et al. [115] investigated the validation of MODIS active fire products in Siberia. ...
... The other group is where satellite pixels are partitioned into smouldering, flaming and unburned areas by assigning temperature values [115]. Csiszar et al. [115] investigated the validation of MODIS active fire products in Siberia. Spatial patterns of flaming were characterised at the pixel level using ASTER imagery. ...
... Satellite, Sensors and Data Content, Analysis Techniques and Remarks [114] TERRA and AQUA satellites, MODIS Proposed improvements to the MODIS fire detection algorithms by integrating a radiance-based approach [115] MODIS, ASTER Investigated the validation of MODIS active fire products in Siberia. Spatial patterns of flaming were characterised at the pixel level using ASTER imagery, and a cluster-based analysis was proposed. ...
Bushfires are classified as catastrophic disasters capable of inflicting significant destruction. The key detrimental consequences of bushfires include the loss of human lives, trauma within communities, economic losses and environmental damage. For example, the estimated economic loss from the September 2019 to March 2020 bushfires in New South Wales (Australia) was about AUD 110 billion, including more than 3000 burned houses. There has been a notable increase in both the frequency and intensity of bushfires, as clearly demonstrated by recent bushfire events. Bushfires are an intricate phenomenon that transpires across various spatial and temporal scales. Further, the changing circumstances of landscapes, vegetation patterns, weather conditions and ecosystems account for the complexity. Therefore, continual attention is essential for the development of bushfire management strategies. In this context, this paper undertakes a comprehensive literature review of bushfire management strategies, encompassing aspects such as bushfire prediction, detection, suppression and prevention. Based on the review, a bushfire management framework is proposed that can eliminate or successfully mitigate the consequences of bushfires. Further, the paper delves into the domains of fire weather conditions, the initiation of bushfires and the adverse consequences stemming from these fires. Both terrestrial and aerial remote sensing methods have proven to be effective in predicting and detecting bushfires. Nevertheless, a simple unique solution cannot be proposed for bushfire management. Changing weather conditions, topography and the geographic mix of asset types need to be considered when deciding on bushfire management strategies and their breadth and depth of application.
... This approach enables precise localization of the fire area with a low margin of error. In another study, Csizar et al. [83] propose a fire detection method that combines ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and MODIS. By adapting the fire mask proposed by MODIS with ASTER's broader coverage, the method achieves improved accuracy in detecting fire areas in Northern Eurasia. ...
Nowadays, the challenges related to technological and environmental development are becoming increasingly complex. Among the environmentally significant issues, wildfires pose a serious threat to the global ecosystem. The damages inflicted upon forests are manifold, leading not only to the destruction of terrestrial ecosystems but also to climate changes. Consequently, reducing their impact on both people and nature requires the adoption of effective approaches for prevention, early warning, and well-coordinated interventions. This document presents an analysis of the evolution of various technologies used in the detection, monitoring, and prevention of forest fires from past years to the present. It highlights the strengths, limitations, and future developments in this field. Forest fires have emerged as a critical environmental concern due to their devastating effects on ecosystems and the potential repercussions on the climate. Understanding the evolution of technology in addressing this issue is essential to formulate more effective strategies for mitigating and preventing wildfires.
... The accuracy of the data was validated by numerous independent investigations using the high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) image. Detailed information about this issue can be found elsewhere [25][26][27][28]. ...
Understanding the impact of drought on fire dynamics is crucial for assessing the potential effects of climate change on wildfire activity in China. In this study, we present a series of multiple linear regression (MLR) models linking burned area (BA) during mainland China’s fire season from 2001 to 2019, across seven regions, to concurrent drought, antecedent drought, and time trend. We estimated burned area using Collection 6 Moderate Resolution Imaging Spectradiometer (MODIS) and drought indicators using either the Standardized Precipitation Evapotranspiration Index (SPEI) or the self-calibrated Palmer Drought Severity Index (sc-PDSI). Our findings indicate that the wildfire season displays a spatial variation pattern that increases with latitude, with the Northeast China (NEC), North China (NC), and Central China (CC) regions identified as the primary areas of wildfire occurrence. Concurrent and antecedent drought conditions were found to have varying effects across regions, with concurrent drought as the dominant predictor for NEC and Southeast China (SEC) regions and antecedent drought as the key predictor for most regions. We also found that the Northwest China (NWC) and CC regions exhibit a gradual decrease in burned area over time, while the NEC region showed a slight increase. Our multiple linear regression models exhibited a notable level of predictive power, as evidenced by the average correlation coefficient of 0.63 between the leave-one-out cross-validation predictions and observed values. In particular, the NEC, NWC, and CC regions demonstrated strong correlations of 0.88, 0.80, and 0.76, respectively. This indicates the potential of our models to contribute to the prediction of future wildfire occurrences and the development of effective wildfire management and prevention strategies. Nevertheless, the intricate relationship among fire, climate change, human activities, and vegetation distribution may limit the generalizability of these findings to other conditions. Consequently, future research should consider a broad range of factors to develop more comprehensive models.
