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Characterizing Vegetation Fire Dynamics in Brazil through Multisatellite Data: Common Trends and Practical Issues
Abstract
Correctly characterizing the frequency and distribution of fire occurrence is essential for understanding the environmental impacts of biomass burning. Satellite fire detection is analyzed from two sensors-the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-12 and the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, for 2001-03-to characterize fire activity in Brazil, giving special emphasis to the Amazon region. In evaluating the daily fire counts, their dependence on variations in satellite viewing geometry, overpass time, atmospheric conditions, and fire characteristics were considered. Fire counts were assessed for major biomes of Brazil, the nine states of the Legal Amazon, and two important road corridors in the Amazon region. All three datasets provide consistent information on the timing of peak fire activity for a given state. Also, ranking by relative fire counts per unit area highlights the importance of fire in smaller biomes such as Complexo do Pantanal. The local analysis of road corridors shows trends for fire detections with the increasing intensity of land use. Although absolute fire counts differ by as much as 1200%, when summarized over space and time, trends in fire counts among the three datasets show clear patterns of fire dynamics. The fire dynamics that are evident in these trend analyses are important foundations for assessing environmental impacts of biomass burning and policy measures to manage fire in Brazil.
... Heritage active fire detection methodologies have been developed for different sensors using algorithms that take advantage of the elevated radiance of fire at longer middle infrared (MIR) wavelengths [1][2][3][4][5]. Satellite active fire detections have found applications in diverse fields including fire characterization studies [6][7][8][9][10][11], studies of human activity [12,13], examination of the ecological responses to fire [14,15], studies of active volcanism [16,17], estimation of pyrogenic emissions of greenhouse gases and aerosols [18,19] for wildfire fire monitoring, control, and natural resource management [20][21][22], and have also been used in burned area mapping algorithms [23][24][25][26]. ...
... In this paper, we present a straightforward approach with proof of concept results, and accuracy assessments to downscale the MODIS 1 km active fire detections to estimate the active fire location probabilities within the 500 m subpixels. The downscaling algorithm is based on established satellite-based active fire detection capabilities using VIS-SWIR reflectance [10,17,[35][36][37][38]. These algorithms leverage on the increased radiance/reflectance in the 2 µm (SWIR) bands relative to the shorter (0.8 µm near-infrared (NIR)) wavelengths and elevated SWIR radiance/reflectance, to identify pixels that have actively burning components. ...
... The downscaling algorithm adapts established work [10,17,[35][36][37][38] to assign the probability of active fire presence to those 500 m subpixels within the 1 km active fire detection footprint. A downscaled 500 m active fire product from 1 km can potentially reduce the location and area uncertainty by one half and one quarter, respectively. ...
This work presents development of an algorithm to reduce the spatial uncertainty of active fire locations within the 1 km MODerate resolution Imaging Spectroradiometer (MODIS Aqua and Terra) daytime detection footprint. The algorithm is developed using the finer 500 m reflective bands by leveraging on the increase in 2.13 μm shortwave infrared reflectance due to the burning components as compared to the non-burning neighborhood components. Active fire presence probability class for each of the 500 m pixels within the 1 km footprint is assigned by locally adaptive contextual tests against its surrounding neighborhood pixels. Accuracy is assessed using gas flares and wildfires in conjunction with available high-resolution imagery. Proof of concept results using MODIS observations over two sites show that under clear sky conditions, over 84% of the 500 m locations that had active fires were correctly assigned to high to medium probabilities, and correspondingly low to poor probabilities were assigned to locations with no visible flaming fronts. Factors limiting the algorithm performance include fire size/temperature distributions, cloud and smoke obscuration, sensor point spread functions, and geolocation errors. Despite these limitations, the resulting finer spatial scale of active fire detections will not only help first responders and managers to locate actively burning fire fronts more precisely but will also be useful for the fire science community.
... Fire is used as the primary tool for forest and agricultural land clearing and the majority of fires are thought to be anthropogenic. Fires have been broadly classified into one of three types: (i) Maintenance fires, (ii) Deforestation fires, and (iii) Forest fires Nepstad et al. 2001;Schroeder et al. 2005;Ten Hoeve et al. 2012). Maintenance fires are lit on pasture and arable land to remove crop residues, shrub, and secondary forest regrowth, to reduce pests, and to encourage nutrient recycling (Crutzen and Andreae 1990;Nepstad et al. 2001) and can burn variable amounts of biomass depending on the vegetation condition and the time since the last fire application . ...
... This paper develops and assesses a methodology to classify MODerate resolution Imaging Spectroradiometer (MODIS) active fire detections over the BTMFB as maintenance, forest, or deforestation fire types. Previously, satellite active fire detection fire types have been inferred using different techniques including the geographic context and proximity of satellite active fire detections relative to thematic land cover classes, roads, and forest edges (Nepstad et al. 2001;Schroeder et al. 2005;Alencar, Nepstad, and Diaz 2006;Giglio 2007;Ten Hoeve et al. 2012;Chen, Morton, et al. 2013) and by consideration of the temporal persistence of satellite active fire detections Le Page et al. 2010;Chen, Morton, et al. 2013). These approaches have not been validated, and are expected to be less useful when new isolated forest areas are burned and because thematic land cover classes, roads, and forest edges may not be reliably mapped. ...
... This study described the first supervised classification of MODIS satellite fire types over the BTMFB. Other approaches have inferred fire type, for example, using geographic context and proximity to thematic land cover classes, roads, and forest edges (Nepstad et al. 2001;Schroeder et al. 2005;Alencar, Nepstad, and Diaz 2006;Giglio 2007;Ten Hoeve et al. 2012;Chen, Morton et al. 2013). Unlike other approaches, the described approach uses predictor variable information derived directly from MODIS active fire detectionsthe top two most important predictor variables were Table 5. Predictor variable importance summary showing the percentage (out of 48) of uncorrelated variable combinations that a variable from a group (Table 1) derived from the MODIS FRP (fire seasonality variables) and the MODIS 4 and 11 µm brightness temperatures (local temperature variables). ...
Abstract
Vegetation fires in the Brazilian Tropical Moist Forest Biome can be broadly classified into three types: i) Deforestation fires, lit to aid deforestation by burning of slashed, piled and dried forest biomass, ii) Maintenance fires, lit on agricultural fields or pasture areas to maintain and clear woody material and to rehabilitate degraded pasture areas, iii) Forest fires, associated with escaped anthropogenic fires or, less frequently, caused by lightning. Information on the incidence and spatial distribution of fire types is important as they have widely varying atmospheric emissions and ecological impacts. Satellite remote sensing offers a practical means of monitoring fires over areas as extensive as the Brazilian Tropical Moist Forest Biome which spans almost 4 million square kilometers. To date, fire type has been inferred based on the geographic context and proximity of satellite active fire detections relative to thematic land cover classes, roads, and forest edges, or by empirical consideration of the active fire detection frequency. In this paper a classification methodology is presented that demonstrates a way to classify the fire type of MODerate Resolution Imaging Spectroradiometer (MODIS) active fire detections. Training and validation fire type data are defined conservatively for MODIS active fire detections using a land cover transition matrix that labels MODIS active fires by consideration of the PRODES 120m land cover for the previous year and the year of fire detection. The training data are used with a random forest classifier and remotely sensed predictor variables including the number of MODIS Aqua and Terra satellite detections, the maximum and median Fire Radiative Power (FRP) [MW km-2], the scaling parameter of the FRP power law distribution, the number of day and night detections, and the fire surrounding "background" surface brightness temperature [K]. In addition, the total rainfall over periods from 1 to 24 months prior to fire detection and the fire detection proximity to official and unofficial roads and navigable rivers are included as predictor variables. Results are illustrated for eight years (2003-2010) of MODIS active fire detections with a cross validation showing greater than 70% fire type classification accuracy. The spatio-temporal distribution of fire types across the Brazilian Tropical Moist Forest Biome are presented with higher incidences of deforestation fires in the "arc of deforestation" and similar proportions of forest and maintenance fires for all years except for 2007 and 2010 that exhibited a relatively higher proportion of forest fires.
... Fires promote seed germination and sprouting [Anderson and Romme, 1991;Lamont et al., 1993;Pérez and Moreno, 1998], stimulate soil microbial activity and promote nutrient cycling [Poth et al., 1995;Wan et al., 2001;Choromanska and DeLuca, 2002]. Fires are also used to control weeds, pest and insects, prevent accumulation of agricultural waste, aid clearing of vegetation for other land use purposes Schroeder et al., 2005]. They also pose a significant potential hazard to human life and property. ...
... The most significant contributors to global fire emissions come from Africa (52%), South America (15%), Equatorial Asia (10%), Boreal regions (9%), and Australia (7%) . The occurrences of fires and amount of biomass burned annually are significantly more in the tropics than in other regions of the globe Schroeder et al., 2005]. This study focusses on characterization of vegetation fires in the Brazilian Tropical Moist Forest Biome [Olson et al., 2001]. ...
... Despite several decades of satellite data, there has been no reliable way to classify fire types. Fire types in the Brazilian Amazon have been inferred, without robust validation, using different techniques, including the geographic context and proximity of satellite active fire detections relative to thematic land cover classes, roads, and forest edges Schroeder et al., 2005; and by consideration of the temporal persistence of satellite active fire detections Chen et al., 2013]. Consequently, questions regarding the incidence and impacts of different fire types in the BTMFB have been confined to small spatial and short temporal coverages. ...
The Brazilian Tropical Moist Forest Biome (BTMFB) is “Earth’s greatest biological treasure and a major component of the earth system” and forest degradation and deforestation by fire is a serious issue in this region. Fires in the BTMFB can be broadly classified as maintenance, deforestation and forest fire types. Spatially and temporally explicit information on the incidences of fire types are important as they have widely varying atmospheric emissions and ecological impacts. Satellite based remote sensing is a practical means of monitoring the BTMFB that spans almost 4 million km2. However, there has been no way to reliably classify satellite active fire type to date. In this work, methods to characterize MODIS active fire detections are developed using physically based and geographic context/proximity approaches. The research methodology is developed by addressing four hypotheses concerning differences among active fire type characteristics including factors that drive and mediate fire in the BTMFB. Differences in the active fire characteristics among different fire types are presented and discussed. The spatio-temporal distribution of fire types over 8 year (2003-2010) period is documented, analyzed and presented. This dissertation has, to date, resulted in one published, one in press, and one submitted paper.
http://openprairie.sdstate.edu/etd/1078/
... Fire is used as the primary tool for forest and agricultural land clearing and the majority of fires are thought to be anthropogenic. Fires have been broadly classified into one of three types: (i) Maintenance fires, (ii) Deforestation fires, and (iii) Forest fires Nepstad et al. 2001;Schroeder et al. 2005;Ten Hoeve et al. 2012). Maintenance fires are lit on pasture and arable land to remove crop residues, shrub, and secondary forest regrowth, to reduce pests, and to encourage nutrient recycling (Crutzen and Andreae 1990;Nepstad et al. 2001) and can burn variable amounts of biomass depending on the vegetation condition and the time since the last fire application . ...
... This paper develops and assesses a methodology to classify MODerate resolution Imaging Spectroradiometer (MODIS) active fire detections over the BTMFB as maintenance, forest, or deforestation fire types. Previously, satellite active fire detection fire types have been inferred using different techniques including the geographic context and proximity of satellite active fire detections relative to thematic land cover classes, roads, and forest edges (Nepstad et al. 2001;Schroeder et al. 2005;Alencar, Nepstad, and Diaz 2006;Giglio 2007;Ten Hoeve et al. 2012;Chen, Morton, et al. 2013) and by consideration of the temporal persistence of satellite active fire detections Le Page et al. 2010;Chen, Morton, et al. 2013). These approaches have not been validated, and are expected to be less useful when new isolated forest areas are burned and because thematic land cover classes, roads, and forest edges may not be reliably mapped. ...
... This study described the first supervised classification of MODIS satellite fire types over the BTMFB. Other approaches have inferred fire type, for example, using geographic context and proximity to thematic land cover classes, roads, and forest edges (Nepstad et al. 2001;Schroeder et al. 2005;Alencar, Nepstad, and Diaz 2006;Giglio 2007;Ten Hoeve et al. 2012;Chen, Morton et al. 2013). Unlike other approaches, the described approach uses predictor variable information derived directly from MODIS active fire detectionsthe top two most important predictor variables were Table 5. Predictor variable importance summary showing the percentage (out of 48) of uncorrelated variable combinations that a variable from a group (Table 1) derived from the MODIS FRP (fire seasonality variables) and the MODIS 4 and 11 µm brightness temperatures (local temperature variables). ...
The Brazilian Tropical Moist Forest Biome (BTMFB) spans almost 4 million km2 and is subject to extensive annual fires that have been categorized into deforestation, maintenance, and forest fire types. Information on fire types is important as they have different atmospheric emissions and ecological impacts. A supervised classification methodology is presented to classify the fire type of MODerate resolution Imaging Spectroradiometer (MODIS) active fire detections using training data defined by consideration of Brazilian government forest monitoring program annual land cover maps, and using predictor variables concerned with fuel flammability, fuel load, fire behavior, fire seasonality, fire annual frequency, proximity to surface transportation, and local temperature. The fire seasonality, local temperature, and fuel flammability were the most influential on the classification. Classified fire type results for all 1.6 million MODIS Terra and Aqua BTMFB active fire detections over eight years (2003–2010) are presented with an overall fire type classification accuracy of 90.9% (kappa 0.824). The fire type user’s and producer’s classification accuracies were respectively 92.4% and 94.4% (maintenance fires), 88.4% and 87.5% (forest fires), and, 88.7% and 75.0% (deforestation fires). The spatial and temporal distribution of the classified fire types are presented and are similar to patterns reported in the available recent literature.
... Land-use fires are the dominant source of ignitions in Amazonia (Sanford et al., 1985;Goldammer, 1990) and the primary method of both deforestation and agricultural maintenance (Cochrane, 2003;Schroeder et al., 2005;Schroeder et al., 2008b). Fires are in deforested areas set to burn trunks, stumps, and woody roots following clear-felling of forest vegetation in preparation for cattle ranching or crop production ( Figure 1-2). ...
... Amazonia are most common during the end of the dry season because extended rainless periods reduce fuel moisture and the nutrient-rich ash layer enhances agricultural productivity at the onset of the rainy season (Schroeder et al., 2005). ...