... The response of different resolution sensors to the same fire may be different, which is often discussed when active fire detection results from coarser-resolution satellite data are evaluated using finer-resolution data. For example, the 30 m Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard the National Aeronautics and Space Administration (NASA) Terra satellite was successfully used to detect active fires to validate fire detections from MODIS and the previous Geostationary Operational Environmental Satellite [26][27][28][29][30]. A logistic regression model can be used to estimate the probability of coarse-resolution fire detection in relation to the number of fine-resolution fire pixels contained within the coarse pixel. ...
Wildfires have a significant impact on the atmosphere, terrestrial ecosystems, and society. Real-time monitoring of wildfire locations is crucial in fighting wildfires and reducing human casualties and property damage. Geostationary satellites offer the advantage of high temporal resolution and are gradually being used for real-time fire detection. In this study, we constructed a fire label dataset using the stable VNP14IMG fire product and used the random forest (RF) model for fire detection based on Himawari-8 multiband data. The band calculation features related brightness temperature, spatial features, and auxiliary data as input used in this framework for model training. We also used a recursive feature elimination method to evaluate the impact of these features on model accuracy and to exclude redundant features. The daytime and nighttime RF models (RF-D/RF-N) are separately constructed to analyze their applicability. Finally, we extensively evaluated the model performance by comparing them with the Japan Aerospace Exploration Agency (JAXA) wildfire product. The RF models exhibited higher accuracy, with recall and precision rates of 95.62% and 59%, respectively, and the recall rate for small fires was 19.44% higher than that of the JAXA wildfire product. Adding band calculation features and spatial features, as well as feature selection, effectively reduced the overfitting and improved the model’s generalization ability. The RF-D model had higher fire detection accuracy than the RF-N model. Omission errors and commission errors were mainly concentrated in the adjacent pixels of the fire clusters. In conclusion, our VIIRS fire product and Himawari-8 data-based fire detection model can monitor the fire location in real time and has excellent detection capability for small fires, making it highly significant for fire detection.
... Patchy, irregular-shaped, short, small or low-intensity fires may be underestimated (de Klerk, 2008;Hawbaker et al., 2008). The MCD14ML algorithm was developed by Giglio et al. (2003) -using swath products (MOD/MYD14) rather than tiled products (MOD/MYD14A1) -, and validated by Morisette et al. (2005) have been registering daily hot pixels since the year 2000, and have been extensively validated (Morisette et al., 2005;Csiszar et al., 2006;de Klerk, 2008;Hawbaker et al., 2008). The collection 6 of the data addresses previous limitations such as frequent false alarms caused by small clearings in the Amazon forests (Friedl et al., 2010), which is particularly helpful for our purpose. ...
... Two fire events are considered neighbours if they are in the same 3-dimensional (latitude, longitude, time) Moore neighbourhood with no spatial or temporal gaps (Fig. III-1b). The MOD/MYD14A1 fire product offers an indication of fire activity and has been extensively validated (Morisette et al., 2005;Csiszar et al., 2006;Hawbaker et al., 2008;de Klerk, 2008). The collection 6 of the data addresses previous limitations such as frequent false alarms caused by small clearings in the Amazon forests (Friedl et al., 2010), which is particularly helpful for our purpose. ...