... Satellite observations are the only reasonable way to monitor land-use fire activity over large regions such as Amazonia (e.g., Setzer & Pereira, 1991;Schroeder et al., 2005;Giglio et al., 2006a;Schroeder et al., in press). A range of data products exist for detection of active fires from satellites (e.g., Setzer & Pereira, 1991;Prins & Menzel, 1992;Giglio et al., 2003;Giglio et al., in press). ...
... Forest fires have had an increasingly greater role in contributing to forest degradation in the Amazon region. As an important agent of land-use and land-cover change, forest fires have yet to be properly addressed (Schroeder et al. 2005). Most analyses of forest fires over extensive areas in the Amazon region have been based on general information, mainly focused on the geographic location of fires based on thermal bands and coarse spatial resolution satellite products. ...
... Most of these maps are based on National Oceanic and Atmospheric Administration (NOAA) and Moderate Resolution Imaging Spectroradiometer (MODIS) products and are available for the entire South American continent at http://www.cptec.inpe.br/queimadas. Schroeder et al. (2005) used INPE products to analyse spatiotemporal dynamics of fire in the Brazilian Amazon. The authors had to integrate various data sets to improve fire detection capability and reduce analytical uncertainties caused by the use of a single Downloaded by [Michigan State University] at 13:49 01 November 2012 sensor. ...
... Cochrane and Schulze 1998;Souza, Roberts, and Monteiro 2005). These are not sufficient for a more comprehensive analysis of forest fires (Schroeder et al. 2005) and selective logging in the Amazon region (Matricardi et al. 2007). ...
The rapid environmental changes occurring in the Brazilian Amazon due to widespread deforestation have attracted the attention of the scientific community for several decades. A topic of particular interest involves the assessment of the combined impacts of selective logging and forest fires. Forest disturbances by selective logging and forest fires may vary in scale, from local to global changes, mostly related to the increase of carbon dioxide released into the atmosphere. Selective logging activities and forest fires have been reported by several studies as important agents of land-use and land-cover changes. Previous studies have focused on selective logging, but forest fires on a large scale in tropical regions have yet to be properly addressed. This study involved a more comprehensive investigation of temporal and basin-wide changes of forest disturbances by selective logging and forest fires using remotely sensed data acquired in 1992, 1996, and 1999. Landsat imagery and remote-sensing techniques for detecting burned forests and estimating forest canopy cover were applied. We also conducted rigorous ground measurements and observations to validate remote-sensing techniques and to assess canopy-cover impacts by selective logging and forest fires in three different states in the Brazilian Amazon. The results of this study showed a substantial increase in total forested areas impacted by selective logging and forest fires from approximately 11,800 to 35,600 km2 in 1992 and 1999, respectively. Selective logging was responsible for 60.4% of this forest disturbance in the studied period. Approximately 33% and 7% of forest disturbances detected in the same period were due to impacts of forest fires only and selective logging and forest fires combined, respectively. Most of the degraded forests ∼90% were detected in the states of Mato Grosso and Pará. Our estimates indicated that approximately 5467, 7618, and 17437 km2 were new areas of selective logging and/or forest fires in 1992, 1996, and 1999, respectively. Protected areas seemed to be very effective in constraining these types of forest degradation. Approximately 2.4% and 1.3% of the total detected selectively logged and burned forests, respectively, were geographically located within protected areas. We observed, however, an increasing trend for these anthropogenic activities to occur within the limits of protected areas from 1992 to 1999. Although forest fires impacted the least area of tropical forests in the study region, new areas of burned forests detected in 1996 and 1999 were responsible for the greatest impact on canopy cover, with an estimated canopy loss of 18.8% when compared to undisturbed forests. Selective logging and forest fires combined impacted even more those forest canopies, with an estimated canopy loss of 27.5%. Selectively logged forest only showed the least impact on canopy cover, with an estimated canopy loss of 5%. Finally, we observed that forest canopy cover impacted by selective logging activities can recover faster up to 3 years from impact when compared to those forests disturbed by fires up to 5 years in the Amazon region.
... Human activities associated with those land use processes are in turn largely influenced by the regional climate conditions, characterized by high rainfall rates occurring during a relatively long wet season when fire use is rarely possible. However, during the dry season months, when there is a noticeable reduction in precipitation fires are used extensively [Schroeder et al., 2005]. ...
... However, most users only have access to limited information describing the location and timing of detections derived from individual products. Differences among fire products and the lack of information describing data quality create major difficulties for end users [Schroeder et al., 2005]. As a result, law enforcement activities and the decision making process are significantly compromised, state and federal strategic plans to assign resources to control fire activity at the county level are negatively affected, and scientific studies based on fire detection data become subject to large uncertainties (Figure 1.1). ...
... Previous case study analyses have assessed the detection performance of WF-ABBA and MODIS Thermal Anomalies products over Brazilian Amazonia [Morisette et al., 2005b;Prins et al., 1998]. However, detailed characterization of those products was missing and differences in sensor characteristics and unexplained differences between WF-ABBA and MODIS Thermal Anomalies fire detections were common [Foster Brown, personal communication;Schroeder et al., 2005]. The lack of a large set of good quality ground truth data was one of the major obstacles limiting a comprehensive characterization of those products. ...
Biomass burning is a major environmental problem in Amazonia. Satellite fire detections represent the primary source of information for fire alert systems, decision makers, emissions modeling groups and the scientific community in general. Those various users create a growing demand for good quality fire data of higher spatial and temporal resolution that can only be achieved via integration of multiple satellite fire detection products. The main objective of this dissertation was to develop an integrated fire product capable of improved monitoring and characterization of fire activity in Brazilian Amazonia. Two major active fire detection algorithms based on MODIS and GOES data were used to meet the users demand for fire information. Large differences involving the performance of the MODIS and GOES fire products required the quantification of omission and commission errors in order to allow for appropriate treatment of individual detections produced by each data set. Relatively small omission errors due to cloud obscuration were estimated for Brazilian Amazonia. Regional climate conditions result in reduced cloud coverage in areas of high fire activity during the peak of the dry season, therefore minimizing the effects of cloud obscuration on fire detection omission errors. Clear sky omission and commission errors were largely dependent on the vegetation and background conditions. Relatively large commission errors occurring in high percentage tree cover areas suggested that fire detection algorithms must either be regionalized or incorporate additional tests to provide more consistent fire information across a broader range of surface conditions. Integration of MODIS and GOES fire products using a physical parameter describing fire energy (i.e., fire radiative power) was proven difficult due to limitations involving the interplay between sensor characteristics and the types of fires that occur in Amazonia. As part of this research, a new integrated product was generated based on binary fire detection information derived from MODIS and GOES data, incorporating adjustments to reduce commission and omission errors and optimizing the complementarities among individual detections. These findings made a significant contribution to fire monitoring science in Amazonia and could play an important role in the development of future fire detection algorithms for tropical regions.
... Además de la elasticidad del consumo y de la demanda, esta elasticidad de las necesidades resulta clave para estudiar la dimensión cuantitativa de la doble crisis de la basura. 64 Esta doble crisis de la basura en el capitalismo, entonces, deviene de la subsunción formal-cuantitativa y real-cualitativa del trabajo y el consumo al capital. Sin embargo, aún falta un elemento clave que subyace en esta crisis: el desarrollo tecnológico. ...
... OSTGAARD, K.; JENSEN, A. Evaluation of direct fluorescence spectroscopy for monitoring aqueous petroleum solutions. International Journal of Environmental Analytical Chemistry, v. 14, n. 1, p.[55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72] 1983. ...
Resumen: En América Latina y el Caribe se están desarrollando reflexiones desde la ecología política
orientadas hacia la construcción de una teoría crítica que posibilite el estudio de los conflictos ecológicos
causados por los desperdicios y la contaminación en el Sur Global. De esta forma, académicos,
investigadores, activistas y movimientos sociales han avanzado hacia la fundamentación de una ‘Ecología
Política’ que posibilite el estudio de los conflictos relacionados con la reproducción de una crisis
cualitativa y cuantitativa de la basura asentada en un modelo hegemónico y capitalista de gestión y
disposición final de basuras en rellenos sanitarios controlados, vertederos y basureros a cielo abierto que
se hallan instalados, comúnmente, en áreas periurbanas y rurales de las ciudades. Esta doble crisis no
solamente incide sobre la producción de desperdicios y la contaminación, sino también en la crisis por la
pérdida de biodiversidad y el cambio climático. La degradación ambiental de los ecosistemas causada por
estos conflictos también ha comprometido la alteración de las condiciones sanitarias y saludables que
sustentan la vida humana y las actividades sociales, económicas y culturales de las comunidades que
habitan en estas ‘zonas de sacrificio’. Por tanto, es posible evidenciar fenómenos propios a la disociación
de la dialéctica sociedad-naturaleza, la ruptura del metabolismo social, y las consecuencias nocivas de la
subsunción real y formal de la basura bajo el capital. En este orden, el objetivo de este capítulo de libro
consiste en realizar una aproximación a ciertas categorías teóricas y críticas que están fundamentando la
estructuración de la ‘Ecología Política de la Basura y los Residuos’ a través del análisis de diferentes
contribuciones transdisciplinares que no solo apuntan al estudio de los conflictos por los desperdicios y la
contaminación, sino que coinciden en la necesidad de construir alternativas sustentables, saludables y
democráticas a la doble crisis de la basura en el Sur Global
... Además de la elasticidad del consumo y de la demanda, esta elasticidad de las necesidades resulta clave para estudiar la dimensión cuantitativa de la doble crisis de la basura. 64 Esta doble crisis de la basura en el capitalismo, entonces, deviene de la subsunción formal-cuantitativa y real-cualitativa del trabajo y el consumo al capital. Sin embargo, aún falta un elemento clave que subyace en esta crisis: el desarrollo tecnológico. ...
... OSTGAARD, K.; JENSEN, A. Evaluation of direct fluorescence spectroscopy for monitoring aqueous petroleum solutions. International Journal of Environmental Analytical Chemistry, v. 14, n. 1, p.[55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72] 1983. ...
... Además de la elasticidad del consumo y de la demanda, esta elasticidad de las necesidades resulta clave para estudiar la dimensión cuantitativa de la doble crisis de la basura. 64 Esta doble crisis de la basura en el capitalismo, entonces, deviene de la subsunción formal-cuantitativa y real-cualitativa del trabajo y el consumo al capital. Sin embargo, aún falta un elemento clave que subyace en esta crisis: el desarrollo tecnológico. ...
... OSTGAARD, K.; JENSEN, A. Evaluation of direct fluorescence spectroscopy for monitoring aqueous petroleum solutions. International Journal of Environmental Analytical Chemistry, v. 14, n. 1, p.[55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72] 1983. ...
... Fire dynamics in the Amazon basin have changed considerably over the past few decades, a consequence of changes in land cover and weather (Schroeder et al., 2005;Alencar et al., 2015;Da Silva Júnior et al., 2019). Fire frequency and severity in the Amazon basin are influenced by temperature, precipitation, logging and fragmentation (Aragao et al., 2007;Alencar et al., 2011;Morton et al., 2013;Armenteras & Retana, 2012) under all climate scenarios (Abatzoglou et al., 2018;Gutman, Csiszar & Romanov, 2000). ...
... Fire frequency and severity in the Amazon basin are influenced by temperature, precipitation, logging and fragmentation (Aragao et al., 2007;Alencar et al., 2011;Morton et al., 2013;Armenteras & Retana, 2012) under all climate scenarios (Abatzoglou et al., 2018;Gutman, Csiszar & Romanov, 2000). Forest fires are exacerbated by droughts resulting from El Niño events (Gutman, Csiszar & Romanov, of fire and their frequencies (Schroeder et al., 2005;Morton et al., 2013;Armenteras & Retana, 2012;Da Silva et al., 2018;Uriarte et al., 2012). However, fire characteristics such as size and extent and fire behavioral attributes such as speed are important components of fire regimes (McLauchlan et al., 2020). ...
In the past two decades, Amazon rainforest countries (Brazil, Bolivia, Colombia, Ecuador, Guyana, Peru and Venezuela) have experienced a substantial increase in fire frequency due to the changes in the patterns of different anthropogenic and climatic drivers. This study examines how both fire dynamics and bioclimatic factors varied based on the season (wet season and dry season) El Niño years across the different countries and ecosystems within the Amazon rainforest. Data from publicly available databases on forest fires (Global Fire Atlas) and bioclimatic, topographic and anthropogenic variables were employed in the analysis. Linear mixed-effect models discovered that year type (El Niño vs. non-El Niño), seasonality (dry vs. wet), land cover and forest strata (in terms of canopy cover and intactness) and their interactions varied across the Amazonian countries (and the different ecosystems) under consideration. A machine learning model, Multivariate Adaptive Regression Spline (MARS), was utilized to determine the relative importance of climatic, topographic, forest structure and human modification variables on fire dynamics across wet and dry seasons, both in El Niño and non-El Niño years. The findings of this study make clear that declining precipitation and increased temperatures have strong impact on fire dynamics (size, duration, expansion and speed) for El Niño years. El Niño years also saw greater fire sizes and speeds as compared to non-El Niño years. Dense and relatively undisturbed forests were found to have the lowest fire activity and increased human impact on a landscape was associated with exacerbated fire dynamics, especially in the El Niño years. Additionally, the presence of grass-dominated ecosystems such as grasslands also acted as a driver of fire in both El Niño and non-El Niño years. Hence, from a conservation perspective, increased interventions during the El Niño periods should be considered.
... Fire dynamics in the Amazon basin have changed considerably over the past few decades, a consequence of changes in land cover and weather (Schroeder et al., 2005;Alencar et al., 2015;Da Silva Júnior et al., 2019). Fire frequency and severity in the Amazon basin are influenced by temperature, precipitation, logging and fragmentation (Aragao et al., 2007;Alencar et al., 2011;Morton et al., 2013;Armenteras & Retana, 2012) under all climate scenarios (Abatzoglou et al., 2018;Gutman, Csiszar & Romanov, 2000). ...
... Fire frequency and severity in the Amazon basin are influenced by temperature, precipitation, logging and fragmentation (Aragao et al., 2007;Alencar et al., 2011;Morton et al., 2013;Armenteras & Retana, 2012) under all climate scenarios (Abatzoglou et al., 2018;Gutman, Csiszar & Romanov, 2000). Forest fires are exacerbated by droughts resulting from El Niño events (Gutman, Csiszar & Romanov, of fire and their frequencies (Schroeder et al., 2005;Morton et al., 2013;Armenteras & Retana, 2012;Da Silva et al., 2018;Uriarte et al., 2012). However, fire characteristics such as size and extent and fire behavioral attributes such as speed are important components of fire regimes (McLauchlan et al., 2020). ...
In the past two decades, Amazon rainforest countries (Brazil, Bolivia, Colombia, Ecuador, Guyana, Peru and Venezuela) have experienced a substantial increase in fire frequency due to the changes in the patterns of different anthropogenic and climatic drivers. This study examines how both fire dynamics and bioclimatic factors varied based on the season (wet season and dry season) El Niño years across the different countries and ecosystems within the Amazon rainforest. Data from publicly available databases on forest fires (Global Fire Atlas) and bioclimatic, topographic and anthropogenic variables were employed in the analysis. Linear mixed-effect models discovered that year type (El Niño vs . non-El Niño), seasonality (dry vs . wet), land cover and forest strata (in terms of canopy cover and intactness) and their interactions varied across the Amazonian countries (and the different ecosystems) under consideration. A machine learning model, Multivariate Adaptive Regression Spline (MARS), was utilized to determine the relative importance of climatic, topographic, forest structure and human modification variables on fire dynamics across wet and dry seasons, both in El Niño and non-El Niño years. The findings of this study make clear that declining precipitation and increased temperatures have strong impact on fire dynamics (size, duration, expansion and speed) for El Niño years. El Niño years also saw greater fire sizes and speeds as compared to non-El Niño years. Dense and relatively undisturbed forests were found to have the lowest fire activity and increased human impact on a landscape was associated with exacerbated fire dynamics, especially in the El Niño years. Additionally, the presence of grass-dominated ecosystems such as grasslands also acted as a driver of fire in both El Niño and non-El Niño years. Hence, from a conservation perspective, increased interventions during the El Niño periods should be considered.
... We used the MODIS Active Fire dataset because it provides the longest consistent spatially explicit global time series information of fire. However, MODIS active fire data have some limitations, for example caused by the wide sensor swath of 2,230 km, which can result in pixel area differences between nadir and the swath edges of a factor of 10, thereby potentially underestimating fire area at the swath edges 70 . This is a particular issue as active fires are detected by thermal anomalies that, if classified as fire, are represented by a single point in the centre location of the pixel. ...
The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle. It is where human-environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area and wildland vegetation. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003-2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.
... The tapir's site-use was not correlated to proximity to urban areas, roads nor indigenous territories, but rather, distance to forest fires was revealed as an important factor affecting the species' occurrence in the Amazon. The impact of forest fires on wild populations merits further research (Adeney et al., 2009;Schroeder et al., 2005). However, a recent study designed to evaluate the role of the lowland tapir in dispersing seeds to a recurrently burned and undisturbed Amazonian forest bordering a soybean field, suggested that the species uses this twice as often as undisturbed forested areas, as a consequence of greater availability of palatable plants during early-successional stages (Paolucci et al., 2019). ...
The Amazon is one of the most diverse biomes around the globe, currently threatened by economic and industrial development and climate change. Large mammals are keystone species, playing an important role in ecosystem structure and function as ecological engineers, while being highly susceptible to deforestation, habitat degradation , and human exploitation. Using a unifying hierarchical Bayesian spatial approach, we examine the site-use patterns of four large Amazonian Forest mammals and their relationships to anthropogenic factors at a biome-wide scale. Our results showed that species' patterns of site use are correlated with human induced habitat changes, and that this correlation is species-specific. The white-lipped peccary shows highest site-use estimates within strict protected areas, affected by proximity to urban areas and benefiting from indigenous territories, the tapir responding slightly to proximity to burned forested areas, while the giant armadillo and the jaguar were primarily affected by vegetation cover loss; disturbances related to the colonization of the Amazon. Our findings 2 contribute to the understanding of how human-induced environmental changes influence the site-use patterns of these four large mammals, and inform future conservation and land use planning. Transboundary conservation efforts, empowering and integrating native (indigenous and non-indigenous) communities in land governance schemes, involving the private sector and securing the commitment of developed countries are important paths for the protection and sustainability of the globally-crucial Amazon rainforest.
... 2000 (22). Nevertheless, the relatively coarse resolution of the MODIS thermal imagery, with effective pixel resolution increasing from 1 km 2 at nadir to about 10 km 2 at off-nadir angles, leads to an underestimate of total fire activity, especially for low-energy fires (35,36). Together, the VIIRS instruments on board Suomi NPP (launched in 2012) and NOAA-20 (launched in 2017) improve global coverage for fire detection with higher spatial resolution of individual fire detections (0.14 km 2 ), more accurate geolocation information, and more consistent fire detection sensitivity across the full image swath. ...
Exceptional fire activity in 2019 sparked concern about Amazon forest conservation. However, the inability to rapidly separate satellite fire detections by fire type hampered fire suppression and assessment of ecosystem and air quality impacts. Here, we describe the development of a near–real-time approach for tracking contributions from deforestation, forest, agricultural, and savanna fires to burned area and emissions and apply the approach to the 2019 fire season in South America. Across the southern Amazon, 19,700 deforestation fire events accounted for 39% of all satellite active fire detections and the majority of fire carbon emissions (63%; 69 Tg C). Multiday fires accounted for 81% of burned area and 92% of carbon emissions from the Amazon, with many forest fires burning uncontrolled for weeks. Most fire detections from deforestation fires were correctly identified within 2 days (67%), highlighting the potential to improve situational awareness and management outcomes during fire emergencies.
... In this context, some limitations increase errors in burned area products. Significant source of errors include the presence of clouds, which significantly reduces the ability to detect a fire hotspot due to the attenuation of the spectral radiance emitted by the flaming and smoldering phases in the biomass burning process [32], the lack of data on the moment of fire occurrence and, especially, the incompatibility of the temporal and spatial resolutions of some sensors, making these sensors unsuitable for the identification of burns. One way to reduce the uncertainty in the detection of burned surfaces is by using sensors data that have geometric, radiometric, and temporal resolutions appropriate to map the location and the discrimination of burned areas. ...
Quantifying forest fires remain a challenging task for the implementation of public policies aimed to mitigate climate change. In this paper, we propose a new method to provide an annual burned area map of Mato Grosso State located in the Brazilian Amazon region, taking advantage of the high spatial and temporal resolution sensors. The method consists of generating the vegetation, soil, and shade fraction images by applying the Linear Spectral Mixing Model (LSMM) to the Landsat-8 OLI (Operational Land Imager), PROBA-V (Project for On-Board Autonomy-Vegetation), and Suomi NPP-VIIRS (National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite) datasets. The shade fraction images highlight the burned areas, in which values are represented by low reflectance of ground targets, and the mapping was performed using an unsupervised classifier. Burned areas were evaluated in terms of land use and land cover classes over the Amazon, Cerrado and Pantanal biomes in the Mato Grosso State. Our results showed that most of the burned areas occurred in non-forested areas (66.57%) and old deforestation (21.54%). However, burned areas over forestlands (11.03%), causing forest degradation, reached more than double compared with burned areas identified in consolidated croplands (5.32%). The results obtained were validated using the Sentinel-2 data and compared with active fire data and existing global burned areas products, such as the MODIS (Moderate Resolution Imaging Spectroradiometer product) MCD64A1 and MCD45A1, and Fire CCI (ESA Climate Change Initiative) products. Although there is a good visual agreement among the analyzed products, the areas estimated were quite different. Our results presented correlation of 51% with Sentinel-2 and agreement of r 2 = 0.31, r 2 = 0.29, and r 2 = 0.43 with MCD64A1, MCD45A1, and Fire CCI products, respectively. However, considering the active fire data, it was achieved the better performance between active fire presence and burn mapping (92%). The proposed method provided a general perspective about the patterns of fire in various biomes of Mato Grosso State, Brazil, that are important for the environmental studies, specially related to fire severity, regeneration, and greenhouse gas emissions.
... 23% globally (Giglio et al. 2018). Moreover, studies that used burned-area products in Brazil did not detail their accuracy in the different biomes (Schroeder et al. 2005;de Araújo et al. 2012;Caúla et al. 2015;Rodrigues et al. 2019). ...
The Moderate Resolution Imaging Spectroradiometer (MODIS) products are the most used in burned-area monitoring, on regional and global scales. This research aims to evaluate the accuracy of the MODIS burned-area and active-fire products to describe fire patterns in Brazil in the period 2001–2015. The accuracy analysis, in the year 2015, compared the MODIS products (MCD45/MCD64) and the burned areas extracted by the visual interpretation of the LANDSAT/Operational Land Imager (OLI) images from the confusion matrix. The accuracy analysis of the active-fire products (MOD14/MYD14) in the year 2015 used linear regression. We used the most accurate burned-area product (MCD64), in conjunction with environmental variables of land use and climate. The MCD45 product presented a high error of commission (>36.69%) and omission (>77.04%) for the whole country. The MCD64 product had fewer errors of omission (64.05%) compared with the MCD45 product, but increased errors of commission (45.85%). MCD64 data in 2001–2015 showed three fire domains in Brazil determined by the climatic pattern. Savanna and grassy areas in semi-humid zones are the most prone areas to fire, burning an average of 25% of their total area annually, with a fire return interval of 5–6 years.
... GEO sensors have a high temporal resolution, and exploiting the high temporal resolution enhances the chance of detecting a fire at ignition. Given that fires are generally small when started, the high-temporal data can then allow the detection of small and low-power fire events, typically only possible with the LEO system [20][21][22]. In this study, GEO satellite temporal MIR data are assimilated into the model of Diurnal Temperature Cycle (DTC) parameters of a pixel to describe non-fire background temperature dynamics to aid the early detection of wildfires. ...
Detection of an active fire in an image scene relies on an accurate estimation of the background temperature of the scene, which must be compared to the observed temperature, to decide on the presence of fire. The expected background temperature of a pixel is commonly derived based on spatial-contextual information that can overestimate the background temperature of a fire pixel and therefore results in the omission of a fire event. This paper proposes a method that assimilates brightness temperatures acquired from the Geostationary Earth Orbit (GEO) sensor MSG-SEVIRI into a Diurnal Temperature Cycle (DTC) model. The expected brightness temperatures are observational forecasts derived using the ensemble forecasting approach. The threshold on the difference between the observed and expected temperatures is derived under a Constant False Alarm Rate (CFAR) framework. The detection results are assessed against a reference dataset comprised of MODIS MOD14/MYD14 and EUMETSAT FIR products, and the performance is presented in terms of user’s and producer’s accuracies, and Precision-Recall and Receiver Operating Characteristic (ROC) graphs. The method has a high detection rate when the data assimilation is implemented with an Ensemble Kalman Filter (EnKF) and a Sampling Importance Resampling (SIR) particle filter, while the weak-constraint Four-Dimensional Variational Assimilation (4D-Var) has comparatively lower detection and false alarm rates according to the reference dataset. Consideration of the diurnal variation in the background temperature enables the proposed method to detect even low-power fires.
... The amount of radiative energy reaching the MODIS instruments is much smaller at larger scan angles than at nadir. This means that the MODIS instruments will be less sensitive to low values of FRP at high latitude (Giglio et al., 2003;Schroeder et al., 2005). This could explain the difference of the distribution of FRP associated with fire patches in BONA: the stronger asymmetry of the distribution in this region (i.e. the larger tail toward high FRP values) could arise from missing active fire data from less intense fires in this region. ...
Vegetation fires are an important process in the Earth system. Fire intensity locally impacts fuel consumption , damage to the vegetation, chemical composition of fire emissions and also how fires spread across landscapes. It has been observed that fire occurrence, defined as the frequency of active fires detected by the MODIS sensor, is related to intensity with a hump-shaped empirical relation, meaning that occurrence reaches a maximum at intermediate fire intensity. Raw burned area products obtained from remote sensing can not discriminate between ignition and propagation processes. To go beyond burned area and to test if fire size is driven by fire intensity at a global scale as expected from empirical fire spread models, we used the newly delivered global FRY database, which provides fire patch functional traits based on satellite observation, including fire patch size, and the fire ra-diative power measures from the MCD14ML dataset. This paper describes the varying relationships between fire size and fire radiative power across biomes at a global scale. We show that in most fire regions of the world defined by the GFED database, the linear relationship between fire radia-tive power and fire patch size saturates for a threshold of intermediate-intensity fires. The value of this threshold differs from one region to another and depends on vegetation type. In the most fire-prone savanna regions, once this threshold is reached, fire size decreases for the most intense fires, which mostly happen in the late fire season. According to the percolation theory, we suggest that the decrease in fire size for more intense late season fires is a consequence of the increasing fragmentation of fuel continuity throughout the fire season and suggest that landscape-scale feedbacks should be developed in global fire modules.
... The amount of radiative energy reaching the MODIS instruments is much smaller at larger scan angles than at nadir. This means that the MODIS instruments will be less sensitive to low values of FRP at high latitude (Giglio et al., 2003;Schroeder et al., 2005). This could explain the difference of the distribution of FRP associated with fire patches in BONA: the stronger asymmetry of the distribution in this region (i.e. the larger tail toward high FRP values) could arise from missing active fire data from less intense fires in this region. ...
Vegetation fires are an important process in the Earth system. Fire intensity
locally impacts fuel consumption, damage to the vegetation, chemical
composition of fire emissions and also how fires spread across landscapes. It
has been observed that fire occurrence, defined as the frequency of active
fires detected by the MODIS sensor, is related to intensity with a
hump-shaped empirical relation, meaning that occurrence reaches a maximum at
intermediate fire intensity. Raw burned area products obtained from
remote sensing can not discriminate between ignition and propagation
processes. To go beyond burned area and to test if fire size is driven by
fire intensity at a global scale as expected from empirical fire spread models,
we used the newly delivered global FRY database, which provides fire patch
functional traits based on satellite observation, including fire patch size,
and the fire radiative power measures from the MCD14ML dataset. This paper
describes the varying relationships between fire size and fire radiative
power across biomes at a global scale. We show that in most fire regions of the
world defined by the GFED database, the linear relationship between fire
radiative power and fire patch size saturates for a threshold of intermediate-intensity fires. The value of this threshold differs from one region to
another and depends on vegetation type. In the most fire-prone savanna
regions, once this threshold is reached, fire size decreases for the most
intense fires, which mostly happen in the late fire season. According to the
percolation theory, we suggest that the decrease in fire size for more
intense late season fires is a consequence of the increasing fragmentation of
fuel continuity throughout the fire season and suggest that landscape-scale
feedbacks should be developed in global fire modules.