Das Amazonasgebiet hat in den letzten Jahrzehnten eine Intensivierung der menschlichen Aktivitäten erfahren, die in Verbindung mit häufigen schweren Dürren die Umwelt anfälliger für Brände gemacht hat. In dieser Dissertation wurden Fernerkundungsdaten analysiert, um die räumlich-zeitliche Verteilung der Feuer in den letzten 20 Jahren im brasilianischen Amazonasgebiet umfassend zu untersuchen und die verschiedenen Brandursachen zu entschlüsseln. (I) Die erste Forschungsarbeit wertete die Verteilung der verbrannten Fläche aus und zeigte, dass die meisten Brände auf bewirtschafteten Weiden und in den immergrünen Tropenwäldern auftraten, was die Behauptung stützt, dass ihr Auftreten stark auf anthropogene Landnutzungsänderungen reagiert. Die Ergebnisse zeigten auch, dass weder Entwaldung noch Walddegradierung mit Waldbränden korrelierte, wohl aber Feuer, die auf Weiden oder Ackerflächen gelegt wurden und in den angrenzenden Wald übergesprungen sind. (II) Die zweite Forschungsarbeit analysierte einzelne Brände, die durch den auf komplexen Netzwerken basierenden FireTracks-Algorithmus identifiziert wurden. Der Algorithmus wurde verwendet, um Feuerregime für sechs verschiedene Landnutzungsklassen zu ermitteln. Die integrierte Größe, Dauer, Intensität und Ausbreitungsrate dieser räumlich-zeitlichen Brandcluster in den verschiedenen Landnutzungstypen zeigte auf, wie seltene Waldbrände, die natürlicherweise nicht in immergrünen tropischen Wäldern vorkommen, sich zu einem Feuerregime entwickelten, das für Savannenbrände typisch ist. (III) Die dritte Forschungsarbeit analysierte extreme, d. h. die intensivsten Einzelfeuer in immergrünen tropischen Wäldern, und zeigte deren großen Anteil an der insgesamt verbrannten Waldfläche. Während der globale Klimawandel das Potenzial hat, die Trockenheit zu verstärken, sind die anthropogenen Ursachen der Waldzerstörung die Zündquellen, die die Verteilung extremer Brände in den empfindlichen tropischen Wäldern bestimmen.
... Satellite fire detection is performed using algorithms that measures the emission of midinfrared radiation from fires (GIGLIO et al. 2006). ...
... Such data from the reference satellites, mostly from the AQUA, have already been used by several researchers to describe the spatiotemporal variation of wildland fire occurrence at global level (eg. Csiszar et al., 2005;Giglio et al., 2006), at continental level (eg. Csiszar et al., 2006;, at country level (eg. ...
... Csiszar et al., 2005;Giglio et al., 2006), at continental level (eg. Csiszar et al., 2006;, at country level (eg. Matin et al., 2017;Hawbaker, 2008;Xia et al., 2013); at state level (eg. ...
Since 2002, the AQUA (MODIS) satellite has been used as a “reference” by the Brazilian National Institute of Space Research to analyze spatial and temporal trends over fire pixel detection in all South America. Since this satellite will stop providing data in the near future, in order to continue the trend analyzes it will be necessary an integration and adjustment between AQUA fire pixels data with the data from the next reference satellite: the Suomi NPP (VIIRS). Therefore, this study has as objective to analyze the differences in fire pixels detection from AQUA and S-NPP satellites at country, state and municipal level. During the 10 years period assessed, the S-NPP detected, on average, 5.13 times more fire pixels than the AQUA on the South America continent. Venezuela was the country with the highest S-NPP/AQUA ratio (6.81) and Chile the lowest (3.87). When analyzing the fire pixels only in the Brazilian states, Acre presented the lowest S-NPP/AQUA ratio (3,72), while in Sergipe the highest (10,07). In the Pará’s municipalities, the lowest S-NPP/AQUA ratio was in Quatipuru (2.84), while the highest in Ananindeua (11.25). Despite the differences in the ratio, the number of fire pixels detected by the AQUA and S-NPP presented, almost in all cases, a significant correlation. Only the smallest municipalities in Pará had no significant correlation, probably due to low data and/or detection location errors. The changes in the S-NPP/AQUA ratio occurred probably due to factors such as sampling characteristics (pixel enlargement away from nadir), geographic area analyzed, timing of satellite overpasses, predominant type of vegetation, and others. Therefore, there isn’t one unique formula to adjust AQUA data to S-NPP, variations will persist at different locations. Diferenças quantitativas na detecção de pixels de fogo usando os satélites Aqua/MODIS e NPP-Suomi/VIIRS RESUMODesde 2002, o satélite AQUA (MODIS) tem sido usado como “referência” pelo Instituto Nacional de Pesquisas Espaciais do Brasil para analisar tendências espaciais e temporais na detecção de pixels de fogo em toda a América do Sul. Uma vez que este satélite deixará de fornecer dados em um futuro próximo, para continuar as análises de tendências, será necessária uma integração e ajuste entre os dados de pixels de fogo AQUA com os dados do próximo satélite de referência: o Suomi NPP (VIIRS). Portanto, este estudo tem como objetivo analisar as diferenças na detecção de pixels de incêndio dos satélites AQUA e S-NPP em nível nacional, estadual e municipal. Durante o período de 10 anos avaliado, o S-NPP detectou, em média, 5,13 vezes mais pixels de incêndio do que o AQUA no continente sul-americano. A Venezuela foi o país com a maior relação S-NPP/AQUA (6,81) e o Chile a menor (3,87). Ao analisar os pixels de fogo apenas nos estados brasileiros, o Acre apresentou a menor relação S-NPP/AQUA (3,72), enquanto em Sergipe a maior (10,07). Nos municípios paraenses, a menor relação S-NPP/AQUA foi em Quatipuru (2,84), enquanto a maior em Ananindeua (11,25). Apesar das diferenças na proporção, o número de pixels de incêndio detectados pelo AQUA e S-NPP apresentou, quase em todos os casos, uma correlação significativa. Apenas os menores municípios do Pará não tiveram correlação significativa, provavelmente devido a poucos dados e/ou erros de localização de detecção. As mudanças na relação S-NPP/AQUA ocorreram provavelmente devido a fatores como características da amostragem (alargamento dos pixels a partir do nadir), área geográfica analisada, tempo de passagem dos satélites, tipo de vegetação predominante, entre outros. Portanto, não há uma fórmula única para ajustar os dados AQUA para S-NPP, as variações persistirão em diferentes locais.Palavras-chave: incêndio florestal; sensoriamento remoto; Prevenção de incêndio.