... There is an established heritage for active fire detection using algorithms developed for different sensors to take advantage of the elevated radiance of fire at longer wavelengths (Matson and Dozier 1981;Robinson 1991;Prins and Menzel 1992;Davies et al. 2006). Satellite active fire detections have been used in fire regime characterization studies (Schroeder et al. 2005;Giglio 2007; Loboda and Csiszar 2007;Aragão et al. 2007;Chuvieco, Giglio, and Justice 2008;Boschetti and Roy 2008), studies of human activity (FEMA 2005;Kumar et al. 2014;Pereira et al. 2015), examination of the ecological responses to fire (Lentile et al. 2006;Bowman et al. 2009), studies of active volcanism (Oppenheimer 1991), to estimate pyrogenic emissions of greenhouse gases and aerosols (Kaiser et al. 2012;Kumar et al. 2011;Zhang, Kondragunta, and Roy 2014), for wildfire fire monitoring, control, and natural resource management (Trigg and Roy 2007;Davies et al. 2009;Frost 2013), and have been used in burned area mapping algorithms (Fraser et al. 2000;Roy et al. 1999;Giglio et al. 2009;Boschetti et al. 2015). Active fire detection algorithms have predominantly been developed for high-temporal resolution satellite systems due to the ephemeral nature of fire. ...
A global operational land imager (GOLI) Landsat-8 daytime active fire detection algorithm is presented. It utilizes established contextual active fire detection approaches but takes advantage of the significant increase in fire reflectance in Landsat-8 band 7 (2.20 μm) relative to band 4 (0.66 μm). The detection thresholds are fixed and based on a statistical examination of 39 million non-burning Landsat-8 pixels. Multi-temporal tests based on band 7 reflectance and relative changes in normalized difference vegetation index in the previous six months are used to reduce commissions errors. The probabilities of active fire detection for the GOLI and two recent Landsat-8 active fire detection algorithms are simulated to provide insights into their performance with respect to the fire size and temperature. The algorithms are applied to 11 Landsat-8 images that encompass a range of burning conditions and environments. Commission and omission errors are assessed by visual interpretation of detected active fire locations and by examination of the Landsat-8 images and higher spatial resolution Google Earth imagery. The GOLI algorithm has lower omission and comparable commission errors than the recent Landsat-8 active fire detection algorithms. The GOLI algorithm has demonstrable potential for global application and is suitable for implementation with other Landsat-like reflective wavelength sensors. ARTICLE HISTORY
... The estimated fraction of fire-driven deforestation for different land management categories in this study is likely conservative because satellite platforms do not detect all fires. Satellite sensors may not sample at the peak of diurnal fire activity (Giglio et al., 2000), and cloud obscuration and orbital coverage (Schroeder et al., 2005) reduce the probability of fire detections, particularly for low-latitude regions with persistent cloud cover such as Southeast Asia. New satellite products partially overcome these limitations through improvements in orbital coverage and spatial resolution (Schroeder et al., 2014), especially for detection of small and low-intensity fires in deforestation or peatland areas (Schroeder et al., 2015;Elvidge et al., 2015). ...
Indonesia and Malaysia have emerged as leading producers of palm
oil in the past several decades, expanding production through the conversion
of tropical forests to industrial plantations. Efforts to produce
sustainable palm oil, including certification by the Roundtable on
Sustainable Palm Oil (RSPO), include guidelines designed to reduce the
environmental impact of palm oil production. Fire-driven deforestation is
prohibited by law in both countries and a stipulation of RSPO certification,
yet the degree of environmental compliance is unclear, especially during El
Niño events when drought conditions increase fire risk. Here, we used
time series of satellite data to estimate the spatial and temporal patterns
of fire-driven deforestation on and around oil palm plantations. In
Indonesia, fire-driven deforestation accounted for one-quarter of total
forest losses on both certified and noncertified plantations. After the
first plantations in Indonesia received RSPO certification in 2009, forest
loss and fire-driven deforestation declined on certified plantations but did
not stop altogether. Oil palm expansion in Malaysia rarely involved fire;
only 5 % of forest loss on certified plantations had coincident active
fire detections. Interannual variability in fire detections was strongly
influenced by El Niño and the timing of certification. Fire activity
during the 2002, 2004, and 2006 El Niño events was similar among oil palm
plantations in Indonesia that would later become certified, noncertified
plantations, and surrounding areas. However, total fire activity was 75 %
and 66 % lower on certified plantations than noncertified plantations
during the 2009 and 2015 El Niño events, respectively. The decline in
fire activity on certified plantations, including during drought periods,
highlights the potential for RSPO certification to safeguard carbon stocks in
peatlands and remaining forests in accordance with legislation banning fires.
However, aligning certification standards with satellite monitoring
capabilities will be critical to realize sustainable palm oil production and
meet industry commitments to zero deforestation.
... The estimated fraction of fire-driven deforestation for different land management categories in this study is likely conservative because satellite platforms do not detect all fires. Satellite sensors may not sample at the peak of diurnal fire activity (Giglio et al., 2000), and cloud obscuration and orbital coverage (Schroeder et al., 2005) reduce the probability of fire detections, particularly for low-latitude regions with persistent cloud cover such as Southeast Asia. New satellite products partially overcome these limitations through improvements in orbital coverage and spatial resolution (Schroeder et al., 2014), especially for detection of small and low-intensity fires in deforestation or peatland areas (Schroeder et al., 2015;Elvidge et al., 2015). ...
Indonesia and Malaysia have emerged as leading producers of palm oil in the past several decades, expanding production through the conversion of tropical forests to industrial plantations. Efforts to produce "sustainable" palm oil, including certification by the Roundtable on Sustainable Palm Oil (RSPO), include guidelines designed to reduce the environmental impact of palm oil production. Fire-driven deforestation is prohibited by law in both countries and a stipulation of RSPO certification, yet the degree of environmental compliance is unclear, especially during El Niño events when drought conditions increase fire risk. Here, we used time series of satellite data to estimate the spatial and temporal patterns of fire-driven deforestation in and around oil palm plantations. In Indonesia, fire-driven deforestation accounted for one quarter of total forest losses in both certified and non-certified plantations. After the first plantations in Indonesia received RSPO certification in 2009, forest loss and fire-driven deforestation declined in certified plantations but did stop altogether. Oil palm expansion in Malaysia rarely involved fire; only 6 % of forest loss in certified plantations had coincident active fire detections. Interannual variability in fire detections was strongly influenced by El Niño and the timing of certification. Fire activity during the 2002, 2004, and 2006 El Niño event was similar among oil palm plantations in Indonesia that would later become certified, non-certified plantations, and surrounding areas. However, rates of fire activity were 57 % and 44 % lower in certified plantations than non-certified plantations during the 2009 and 2015 El Niño events, respectively. The decline in fire activity on certified plantations, including during drought periods, highlights the potential for RSPO certification to safeguard carbon stocks in peatlands and remaining forests and support legislation banning fires. However, aligning certification standards with satellite monitoring capabilities will be critical to realize sustainable palm oil production and meet industry commitments to zero deforestation.
... Before the advent of satellite remote sensing, smoke emissions were estimated through small-scale biomass burning experiments, modeling, or by approximation based on proxy data such as population or cultural practices (e.g., Seiler and Crutzen, 1980; Hao and Liu, 1994; Liousse et al., 1996). The satellite era has brought significant improvement in biomass burning characterization and emissions estimation (e.g., Dozier, 1981; Prins and Menzel, 1992; Justice et al., 1993 Justice et al., , 2002 Cahoon et al., 1994; Kaufman et al., 1998; Giglio et al., 2003 Giglio et al., , 2008 Wooster et al., 2003 Ito and Penner, 2004; Ichoku and Kaufman, 2005; Ichoku et al., , 2012 Schroeder et al., 2005 Schroeder et al., , 2014 van der Werf et al., 2006 van der Werf et al., , 2010 Giglio, 2007; Roberts and Wooster, 2008; Zhang et al., 2008; Reid et al., 2009; Vermote et al., 2009; Kaiser et al., 2012). Despite the considerable advancement achieved in satellite remote sensing and atmospheric modeling during the last couple of decades, there still remains a large uncertainty in the overall atmospheric impacts of aerosols and certain shortlived trace gases, particularly those originating from biomass burning such as BC and carbon monoxide (CO) (e.g., Urbanski et al., 2011; Yurganov et al., 2011; Ichoku et al. 2012; Bond et al., 2013). ...
Fire emissions estimates have long been based on bottom-up approaches that
are not only complex, but also fraught with compounding uncertainties. We
present the development of a global gridded
(1° × 1°) emission coefficients (Ce)
product for smoke total particulate matter (TPM) based on a top-down approach
using coincident measurements of fire radiative power (FRP) and aerosol
optical thickness (AOT) from the Moderate-resolution Imaging
Spectro-radiometer (MODIS) sensors aboard the Terra and Aqua satellites. This
new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce
product has now been released to the community and can be obtained from
... Firstly, insufficient data can arise from asynchronous fire activity and satellite detections, low satellite detection thresholds due to sensor characteristics, limited number of overpasses, landscape heterogeneity, cloud cover and smoke [51,[60][61][62]. Small or short duration or fast moving or low intensity fires are likely to be more affected by satellite omissions [60]. ...
Each wildfire has its own “history”, burns under specific conditions and leads to unique environmental impacts. Information on where and when it has started and its duration is important to improve understanding on the dynamics of individual wildfires. This information is typically included in fire databases that are known to have: (i) multiple error sources; (ii) limited spatial coverage and/or time span, and; (iii) often unknown accuracy and uncertainty. Satellite data have a large potential to reduce such limitations. We used active fire data from the MODerate Resolution Imaging Spectroradiometer (MODIS) to estimate fire start/end dates and ignition location(s) for large wildfires that occurred in Alaska, Portugal, Greece, California and southeastern Australia.
We assessed the agreement between satellite-derived estimates and data from fire databases, and determined the associated uncertainty. Fire dates and ignition location(s) were estimated for circa 76% of the total burnt area extent for the five study regions. The ability to estimate fire dates and ignitions from satellite data increased with fire size. The agreement between reported and estimated fire dates was very good for start dates (Model efficiency index, MEF = 0.91) and reasonable for end dates (MEF = 0.73). The spatio-temporal agreement between reported and satellite-derived wildfire ignitions showed temporal lags and distances within 12 h and 2 km, respectively. Uncertainties associated with ignition estimates were generally larger than the disagreements with data reported in fire databases. Our results show how satellite data can contribute to improve information regarding dates and ignitions of large wildfires. This contribution can be particularly relevant in regions with scarce fire information, while in well-documented areas it can be used to complement, potentially detect, and correct inconsistencies in existing fire databases. Using data from other existing and/or upcoming satellites should significantly contribute to reduce errors and uncertainties in satellite-derived fire dates and ignitions, as well as improve coverage of small fires.
... Schroeder et al. [51] have quantified the impact of cloud obscuration for GOES active fires in the Brazilian Amazonia, showing active fires omissions around 15% due to cloud cover. When assessing fire continuity over time and space, Schroeder et al. [52] suggest the integration of multiple datasets in order to reduce the uncertainties in fire counts when derived using a single system. Giglio et al. [24] also pointed out that BA detection may benefit from the fusion of multi-sensor active fire observations. ...
The Brazilian Cerrado is significantly affected by anthropic fires every year, which makes the region an important source of pyrogenic emissions. This study aims at generating improved 1 km monthly burned area maps for Cerrado based on remote-sensed information. The algorithm relies on a burn-sensitive vegetation index based on MODIS daily values of near and middle infrared reflectance and makes use of active fire detection from multiple sensors. Validation is performed using reference burned area (BA) maps derived from Landsat imagery. Results are also compared with MODIS standard BA products. A monthly BA database for the Brazilian Cerrado is generated covering the period 2005-2014. Estimated value of BA is 1.3 times larger than the value derived from reference data, making the product suitable for applications in fire emission studies and ecosystem management. As expected the intra and inter-annual variability of estimated BA over the Brazilian Cerrado is in agreement with the regime of precipitation. This work represents the first step towards setting up a regional database of BA for Brazil to be developed in the framework of BrFLAS, an R and D project in the areas of fire emissions and ecosystem management planning.
... The MODIS sensor can detect flaming fires (~1,000 Kelvin) as small as 100 m 2 under ideal conditions with a 50% detection probability, and it can detect a 1,000-2,000 m 2 smoldering fire (~600 Kelvin) (Kaufman et al., 1998;Gigolo et al., 2003;Hawbaker et al., 2008). The detection rates will be higher if the daily peak fire activity coincides with the time of satellite overpass (Schroeder et al., 2005). ...
Increasing incidences of fire from land conversion and residue burning in tropics is the major concern in global warming. Spatial and temporal monitoring of trends of fire incidences is, therefore, significant in order to determine contribution of carbon emissions from slash and burn agriculture. In this study, we analyzed time-series Terra / Aqua MODIS satellite hotspot products from 2001 to 2013 to derive intra- and inter-annual trends in fire incidences in Nagaland state, located in the Indo-Burma biodiversity hotspot. Time-series regression was applied to MODIS fire products at variable spatial scales in GIS. Significance of change in fire frequency at each grid level was tested using t statistic. Spatial clustering of higher or lower fire incidences across study area was determined using Getis-OrdGi statistic. Maximum fire incidences were encountered in moist mixed deciduous forests (46%) followed by secondary moist bamboo brakes (30%). In most parts of the study area fire incidences peaked during March while in warmer parts (e.g. Mon district dominated by indigenous people) fire activity starts as early as during November and peaks in January. Regression trend analysis captured noticeable areas with statistically significant positive (e.g. Mokokchung, Wokha, Mon, Tuensang and Kiphire districts) and negative (e.g. Kohima and north-western part of Mokokchung district) inter-annual fire frequency trends based on area-based aggregation of fire occurrences at different grid sizes. Localization of spatial clusters of high fire incidences was observed in Mokokchung, Wokha, Mon,Tuensang and Kiphire districts.
... They showed that in some regions 15% of GOES active fires were omitted due to cloud cover. When assessing fire continuity over time and space, Schroeder et al. (2005) suggest the integration of multiple datasets in order to reduce the uncertainties in fire counts when derived using a single system. Giglio et al. (2009) also pointed out that BA detection may benefit from the fusion of multi-sensor active fire observations. ...
This work presents an automated regional algorithm that allows detecting burned areas in Brazil based on information from TERRA/AQUA MODIS data. The procedure relies on the so-called W burning index, that requires daily reflectance from the 1km MODIS Level 1B calibrated radiance from bands 2 (near infrared) and 20 (middle infrared). Burned pixels are first identified as those located in the neighbourhood of active fires and associated to values of W and temporal changes in W larger than a fixed threshold. Pixels in the neighbourhood of the previously identified ones are then tested as burned ones based on contextual tests performed on associated values of W and temporal changes in W. Validation of results was performed over Cerrado region using high resolution burned area maps derived from Landsat imagery, paying special attention to the omission and commission errors. For comparison, validation of NASA/MODIS burned area products MCD45A1 and MCD64A1 is also carried out over the same area. Results from the new algorithm present considerably lower omission error when compared to NASA/MODIS products. The two NASA products present very low commission errors (ranging from 2 to 10%) but they are affected by very high occurrence of omission errors (greater than 60% in almost all cases analysed). The new product has larger commission errors (ranging from 20 to 40%) but a large fraction of those (more than 40%) occur at the borders of the scars and may therefore not be strictly viewed as false alarms; there is also a clear reduction of the omission cases (below 40% in all cases).
... only limited thermal remote sensing research has indicated the potential to infer whether a fire is flaming or smouldering . Fire type and cause information have been mostly evaluated via fire behaviour and effects modelling frameworks (Sullivan, 2009;hyde et al., 2011) or inferred based on geographical context and proximity of satellite fire detections relative to thematic land cover classes, and features such as rivers, roads and forest edges (Nepstad et al., 2001;Schroeder et al., 2005;Morton et al., 2008). ...
Space-borne sensors provide the only way to monitor the global distribution and characteristics of fire. Dramatic satellite maps showing fire activity across the entire Earth have been providing a unique picture of fire activity for the last three decades. This chapter demonstrates the key role that satellite remote sensing can play in providing spatially and temporally explicit data and derived data products for monitoring of wildfires. Data from satellite remote sensing systems have been used to monitor smoke plumes, the extent of fire-affected areas, flaming and smouldering fire locations and timing, and to characterize various fire properties.
... only limited thermal remote sensing research has indicated the potential to infer whether a fire is flaming or smouldering . Fire type and cause information have been mostly evaluated via fire behaviour and effects modelling frameworks (Sullivan, 2009;hyde et al., 2011) or inferred based on geographical context and proximity of satellite fire detections relative to thematic land cover classes, and features such as rivers, roads and forest edges (Nepstad et al., 2001;Schroeder et al., 2005;Morton et al., 2008). ...
White ash results from the complete combustion of surface fuels, making it a logically simple retrospective indicator of surface fuel consumption. However, the strength of this relationship has been neither tested nor adequately demonstrated with field measurements. We measured surface fuel loads and cover fractions of white ash and four other surface materials (green vegetation, brown non-photosynthetic vegetation, black char and mineral soil) immediately before and after eight prescribed fires in four disparate fuelbed types: boreal forest floor, mixed conifer woody slash, mixed conifer understorey and longleaf pine understorey. We hypothesised that increased white ash cover should correlate significantly to surface fuel consumption. To test this hypothesis, we correlated field measures of surface fuel consumption with field measures of surface cover change. Across all four fuelbed types, we found increased white ash cover to be the only measure of surface cover change that correlated significantly to surface fuel consumption, supporting our hypothesis. We conclude that white ash load calculated from immediate post-fire measurements of white ash cover, depth and density may provide an even more accurate proxy for surface fuel consumption, and furthermore a more physically based indicator of fire severity that could be incorporated into rapid response, retrospective wildfire assessments.
... For example, the tropical grasslands and savannas in Brazil and South Africa are ecosystems intensely modified by human activities. Fires in these regions are mostly related to agricultural practices due to land conversion or crop and pasture maintenance (Alencar, Asner, Knapp, & Zarin, 2011;Morton et al., 2008;Schroeder et al., 2005;Stocks et al., 1996). ...
... About 17 % of the Pantanal has been deforested and 63 % of the natural vegetation cover of the surrounding plateaus in the Planalto (savanna woodland and semi-deciduous forest) has been lost through the use of fires induced by ranchers to rid the natural vegetation for cattle farming. The fire frequency per unit area in Pantanal is the highest among different biomes in Brazil (Schroeder et al. 2005). Another large, fireimpacted, subtropical wetland ecosystem is the Okavango Delta in Botswana, Africa. ...
Wetlands are ecosystems commonly characterized by elevated levels of dissolved organic carbon (DOC), and although they cover a surface area less than 2 % worldwide, they are an important carbon source representing an estimated 15 % of global annual DOC flux to the oceans. Because of their unique hydrological characteristics, fire can be an important ecological driver in pulsed wetland systems. Consequently, wetlands may be important sources not only of DOC but also of products derived from biomass burning, such as dissolved black carbon (DBC). However, the biogeochemistry of DBC in wetlands has not been studied in detail. The objective of this study is to determine the environmental dynamics of DBC in different fire-impacted wetlands. An intensive, 2-year spatial and temporal dynamics study of DBC in a coastal wetland, the Everglades (Florida) system, as well as one-time sampling surveys for the other two inland wetlands, Okavango Delta (Botswana) and the Pantanal (Brazil), were reported. Our data reveal that DBC dynamics are strongly coupled with the DOC dynamics regardless of location, season or recent fire history. The statistically significant linear regression between DOC and DBC was applied to estimate DBC fluxes to the coastal zone through two main riverine DOC export routes in the Everglades ecosystem. The presence of significant amounts of DBC in these three fire-impacted ecosystems suggests that sub-tropical wetlands could represent an important continental-ocean carrier of combustion products from biomass burning. The discrimination of DBC molecular structure (i.e. aromaticity) between coastal and terrestrial samples, and between samples collected in wet and dry season, suggests that spatially-significant variation in DBC source strength and/or degree of degradation may also influence DBC dynamics.
... However, remote sensing methods have limitations that can cause errors in final burned area products [19]. Major factors include the presence of clouds, which significantly reduces the ability to detect a fire hotspot due to the attenuation of the spectral radiance emitted by the flaming and smoldering phases in the biomass burning process [20], the lack of data on the moment of fire occurrence and, especially, the incompatibility of the spatial resolutions of some sensors, making these sensors unsuitable for the identification of fires [21][22][23]. ...
The objective of this study was to analyze the spatial and temporal distribution of burned areas in Rondônia State, Brazil during the years 2000 to 2011 and evaluate the burned area maps. A Linear Spectral Mixture Model (LSMM) was applied to MODIS surface reflectance images to originate the burned areas maps, which were validated with TM/Landsat 5 and ETM+/Landsat 7 images and field data acquired in August 2013. The validation presented a correlation ranging from 67% to 96% with an average value of 86%. The lower correlation values are related to the distinct spatial resolutions of the MODIS and TM/ETM+ sensors because small burn scars are not detected in MODIS images and higher spatial correlations are related to the presence of large fires, which are better identified in MODIS, increasing the accuracy of the mapping methodology. In addition, the 12-year burned area maps of Rondônia indicate that fires, as a general pattern, occur in areas that have already been converted to some land use, such as vegetal extraction, large animal livestock areas or diversified permanent crops. Furthermore, during the analyzed period, land use conversion associated with climatic events significantly influenced the occurrence of fire in Rondônia and amplified its impacts.
... mirror/lbaeco). During the monitoring, doubts as to satellite coverage and hot spot counts were raised and resolved by communication between scientists at INPE, in Acre, and those at NASA/University of Maryland who already had begun working together in previous years Schroeder et al., 2005]. ...
From mid‐July to mid‐October 2005, an environmental disaster unfolded in the trinational region of Madre de Dios, Peru; Acre, Brazil; and Pando, Bolivia (the MAP region), in southwestern Amazonia. A prolonged dry season and human‐initiated fires resulted in smoke pollution affecting more than 400,000 persons, fire damage to over 300,000 hectares of rain forest, and over US$50 million of direct economic losses. Indicatorrs suggest that anomalous drought conditions could occur again this year.
In May 2005, river levels, were the lowest in 34 years in Rio Branco,Acre, Brazil, signaling that the subsequent dry season would be unusual. Rainfall became virtually absent for several months, not only in eastern Acre but also in the neighboring Bolivian department of Pando and the Peruvian region of Madre de Dios. This enhanced dry season extended over much of western Amazonia with severe societal impact; by October 2005, regional governments had declared states of emergency in Pando, Acre, and Amazonas, an area covering more than a million square kilometers. Whereas previous droughts could be linked to El Niño events [ Williams et al ., 2005; Marengo, 2004]], J. A. Marengo et al. (The drought of Amazonia in 2005, manuscript in preparation, 2006) suggest that this drought was not related to El Niño but was instead associated with anomalously warm surface water in the tropical North Atlantic, similar to a previous drought in 1963–1964.
... Deforestation fires may continue after the initial clearing, either to remove residual biomass to permit mechanized agriculture [56], or to allow for removal of higher biomass levels in more recent clearings [70]. Concurrently, expansion of the area under agricultural management may elevate the base level of fire activity associated with land management [71][72][73]. Finally, other fire types such as understory forest fires probably account for some fraction of the observed increase in DFI in areas with small clearing sizes [74,75]. ...
Background: Landscape fires in South America have considerable impacts on ecosystems, air quality and the climate system. We examined long-term trends and interannual variability of forest, savanna and agricultural fires for the continent during 2001–2012 using multiple satellite-derived fire products. Results: The annual number of active fires in tropical forests increased significantly during 2001–2005. Several satellite-derived metrics, including fire persistence, indicated that this trend was mostly driven by deforestation. Fires between 2005 and 2012 had a small decreasing trend and large year-to-year changes that were associated with climate extremes. Fires in savannas and evergreen forests increased in parallel during drought events in 2005, 2007 and 2010, suggesting similar regional climate controls on fire behavior. Deforestation fire intensity (the number of fires per unit of deforested area) increased significantly within the Brazilian Amazon in areas with small-scale deforestation. Conclusion: Fires associated with forest degradation are becoming an increasingly important component of the fire regime and associated carbon emissions.
... Despite improved fire detection capabilities, the use of Terra and Aqua MODIS active fire data alone may not meet the requirements for vegetation fire monitoring or fire-related studies, given the heterogeneity of Amazon fires in both time and space. Changing conditions between a fire's flaming and smoldering stages, along with the temperature of the background materials, the time of satellite overpass, and variable cloud coverage, can cause the number of fire detections to vary considerably over different products, making data interpretation difficult (Fig. 29.7) (Schroeder et al. 2005(Schroeder et al. , 2007. To characterize vegetation fire dynamics at the local, regional, or global scales, it becomes important to link multiple active fire observations from available satellites. ...
The NASA MODIS global fire data products are digital maps calculated
from Terra and Aqua MODIS data, designed primarily to serve the needs of
the emissions modeling community. The algorithms were designed to
provide a comprehensive global product, and to perform well over the
expected range of fire conditions and scene variability. The goal was to
maximize product accuracy, and minimize errors of commission and
omission. Two products exist, including one, which characterizes
actively burning fire locations at satellite overpass time, and two,
which depicts the area burned, also called fire-affected areas (URL 1).
Since the launch of Terra and Aqua, the user community has expanded to
include federal agencies with operational fire monitoring mandates and
natural resource managers as well the intended global change
researchers.
... Careful consideration of the limitations of comparison between sensors at multiple scales would obviously be needed [Schroeder et al., 2005]. ...
Biomass burning is an important global phenomenon affecting atmospheric
composition with significant implications for climatic forcing. Wildland
fire is the main global source of fine primary carbonaceous aerosols in
the form of organic carbon (OC) and black carbon (BC), but uncertainty
in aerosol emission estimates from biomass burning is still rather
large. Application of satellite based measures of fire radiative power
(FRP) has been demonstrated to offer an alternative approach to estimate
biomass consumed with the potential to estimate the associated emissions
from fires. To date, though, no study has derived integrated FRP
(referred to as fire radiative energy or FRE) at a global scale, in part
due to limitations in temporal or spatial resolution of satellite
sensors. The main objective of this research was to quantify global
biomass burning emissions of organic and black carbon aerosols and the
corresponding effect on planetary radiative forcing. The approach is
based on the geophysical relationship between the flux of FRE emitted,
biomass consumed, and aerosol emissions. Aqua and Terra MODIS
observations were used to estimate FRE using a simple model to
parameterize the fire diurnal cycle based on the long term ratio between
Terra and Aqua MODIS FRP and cases of diurnal satellite measurements of
FRP made by the geostationary sensor SEVIRI, precessing sensor VIRS, and
high latitude (and thus high overpass frequency) observations by MODIS.
Investigation of the atmospheric attenuation of MODIS channels using a
parametric model based on the MODTRAN radiative transfer model indicates
a small bias in FRE estimates which was accounted for. Accuracy
assessment shows that the FRE estimates are precise (R2 = 0.85), but may
be underestimated. Global estimates of FRE show that Africa and South
America dominate biomass burning, accounting for nearly 70% of the
annual FRE generated. The relationship between FRE and OCBC estimates
made with a new MODIS-derived inversion product of daily integrated
biomass burning aerosol emissions was explored. The slope of the
relationship within each of several biomes yielded a FRE-based emission
factor. The biome specific emission factors and FRE monthly data were
used to estimate OCBC emissions from fires on a global basis for 2001 to
2007. The annual average was 17.23 Tg which was comparable to previously
published values, but slightly lower. The result in terms of global
radiative forcing suggests a cooling effect at both the
top-of-atmosphere (TOA) and surface approaching almost - 0.5 K which
implies that biomass burning aerosols could dampen the warming effect of
green house gas emissions. An error budget was developed to explore the
sources and total uncertainty in the OCBC estimation. The results
yielded an uncertainty value of 58% with specific components of the
process warranting future consideration and improvement. The uncertainty
estimate does not demonstrate a significant improvement over current
methods to estimate biomass burning aerosols, but given the simplicity
of the approach should allow for refinements to be made with relative
ease.
... In Amazonia, periods of lower precipitation co-occur with peaks of fire activity (Aragão 61 et al., 2008). Moreover, anomalous climatic conditions, such as warming of sea-surface 62 temperatures (SSTs) in the tropical eastern Pacific (El Niño) and warming of SSTs in the 63 tropical North Atlantic (the Atlantic dipole), can exacerbate the severity of the dry season 64 (Cox et al., 2008;Marengo et al., 2008Marengo et al., , 2011, providing favorable conditions for large-scale 65 fire events (Schroeder et al., 2005). In 2005, anomalously high SSTs in the tropical North 66 ...