... Two fire events are considered neighbours if they are in the same 3-dimensional (latitude, longitude, time) Moore neighbourhood with no spatial or temporal gaps (Fig. 1b). The MOD/MYD14A1 fire product offers an indication of fire activity and has been extensively validated (Morisette et al. 2005;Csiszar et al. 2006;Hawbaker et al. 2008;de Klerk 2008). The collection 6 of the data addresses previous limitations such as frequent false alarms caused by small clearings in the Amazon forests (Friedl et al. 2010), which is particularly helpful for our purpose. ...
Humans profoundly alter fire regimes both directly, by introducing changes in fuel dynamics and ignitions, and indirectly, by increasing the release of greenhouse gases and aerosols from fires, which can alter regional climate and, as a consequence, modify fuel moisture and availability. Interactions between vegetation dynamics, regional climate change and anthropogenic pressure lead to high heterogeneity in the spatio-temporal fire distribution. We use the new FireTracks Scientific Dataset that tracks the spatio-temporal development of individual fires to analyse fire regimes in the Brazilian Legal Amazon over the period 2002–2020. We analyse fire size, duration, intensity and rate of spread in six different land-cover classes. Particular combinations of fire features determine the dominant and characteristic fire regime in each of them. We find that fires in savannas and evergreen forests burn the largest areas and are the most long lasting. Forest fires have the potential for burning at the highest intensities, whereas higher rates of spread are found in savannas. Woody savanna and grassland fires are usually affected by smaller, shorter, less-intense fires compared with fires in evergreen forest and savanna. However, fires in grasslands can burn at rates of spread as high as savanna fires as a result of the easily flammable fuel. We observe that fires
in deciduous forests and croplands are generally small, short and low intense, although the latter can sustain high rates of spread due to the dry post-harvest residuals. The reconstructed fire regimes for each land cover can be used to improve the simulated fire characteristics by models and, thus, future projections.
... In this study we focus on active fires and techniques to retrieve temperatures by using the SWIR (Short Wavelength InfraRed) spectral range. The use of SWIR spectral channels to detect wildfire has been researched by Morisette et al. (2007) who developed a detection algorithm based on the bands 8 centered at 2,330 nm and band 3 centered at 820 nm available in the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor on board of Terra satellite; the algorithm was later applied to different ecosystems (Csiszar et al., 2006;Giglio et al., 2008;Morisette et al., 2007) with promising results. ...
This paper deals with detection and temperature analysis and of wildfires using PRISMA imagery. Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by ASI (Agenzia Spaziale Italiana, Italian Space Agency) launched in 2019. This mission provides hyperspectral images with a spectral range of 400–2,500 nm and an average spectral resolution less than 12 nm and a spatial resolution of 30 m/pixel. This study focuses on the wildfire temperature estimation over the Bootleg Fire, US 2021. The analysis starts by considering the Hyperspectral Fire Detection Index (HFDI) which is used to analyze the informative content of the images, along with the analysis of some specific visible, near‐infrared and shortwave‐infrared bands. This first analysis is used as input to perform a temperature estimation of the areas with active wildfire. Surface temperature is retrieved using PRISMA radiance and a linear mixing model based on two background components (vegetation and burn scar) and two active fire components. PRISMA temperatures are compared with LST (Land Surface Temperature) products from NASA's ECOSTRESS and Landsat 8 which imaged the Bootleg Fire before and after PRISMA. A critical discussion of the results obtained with PRISMA is presented, followed by the advantages and limitation of the proposed approach.