Areas affected by forest fires that occurred in 2005 were mapped in the municipalities of Boca do Acre and Lábrea (in the southern part of Brazil’s state of Amazonas) and estimates were made of the loss of biomass and carbon stock and the committed emissions from increased tree mortality due to fire. Fire scars observed on Landsat-5 TM satellite images from 2004 to 2006 were visually interpreted and digitized; over 865.6 km2 of forest affected by fire were mapped, the majority (2.9% of the total forest cover) concentrated along the southern edges of the municipalities, which border on the states of Rondônia and Acre. The greatest loss of biomass due to the increase in tree mortality was indicated by the survey made 4 years after the fires: 4.5 × 106 Mg total (above + below-ground) and 3.7 × 106 Mg (only above-ground). Consequently, 2.2 × 106 Mg C (total) and 1.8 × 106 Mg C (above-ground) of potential carbon emissions were committed from the initial burn of forest biomass and from trees killed by the fire. Emissions occur both through oxidation of dead biomass by decomposition or through combustion in subsequent fire events. Our results indicate that fires can affect extensive tracts of forest and can emit significant amounts of carbon to the atmosphere in periods of drought. Fire plays a significant role as a threat to the biological balance of the forest and causes loss of biomass and emission of greenhouse gases that have critical implications for the future of forests in the Amazon.
Fire in seasonally inundated floodplains sounds like a contradictory issue. Nevertheless, many tropical and subtropical wetlands in the world, such as Pantanal, are fire-prone. Fire can interact with inundation in these systems determining variation in their vegetation structure, functioning, and composition. This chapter aims to describe the fire regime in the Pantanal floodplain and to review the available literature on the present knowledge about the effects of fire combined with flooding on its vegetation. For that, we searched the number of heat points in Brazilian Pantanal using satellite images from 1999 to 2020. Besides, we searched for published papers and books dealing with fire in the Pantanal vegetation. During that period, all subregions of the Pantanal had fire events. The periodicity of fire occurrence, according to these records, is nearly every second year. The year of most extensive fire was 2020. The most fire-prone zone in the Pantanal comprises the seasonal floodplains of the Paraguay and Miranda rivers, which are also among the most floodable areas in the Pantanal. This area we called here “the corridor of fire and flood.” Fires have been occurring in the Pantanal even before human occupation and can be considered a crucial ecological filter in the region. We present information on 805 species that have some relation to fire. The most common relationship is to resprout after the fire because of adaptations such as underground systems. Most of these species are grasses. Many species are resistant because of their corky bark and are prevalent in Cerrado vegetation. Fire combined with inundation can promote changes in richness, abundance, and composition of species. Fire can change the tendencies of these parameters along the flooding gradient. We verified that fire is part of the landscape in the Pantanal and has an essential role in determining its open and savanna physiognomy, mainly when combined with inundation. In the future, with more available scientific information, controlled fire will be an important tool to be considered for the management of natural systems in the Pantanal.KeywordsFireFlooding gradientPlant regenerationWetlandVegetation structure
Tropical wetlands are ecosystems of great ecological importance, but their loss has accelerated in recent decades. Even though its hydrological, geological, and chemical characteristics make the Pantanos de Centla Biosphere Reserve (PCBR) the most significant wetland in Mesoamerica, it is the worst affected by forest fires area each year of Tabasco, México. Satellite remote sensing is proposed as a cost-effective alternative to locate and delimit fire-affected surfaces in these difficult-to-access environments more precisely. The objective of the present study was to determine the optimal Landsat 8 spectral index for the detection of burned areas within the PCBR. It was possible to identify and extract 41 disturbed areas in six years. These areas were submitted to calculate six spectral burn indices, widely tested in detecting fire scars in forest areas, BAI, MIRBI, NBR, NBR2, NBRT1, NBRT3, including the best-known vegetation index NDVI. The capacity of each index to discriminate burned areas was estimated by comparing them with each other by using a separability index. The comparisons of the annual coefficients of variation allowed the evaluation of separability dispersion, indicating how homogeneous each index was. MIRBI was identified as the index with the highest potential for discrimination of burned areas in the PCBR, followed by far by NBR2. It is expected that these results can serve, among other things, to characterize, evaluate and prioritize monitoring areas to contribute by updating and improving the fire management plan in the PCBR. They are also expected to help subsequent studies on fire dynamics associated with human activities that cause and impact fire, such as burn severity, biomass loss, and post-fire vegetation regeneration.
In this work we analyze spatial variability of forest fires detected in the Legal Amazon region during the period 2000-2013, using the lacunarity method. The results show that for years with higher number of forest fires, the values of lacunarity were lower (indicating more homogeneous behavior), while for years with lower number of forest fires, the values of lacunarity were higher (indicating more heterogeneous behavior). The different properties of spatial distribution of forest fires are also observed for rainy and dry season
Estimates of fire emissions remain uncertain due to limited constraints on the variations in fire characteristics. Here we demonstrate the utility of space-based observations of smoke constituents in addressing this limitation. We introduce a satellite-derived smoke index (SI) as an indicator of the dominant phase of large-scale fires. This index is calculated as the ratio of the geometric mean of observed fractional enhancements (due to fire) in carbon monoxide and aerosol optical depth to that of nitrogen dioxide. We assess the usefulness of this index on fires in the Amazon. We analyze the seasonal, regional, and interannual joint distribution of SI and fire radiative power (FRP) in relation to fire hotspots, land cover, drought severity index, and deforestation rate estimates. We also compare this index with an analogous quantity derived from field data or emission inventories. Our results show that SI changes from low (more flaming) to high (more smoldering) during the course of a fire season, which is consistent with the changes in observed maximum FRPs from high to low. We also find that flaming combustion is more dominant in areas where deforestation fires dominate, while smoldering combustion has a larger influence during drought years when understory fires are more likely enhanced. Lastly, we find that the spatiotemporal variation in SI is inconsistent with current emission inventories. Although we recognize some limitations of this approach, our results point to the utility of SI as a proxy for overall combustion efficiency in the parameterization of fire emission models.
Fire has been used since the first humans arrived in Amazonia; however, it has recently become a widely used instrument for large-scale forest clearance. Patterns of fire incidence in the region have been exacerbated by recent drought events. Understanding temporal and spatial fire patterns as well as their consequences for forest structure, species composition, and the carbon cycle is critical for minimising global change impacts on Amazonian ecosystems and people. In this chapter, we provide an overview of the state of our knowledge on the spatial and temporal patterns of fire incidence in Amazonia, depicting the historical fire usage in the region, their relationship with land use and land cover, and their responses to climate seasonality and droughts. We subsequently focus on the impacts of fire, by quantifying the extent of burnt forests during major droughts and describing the main impacts on forest structure, composition, and carbon stocks. Finally, we present an overview of modelling initiatives for forecasting fire incidence in the region. We conclude by providing a comprehensive view of the processes that influence fire occurrence, potential feedbacks, and impacts in Amazonia. We also highlight how key areas within fire ecology must be improved for a better understanding of the long-term effect of fire on the Amazon forest ‘biome’.
The objectives of the fire mapping and monitoring theme of the global observation of forest and landcover dynamics (GOFC-GOLD) program are to refine and articulate the international requirements for fire related observations, to increase access to and make the best possible use of existing and future observing systems for fire management, policy decision-making and global change research and to ensure the provision of long-term, systematic satellite observations necessary for the production of the full suite of recommended fire products. The GOFC-GOLD Fire Implementation Team also fostered the development of regional networks of data providers and users to capture regional specific information needs and priorities. This chapter discusses specific goals of the program related to pre-fire evaluation, fire observations and post-fire assessment, and the implementation status of corresponding activities. Examples of contributory programs from US agencies are also presented.
In this work we study the long-term correlations in the satellite daily number of hot pixels recorded in the Brazilian Amazon during the period 1999-2012. While the highest peak in daily hot pixel frequencies occurred in 2007, coincident with a severe drought, for other intense droughts such as that occurred in 2005 (one-in-a-hundred year event for its high severity) and 2010, the corresponding number of hot pixels recorded was compatible or lower than that reached during e.g. 2004, with no reported severe drought. On the other hand, we find that the most severe droughts coincide with the peaks of the Detrended Fluctuation Analysis (DFA) scaling exponent of the time series of the daily anomalies in hot pixels. This finding is striking because it highlights the effectiveness of the DFA in disclosing that long-term hot pixel anomaly correlations are clearly associated with the drought events, that were not identifiable by examining hot pixel frequencies of the original time series. The dynamics of the time series of daily anomalies in hot pixels is, therefore, influenced by drought events. The coincidence of the peaks of the scaling exponent with drought events suggests the increase of the persistence of the hot pixel time series during the driest periods.
Changes in weather and land use are transforming the spatial and temporal characteristics of fire regimes in Amazonia, with important effects on the functioning of dense (i.e., closed-canopy), open-canopy, and transitional forests across the Basin. To quantify, document, and describe the characteristics and recent changes in forest fire regimes, we sampled 6 million ha of these three representative forests of the eastern and southern edges of the Amazon using 24 years (1983-2007) of satellite-derived annual forest fire scar maps and 16 years of monthly hot pixel information (1992-2007). Our results reveal that changes in forest fire regime properties differentially affected these three forest types in terms of area burned and fire scar size, frequency, and seasonality. During the study period, forest fires burned 15% (0.3 million ha), 44% (1 million ha), and 46% (0.6 million ha) of dense, open, and transitional forests, respectively. Total forest area burned and fire scar size tended to increase over time (even in years of average rainfall in open canopy and transitional forests). In dense forests, most of the temporal variability in fire regime properties was linked to El Nino Southern Oscillation (ENSO)-related droughts. Compared with dense forests, transitional and open forests experienced fires twice as frequently, with at least 20% of these forests' areas burning two or more times during the 24-year study period. Open and transitional forests also experienced higher deforestation rates than dense forests. During drier years, the end of the dry season was delayed by about a month, which resulted in larger burn scars and increases in overall area burned later in the season. These observations suggest that climate-mediated forest flammability is enhanced by landscape fragmentation caused by deforestation, as observed for open and transitional forests in the Eastern portion of the Amazon Basin.
Fire emissions estimates have long been based on bottom-up approaches that are not only complex, but also fraught with compounding uncertainties. We present the development of a global gridded (1° × 1°) emission coefficients (Ce) product for smoke total particulate matter (TPM) based on a top-down approach using coincident measurements of fire radiative power (FRP) and aerosol optical thickness (AOT) from the Moderate-resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Terra and Aqua satellites. This new Fire Energetics and Emissions Research version 1.0 (FEER.v1) Ce product has now been released to the community and can be obtained from
Abstract Understanding the variability of fire events and their relationship to precipitation and changes in land use and land cover is essential in order to evaluate the susceptibility of Amazonian vegetation. Time series of hotspots, of deforested area and of rainfall (all derived from satellite data) were used to determine the temporal and spatial distributions of fire in Brazil's state of Amazonas in order to establish the seasonal patterns of each variable and interactions with biomass burning. From 2003 to 2012, 60% of the hotspots detected were in the southern part of the state, with high variability between different months and years. Between 95% and 99% of the hotspots were recorded during the period of greatest occurrence of burning (July to March) with peaks during the months of August, September and October (the months with the lowest precipitation), suggesting that fires in Amazonas are mainly initiated by humans. Deforestation activity occurs approximately three months before the start of the burning activity. The number of hotspots did not show a relationship with the area deforested but showed a strong inverse relationship with rainfall. There is marked seasonal and annual variability, with patterns changing over time. Over the last decade the hotspots detected in Amazonas are associated not only with changes in land use and cover, but also with the use of fire in managing deforested areas.
Global and regional-scale estimates of biomass burning emissions rely on satellite data products with varying spatial resolution. In heterogeneous landscapes, moderate-resolution fire location data may not capture fine-scale variation in fuel type, leading to both random and systematic error in emissions. Using 120-meter land cover data for the Amazon basin, we estimate the probability of accurate classification of individual fires at 88% for MODIS and 74% for GOES. Classification error limits the ability of emission models to reproduce patterns of emissions, and can only be reduced by innovative use of current satellite data or ancillary data. Emissions biases caused by spatial error vary with regional distribution of fire types. For regional-scale studies in the Amazon Basin, we estimate emissions biases of +3% to +19% for MODIS and +6% to +39% for GOES. The difference between these two systems is an important consideration for multi-sensor fire applications.
Vegetation fires are becoming increasingly important especially in regions where the proximity to urban areas can result in large populations being directly impacted by such events. During emergency situations, accurate fire location data becomes crucial to assess the affected areas as well as to track smoke plumes and delineate evacuation plans. In this study, the performance of the NOAA/NESDIS Hazard Mapping System (HMS) is evaluated. The system combines automated and analyst‐made fire detections to monitor fires across the conterminous United States. Using 30‐m‐spatial‐resolution ASTER imagery as the main instantaneous validation data, commission and omission error estimates are reported for a subset of HMS automated and analyst‐based fire pixels derived from the Terra MODIS and GOES data.
Abstract As an important agent of climate change and major disturbance to ecosystems, fire isdrawing,increased attention from both scientists and the general public alike. Remote sensing plays an important ,role in obtaining ,quick and complete ,information ,on the occurrence and development,of fires. There currently exist dozens of algorithms that use different satellite sensors to detect and monitor fire activity around the world. This paper provides an overview,of various,AVHRR-based algorithms for detecting active burning inthree general categories: single channel threshold algorithms, multi-channel threshold algorithms, and spatial contextual algorithms. Emphasis of the discussion is placed on their physical principles, merits and limitations, as well as areas of potential improvement. Recommendations, are made ,to address ,some outstanding issues such as cloud cover, surface reflection, and threshold setting. Five fire detection algorithms (IGBP, MODIS, ESA, CCRS, and Giglio et al.) are compared by applying them across the Canadian boreal forest for a six-month,period and comparing,cumulative fire pixels with a ground-truth data set. While fire detection algorithms are generally considered to bemature relative to algorithms for mapping burned areas, the performance of the algorithms under evaluation differs drastically, some producing considerable commission and omission errors. This implies that the hot spot detection algorithms are not robust enough,for global operational use and no single-sensor algorithm,is optimal,to generate global fire products. Suggestions are made to further explore the potential offered by both existing and future sensors that would ,help improve ,the performance ,of fire detection algorithms. 2
Aerosol particles were collected aboard two Brazilian Bandeirante EMB 110 planes, and the University of Washington Convair C-131A aircraft during the Smoke, Clouds, and Radiation-Brazil (SCAR-B) field project in the Amazon Basin in August and September 1995. Aerosols were collected on Nuclepore and Teflon filters. Aerosol size distribution was measured with a MOUDI cascade impactor. Sampling was performed mostly over areas heavily influenced by biomass burning smoke. Particle-induced X ray emission (PIXE) was used to measure concentrations of up to 20 elements (Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, Zr, and Pb). Black carbon (BC) and gravimetric mass analysis were also performed. Instrumental neutron activation analysis (INAA) determined the concentrations of about 15 elements on the Teflon filters. Electron probe X ray microanalysis (EPMA) was used to analyze individual aerosol particles. The average aerosol mass concentration was 105 mugm-3, with a maximum of 297 mugm-3. Black carbon (BC) averaged 5.49 mugm-3, or 1-7% of the aerosol mass load. Five aerosol components were revealed by absolute principal factor analysis: (1) a biomass burning component (responsible for 54% of the aerosol mass and associated with BC, K, Cl, Zn, I, S, Br, Rb, aerosol mass concentration, and other elements); (2) a soil dust aerosol component (15.6% of the aerosol mass); (3) a natural biogenic component (18.7% of the aerosol mass and associated with P, K, S, Ca, Sr, Mg, Mn, Cu and Zn); (4) a second soil dust (5.7% of the aerosol mass and enriched in Si, Ti, and Fe); and (5) a NaCl aerosol component (5.9% of the aerosol mass with Na, Cl, Br, and iodine). Electron microscopy analysis of individual aerosol particles confirmed these five aerosol types. Organic material dominated the aerosol mass and the number concentration of airborne particles. Aerosol size distributions show that the fine mode accounts for 78% of the aerosol mass, centered at 0.33 mum aerodynamic diameter. The coarse mode accounts for 22% of the mass, centered at about 3.2 mum. Black carbon size distributions show a consistent picture, with a mass median diameter centered at about 0.175-0.33 mum aerodynamic diameter. This study suggests that for modeling the optical properties of aerosol in the Amazon Basin, it is essential to use a model that includes the optical and physical properties of at least two aerosol components other than the biomass burning aerosol, namely, natural biogenic aerosol and soil dust.
The Smoke, Clouds, and Radiation-Brazil (SCAR-B) field experiment was conducted in central Brazil and southern Amazonia during the period August 15 to September 20, 1995. This paper presents an overview of atmospheric conditions during the SCAR-B period. A meteorological office was established in Brasilia to support the mission flights and field activities. All the meteorological data collected during the SCAR- B have been archived and are available to the scientific community. The meteorological conditions throughout the SCAR-B period of August and September 1995 were near climatological conditions. Few synoptic-scale waves traveling from southeastern Pacific reached Brazil, therefore the SCAR-B period was characterized by long periods of low humidity, dryness, little cloudiness, or rain, and haze events. The stable situation was interrupted due to the penetration of a frontal system on September 20, 1995, and a second and more rain-producing one on September 28, 1995. Those two frontal systems in a period of 10 days brought an end to the dry season. Air particle trajectories show that most of the smoke below 4 km from Amazonia was transported to the south and then to the east exiting the continent at 25øS-30øS. Radiative transfer calculations carried out for the clear sky gaseous and aerosol atmosphere show the decrease of the solar radiation absorption in the atmosphere-surface system due to smoke aerosol loading at the value from 5 to 50 W m -2 depending on the aerosol optical thickness, single-scattering albedo, and solar zenith angle.
Vegetation fires occur worldwide, all year round and inject enormous amounts of trace gases and particles into the atmosphere. Nonetheless, there is still great uncertainty as to the global spatial and temporal distribution of vegetation fires. Twenty one months of global, daily, daytime satellite data at 1 km resolution, from April 1992 to December 1993, were processed in order to determine the positions of active vegetation fires. Results from the first twelve months of the study period are presented here. This is the first time that such a global study has been carried out using a long time series data set and a single processing technique. The data set and results discussed provide much improved information on the spatial variability and the seasonality of vegetation fires. They will be of use in the global mapping and modelling of emissions due to biomass burning as well as in the study of the role of fire in land cover maintenance and change. We show that half of the fires detected were on the African continent and over 70% within the tropical belt. Fires were detected in more than 6% of 1 km2 pixels, over land, during the 12-month period and savanna grasslands accounted for over one third of this area.
The present study proposes improved multispectral methods for the detection of vegetation fires and smoke plumes that are applied to south-eastern Africa and Madagascar. Data are provided by the AVHRR dagger sensor onboard the NOAA (11 and 14) satellites. Improvements of a multispectral methods address to fire detection difficulties arising from the low saturation level of AVHRR channel 3, from the presence of clouds and from contrasted vegetation and climate conditions. The methods are based on a multi-channel algorithm using AVHRR data, in visible and thermal ranges. Results are checked against other algorithm and ground concurrent data. It is shown that the presented multispectral methods are able to detect vegetation fires and associated smoke plumes with an improved accuracy. The results evidence clearly the seasonal character of biomass burning. Two maxima are characterized in the reference zone: one in September in Mozambique and the other in October in Eastern Madagascar. We note that fire intensity maxima were accompanied by well developed smoke plumes which could reach more than 50 km.
A temporal sequence of images form the Advanced Very High Resolution Radiometer (AVHRR) orbital sensor along 1.5 year was used to study the response of a savanna site that burnt in the dry season. The Emas National Park of Brazil was monitored with 1.1 km high resolution afternoon images from June 1992 to October 1993 through the responses of channels 1 (0.6mm), 2 (0.9mm), 3 (3.7mm), and of the Normalized DiVerence Vegetation Index (NDVI) combination of channels 1 and 2. Are consumed 23% of the park's 1300 km 2 surface in August 1992; based on a subsequent Landsat Thematic Mapper image, three sub-areas that burnt were chosen for a detailed AVHRR comparative analysis withve sub-areas that did not burn. From the 344 images recorded on diVerent days only 26 were eVectively useful. Channel 1 showed little diVerence for burnt and unburnt vegetation. Channel 2 and NDVI displayed strong evidence of there for up to 13 months, while in channel 3 this period was less than 8 months. However, channel 3 and NDVI presented the strongest evidence of the �re occurrence on a short-term basis. The results support the use of AVHRR products based on channels 2 and 3 to monitor and evaluate the extent of vegetation burn and regrowth in savannas, important information for tropical vegetation.
1] Numerous studies with general circulation models suggest that tropical deforestation can result in regional-scale climate change; namely, increased air temperature and wind speed and reduced precipitation and relative humidity. To quantify how this climate change should affect fire risk, we used the National Center for Atmospheric Research (NCAR) CCM3.2 general circulation model and remote sensing to estimate the effect of tropical deforestation on fire risk through the McArthur forest fire danger index (FFDI). Deforestation reduced precipitation and relative humidity and increased wind speed in the Amazon, Congo, and Indonesia/New Guinea. FFDI increased by 41, 56, and 58% in these three regions, respectively, primarily owing to higher wind speeds and reduced precipitation. Actual fire occurrence in the Amazon, as determined from NOAA-12 images, was strongly correlated with the FFDI calculated from meteorological data (P (0.0001). Using the observed relationship between FFDI and fire occurrence, we estimate increases in fire frequency of 44, 80, and 123%, in the Amazon, Congo, and Indonesia, respectively, with deforestation. In all three regions the largest relative increases in fire risk occurred in the more humid areas with the lowest original fire risk.
1] We combine general circulation modeling (GCM), remote sensing, and field results to identify a positive feedback loop in which clearing of tropical savannas results in warmer and drier climate, accelerated fire frequencies, and further tree cover loss. The GCM simulations indicate that ongoing clearing of tropical savannas increases temperatures and wind speeds and decreases precipitation and relative humidity, substantially increasing fire frequency. Using NOAA-12 satellite images and meteorological data, we estimate that complete savanna clearing will increase fire frequency by 42%. Combining these data with long-term fire studies, we demonstrate that this fire-mediated feedback may already be contributing to declining tree densities in the world's savannas and will become increasingly important as vegetation change continues in the coming century.
This study presents a comprehensive investigation of res across the Canadian boreal forest zone by means of satellite-based remote sensing. A re-detection algorithm was designed to monitor res using daily Advanced Very High Resolution Radiometer (AVHRR) images. It exploits information from multichannel AVHRR measurements to determine the locations of res on satellite pixels of about 1 km2 under clear sky or thin smoke cloud conditions. Daily re maps were obtained showing most of the active res across Canada (except those obscured by thick clouds). This was achieved by rst compositing AVHRR scenes acquired over Canada on a given day and then applying the re-detection algo-rithm. For the re seasons of 1994– 1998, about 800 NOAA/AVHRR daily mosaics were processed. The results provide valuable nation-wide information on re activities in terms of their locations, burned area, starting and ending dates, as well as development. The total burned area as detected by satellite across Canada is estimated to be approximately 3.9, 4.9, 1.3, 0.4 and 2.4 million hectares in 1994, 1995, 1996, 1997 and 1998, respectively. The peak month of burning varies considerably from one year to another between June and August, as does the spatial distribution of res. In general, conifer forests appear to be more vulnerable to burning and res tend to grow larger than in deciduous forests.
The Brazilian Cerrado biome comprises a vertically structured mosaic of grassland, shrubland, and woodland physiognomies with distinct phenology patterns. In this study, we investigated the utility of spectral vegetation indices in differentiating these physiognomies and in monitoring their seasonal dynamics. We obtained high spectral resolution reflectances, during the 2000 wet and dry seasons, over the major Cerrado types at Brasilia National Park (BNP) using the light aircraft-based Modland Quick Airborne Looks (MQUALS) package, consisting of a spectroradiometer and digital camera. Site-intensive biophysical and canopy structural measurements were made simultaneously at each of the Cerrado types including Cerrado grassland, shrub Cerrado, wooded Cerrado, Cerrado woodland, and gallery forest. We analyzed the spectral reflectance signatures, their first derivative analogs, and convolved spectral vegetation indices (VI) over all the Cerrado physiognomies. The high spectral resolution data were convolved to the MODIS, AVHRR, and ETM+ bandpasses and converted to the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) to simulate their respective sensors. Dry and wet season comparisons of the measured biophysical attributes were made with the reflectance and VI data for the different Cerrado physiognomies. We found that three major domains of Cerrado could be distinguished with the dry and wet season spectral signatures and vegetation indices. The EVI showed a higher sensitivity to seasonality than the NDVI; however, both indices displayed seasonal variations that were approximately one-half that found with the measured landscape green cover dynamics. Inter-sensor comparisons of seasonal dynamics, based on spectral bandpass properties, revealed the ETM+-simulated VIs had the best seasonal discrimination capability, followed by MODIS and AVHRR. Differences between sensor bandpass-derived VI values, however, varied with Cerrado type and between dry and wet seasons, indicating the need for inter-sensor VI translation equations for effective multi-sensor applications.
Remote sensing from space is the only technique that can be used operationally to detect, monitor and map biomass burning of tropical forests on large or global scales. However, high and low resolution imagery from existing satellites present many limitations in such studies. This paper discusses some of these limitations based on case studies in the tropical forests of Amazonia. Results showed that Thematic Mapper (TM/Landsat)images provide estimates of the area burned in association with new deforestation, but because of cloud cover and low frequency of acquisition, are limited in indicating the total extent of fire activity. Advanced Very High Resolution Radiometer (AVHRR/NOAA)images detect fires on a daily basis and are suitable for real-time operational use to identify and locate fires, but are of limited value for estimating the area burned or the fire temperature. Pages: 91-103
Fire influences global change and tropical ecosystems through its connection to land-cover dynamics, atmospheric composition, and the global carbon cycle. As such, the climate change community, the Brazilian government, and the Large-Scale BiosphereAtmosphere (LBA) Experiment in Amazonia are interested in the use of satellites to monitor and quantify fire occurrence throughout Brazil. Because multiple satellites and algorithms are being utilized, it is important to quantify the accuracy of the derived products. In this paper the characteristics of two fire detection algorithms are evaluated, both of which are applied to Terras Moderate Resolution Imagine Spectroradiometer (MODIS) data and with both operationally producing publicly available fire locations. The two algorithms are NASAs operational Earth Observing System (EOS) MODIS fire detection product and Brazils Instituto Nacional de Pesquisas Espaciais (INPE) algorithm. Both algorithms are compared to fire maps that are derived independently from 30-m spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. A quantitative comparison is accomplished through logistic regression and error matrices. Results show that the likelihood of MODIS fire detection, for either algorithm, is a function of both the number of ASTER fire pixels within the MODIS pixel as well as the contiguity of those pixels. Both algorithms have similar omission errors and each has a fairly high likelihood of detecting relatively small fires, as observed in the ASTER data. However, INPEs commission error is roughly 3 times more than that of the EOS algorithm. Pages: 1-25
Amzonian deforestation rates are used to determine human effects on the global carbon cycle 1-3 and to measure Brazils progress in curbing forest impoverishment 1,4,5. But this widely used measure of tropical land use tells only part of the story. Here we present field surveys of wood mills and forest burning across Brazilian Amazonia which show that logging crews severely damage 10,000 to 15,000km2yr-1 offorest that are not included in deforestation mapping programmes. Moreover, we find that surface fires bum additionallarge areas of standing forest, the destruction of which is normally not documented. Forest impoverishment due to such fires mar increase dramatically when severe droughts provoke forest leaf-shedding and greater flammability; our regional water-balance model indicates that an estimated 270,000 km2 of forest became vulnerable to fire in the 1998 dry season. Overall, we find that present estimates of annual deforestation for Brazilian Amazonia capture less than half of the forest area that is impoverished each year, and even less during years of severe drOUght. Both logging and fire increase forest vulnerability to future burning",7 and release forest carbon stocks to the atmosphere, potentially doubling net carbon emissions Ifrom regional land-use during severe El Niflo episodes. If this forest impoverishment is to be controIled, then logging activities I need to be restricted or replaced with low-impact timber harvest techniques, and more effective strategies to prevent accidental forest fires need to be implemented. Pages: 505-508
Investigation of the effects of biomass burning aerosols on the surface irradiance were conducted as a part of the Smoke, Clouds, and Radiation-Brazil (SCAR-B) experiment during AugustSeptember 1995. Measurements of broadband and spectral irradiance, in conjunction with measurements of aerosol physical and optical properties (optical depth, phase function, and size distribution) were made under varying conditions of aerosol loading during the SCAR-B field campaign. Estimates of aerosol single scattering albedo (ù0) were made from matching of the measured irradiance values to the model computed irradiances by varying ù0, for observations made under cloudless conditions. Values of ù0, at approximately 550 nm, estimated from this technique using broadband 400700 nm irradiance measurements, ranged from approximately 0.82 to 0.94 for the dates and times of these SCAR-B measurements. Utilizing spectral irradiance data, the model retrieved values of ù0 decreased with increasing wavelength, with the change of ù0 as a function of wavelength differing on different days. Reductions in photosynthetically active radiation (PAR; 400700 nm) incident at the surface were computed to range from about 20 to 45% compared to background aerosol conditions for the 2 month biomass burning season at several locations in the southern Amazon Basin. These large reductions in incident PAR at the surface due to the heavy aerosol loadings could have implications for primary production of sensitive ecosystems. In addition, reductions of total incident solar radiation from aerosol direct radiative effects may have significant impact on reducing surface heating and increasing aerosol layer heating from absorption. © 1998 American Geophysical Union Pages: 31865-31878
We assessed the effects of biophysical and anthropogenic predictors on deforestation in Brazilian Amazonia. This region has the world's highest absolute rates of forest destruction and fragmentation.
Using a GIS, spatial data coverages were developed for deforestation and for three types of potential predictors: (1) human-demographic factors (rural-population density, urban-population size); (2) factors that affect physical accessibility to forests (linear distances to the nearest paved highway, unpaved road and navigable river), and (3) factors that may affect land-use suitability for human occupation and agriculture (annual rainfall, dry-season severity, soil fertility, soil waterlogging, soil depth). To reduce the effects of spatial autocorrelation among variables, the basin was subdivided into >1900 quadrats of 50 × 50 km, and a random subset of 120 quadrats was selected that was stratified on deforestation intensity. A robust ordination analysis (non-metric multidimensional scaling) was then used to identify key orthogonal gradients among the ten original predictor variables.
The ordination revealed two major environmental gradients in the study area. Axis 1 discriminated among areas with relatively dense human populations and highways, and areas with sparse populations and no highways; whereas axis 2 described a gradient between wet sites having low dry-season severity, many navigable rivers and few roads, and those with opposite values. A multiple regression analysis revealed that both factors were highly significant predictors, collectively explaining nearly 60% of the total variation in deforestation intensity (F2,117=85.46, P < 0.0001). Simple correlations of the original variables were highly concordant with the multiple regression model and suggested that highway density and rural-population size were the most important correlates of deforestation.
These trends suggest that deforestation in the Brazilian Amazon is being largely determined by three proximate factors: human population density, highways and dry-season severity, all of which increase deforestation. At least at the spatial scale of this analysis, soil fertility and waterlogging had little influence on deforestation activity, and soil depth was only marginally significant. Our findings suggest that current policy initiatives designed to increase immigration and dramatically expand highway and infrastructure networks in the Brazilian Amazon are likely to have important impacts on deforestation activity. Deforestation will be greatest in relatively seasonal, south-easterly areas of the basin, which are most accessible to major population centres and where large-scale cattle ranching and slash-and-burn farming are most easily implemented.
This comprehensive volume is the first to consider biomass burning as a global phenomenon and to assess its impact on the atmosphere, on climate, and on the biosphere itself.
The burning of biomass - forests, grasslands, and agricultural fields after the harvest - is much more widespread and extensive than previously believed; most biomass burning is thought to be initiated by humans and is on the increase. This comprehensive volume is the first to consider biomass burning as a global phenomenon and to assess its impact on the atmosphere, on climate, and on the biosphere itself. The 63 chapters by 158 scientists - including leading biomass burn researchers from third-world countries, such as Brazil, Nigeria, Zaire, India, and China, where biomass burning is so prevalent - point to biomass burning as a significant driver of global change on our planet. Global Biomass Burning provides a convenient and current reference on such topics as the remote sensing of biomass burning from space, the geographical distribution of burning; the combustion products of burning in tropical, temperate, and boreal ecosystems; burning as a global source of atmospheric gases and particulates; the impact of biomass burning gases and particulates on global climate; and the role of biomass burning on biodiversity and past global extinctions. Also included are contributions on the importance of biomass burning from the International Geosphere-Biosphere Program: A Study of Global Change and from the International Global Atmospheric Chemistry Project, as well as policy options prepared by the U.S. Environmental Protection Agency for managing biomass burning to mitigate global climate change.
Joel S. Levine is Senior Research Scientist in the Atmospheric Sciences Division, NASA Langley Research Center and is the Principal Investigator of NASA's research program on global biomass burning, Biospheric Research Program, Office of Space Sciences and Applications.
This comprehensive volume is the first to consider biomass burning as a global phenomenon and to assess its impact on the atmosphere, on climate, and on the biosphere itself.
The burning of biomass - forests, grasslands, and agricultural fields after the harvest - is much more widespread and extensive than previously believed; most biomass burning is thought to be initiated by humans and is on the increase. This comprehensive volume is the first to consider biomass burning as a global phenomenon and to assess its impact on the atmosphere, on climate, and on the biosphere itself. The 63 chapters by 158 scientists - including leading biomass burn researchers from third-world countries, such as Brazil, Nigeria, Zaire, India, and China, where biomass burning is so prevalent - point to biomass burning as a significant driver of global change on our planet. Global Biomass Burning provides a convenient and current reference on such topics as the remote sensing of biomass burning from space, the geographical distribution of burning; the combustion products of burning in tropical, temperate, and boreal ecosystems; burning as a global source of atmospheric gases and particulates; the impact of biomass burning gases and particulates on global climate; and the role of biomass burning on biodiversity and past global extinctions. Also included are contributions on the importance of biomass burning from the International Geosphere-Biosphere Program: A Study of Global Change and from the International Global Atmospheric Chemistry Project, as well as policy options prepared by the U.S. Environmental Protection Agency for managing biomass burning to mitigate global climate change.
Joel S. Levine is Senior Research Scientist in the Atmospheric Sciences Division, NASA Langley Research Center and is the Principal Investigator of NASA's research program on global biomass burning, Biospheric Research Program, Office of Space Sciences and Applications.
This comprehensive volume is the first to consider biomass burning as a global phenomenon and to assess its impact on the atmosphere, on climate, and on the biosphere itself.
The burning of biomass - forests, grasslands, and agricultural fields after the harvest - is much more widespread and extensive than previously believed; most biomass burning is thought to be initiated by humans and is on the increase. This comprehensive volume is the first to consider biomass burning as a global phenomenon and to assess its impact on the atmosphere, on climate, and on the biosphere itself. The 63 chapters by 158 scientists - including leading biomass burn researchers from third-world countries, such as Brazil, Nigeria, Zaire, India, and China, where biomass burning is so prevalent - point to biomass burning as a significant driver of global change on our planet. Global Biomass Burning provides a convenient and current reference on such topics as the remote sensing of biomass burning from space, the geographical distribution of burning; the combustion products of burning in tropical, temperate, and boreal ecosystems; burning as a global source of atmospheric gases and particulates; the impact of biomass burning gases and particulates on global climate; and the role of biomass burning on biodiversity and past global extinctions. Also included are contributions on the importance of biomass burning from the International Geosphere-Biosphere Program: A Study of Global Change and from the International Global Atmospheric Chemistry Project, as well as policy options prepared by the U.S. Environmental Protection Agency for managing biomass burning to mitigate global climate change.
Joel S. Levine is Senior Research Scientist in the Atmospheric Sciences Division, NASA Langley Research Center and is the Principal Investigator of NASA's research program on global biomass burning, Biospheric Research Program, Office of Space Sciences and Applications.
The incidence and importance of fire in the Amazon have increased substantially during the past decade, but the effects of
this disturbance force are still poorly understood. The forest fire dynamics in two regions of the eastern Amazon were studied.
Accidental fires have affected nearly 50 percent of the remaining forests and have caused more deforestation than has intentional
clearing in recent years. Forest fires create positive feedbacks in future fire susceptibility, fuel loading, and fire intensity.
Unless current land use and fire use practices are changed, fire has the potential to transform large areas of tropical forest
into scrub or savanna.
The growing prevalence of fragmentation and fire in tropical forests makes it imperative to quant fy changes in these disturbances and to understand the ways in which they interact across the landscape. I used a multitemporal series of Landsat images to study the incidence and coincidence of fire and fragmentation in two areas of Para state in the eastern Brazilian Amazon,, Tailandia and Paragominase. In both areas, deforestation and forest fires were quantified for time series of 6-10years. The Tailandia study area typifies a landscape with The herringbone pattern of government-settled colonists, and the Paragominas area is dominated by large cattle ranches. In both areas, over 90% of the forests affected by fire were associated with form est edges. Although most burned forest occurred within 500 m of forest edges, some fires occurred in deep forest, several kilometers from any edge. The obvious synergism between forest fragmentation and fire poses serious risks to tropical ecosystems and has important implications for land management.
Global active fire maps have been produced over a 21-month period from April 1992 to December 1993. A contextual active fire detection algorithm has been applied to the NOAA AVHRR (National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer) 1.1 km images provided by the IGBP-DIS (International Geosphere-Biosphere Programme Data and Information System) 1 km AVHRR Global Land Project data set. The Global Fire Product (GFP) is composed of daily fire position tables, 10-day synthesis raster format maps containing fire density and cloud/no-data information; it is now available as the first global scale description of the spatial and temporal distribution of active vegetation fire. In answer to science community requirements the GFP supplies information which can be used to estimate fire impacts on atmospheric chemistry, climate, land use and land cover changes.
Although the Visible and Infrared Scanner (VIRS) instrument on board the Tropical Rainfall Measuring Mission (TRMM) satellite is designed primarily to study precipitation, it offers a new opportunity for the remote sensing of fire activity in regions within 40 of the equator. VIRS is a five-channel imaging spectroradiometer with bands ranging from 0.6 to 12 mu m. Its similarity to the Advanced Very High Resolution Radiometer (AVHRR), which has operated since 1978 on board the National Oceanic and Atmospheric Administration (NOAA) satellite series, is no coincidence, as a primary objective of VIRS is to provide an important link between TRMM precipitation measurements and those derived from other current and historical satellite sensors. The similarity of the VIRS infrared bands, in particular, to those of AVHRR provides a foundation for fire detection, which has been clearly demonstrated for AVHRR. However, VIRS offers some additional capabilities which should enable it to make an important contribution to the remote sensing of fire.
A database for the spatial and temporal distribution of the amount of biomass burned in tropical America, Africa, and Asia during the late 1970s is presented with a resolution of 5° latitude × 5° longitude. The sources of burning in each grid cell have been quantified. Savanna fires, shifting cultivation, deforestation, fuel wood use, and burning of agricultural residues contribute about 50, 24, 10, 11, and 5%, respectively, of total biomass burned in the tropics. Savanna fires dominate in tropical Africa, and forest fires dominate in tropical Asia. A similar amount of biomass is burned from forest and savanna fires in tropical America. The distribution of biomass burned monthly during the dry season has been derived for each grid cell using the seasonal cycles of surface ozone concentrations. Land use changes during the last decade could have a profound impact on the amount of biomass burned and the amount of trace gases and aerosol particles emitted.
Due to the El Niño phenomenon, the 1997-1998 dry season in Roraima (Brazil, Amazonia) was particularly pronounced. Consequently, vegetation fires spread widely and were monitored by many satellites in real time. Satellite images are currently being used to monitor vegetation fires either globally for climate studies or more regionally for impact assessment. After reviewing different satellite data used for impact assessment, this paper focuses on the contribution of SPOT-4's imagery provided by high resolution HRVIR and coarse resolution VEGETATION sensors. These sensors are described with emphasis on those characteristics of potential benefit for forest mapping and fire detection. Early images of Roraima from SPOT-4 are analysed and interpreted to delineate the areas already damaged by fire. VEGETATION images provide a first estimate of damaged areas on a regional scale and an indication of the main ecosystems affected. SPOT HRVIR is used to establish a much more precise classification of various ecosystems. Each vegetation class is associated with a biomass density. From the known burned areas, an estimate of burned biomass during the 1998 dry season is computed, as well as total carbon release. On an intensive study site of 20 400 km 2, 3060 km 2 of savannahs and crops and 6980 km 2 of forest have been burned; the corresponding carbon release is estimated as 210 000 t for croplands and savannahs and 23 M t for the evergreen seasonal forest. The estimated burnt surface areas derived from VEGETATION are then cross-validated with HRVIR and thus an attempt is made to extrapolate the burned biomass with the help of VEGETATION on a regional scale.
Ground-based Sun photometer measurements, and airborne measurements of the physical and optical properties of regional hazes dominated by smoke from biomass burning in Brazil, are used for aerosol radiative vertical column and local radiative closure tests. Optical depths at midvisible wavelengths of up to 2.5 measured by two independent methods (ground-based Sun photometers and airborne measurements of the vertical profries of aerosol optical extinction to the top of the smoke layer) agreed, on average, to within -20%. Local aerosol closure tests were carded out using in situ measurements of particle size distributions as inputs to a computational model of the aerosol. Calculated aerosol masses, aerosol absorption and scattering coefficients, and the amounts of solar radiation backscattered by the aerosol were generally within 25% of the measured values. The computational model was used to calculate a broader range of radiative transfer parameters, including aerosol mass scattering and absorption efficiencies, the asymmetry parameter, and upscatter fraction, across the solar spectrum. Regional values of direct aerosol radiative forcing produced by smoke aerosol in the cerrado and primary forest areas of Brazil are derived using the radiative transfer parameters as inputs to a radiative transfer model. The resulting net direct radiative forcing can result in either a cooling or a heating depending on the underlying surface albedo. Over a typical tropical forest the change in the daily average net shortwave flux per unit optical depth (at a wavelength of 550 nm) is -20 + 7 W m -2 (where a negative value indicates cooling). Over the cerrado the forcing is -8 + 9 W m -2, while over a dark surface, such as the ocean, the forcing is -26 + 6 W m -2. Over a reflective surface, such as a desert, we calculate a positive (heating) forcing of +25 + 12 W m -2.
The launch of the eighth Geostationary Operational Environmental Satellite (GOES-8) in 1994 introduced an improved capability for diurnal fire and smoke monitoring throughout the western hemisphere. In South America the GOES-8 automated biomass burning algorithm (ABBA) and the automated smoke/aerosol detection algorithm (ASADA) are being used to monitor biomass burning. This paper outlines GOES-8 ABBA and ASADA development activities and summarizes results for the Smoke, Clouds, and Radiation in Brazil (SCAR-B) experiment and the 1995 fire season. GOES-8 ABBA results document the diurnal, spatial, and seasonal variability in fire activity throughout South America. A validation exercise compares GOES-8 ABBA results with ground truth measurements for two SCAR-B prescribed burns. GOES-8 ASADA aerosol coverage and derived albedo results provide an overview of the extent of daily and seasonal smoke coverage and relative intensities. Day-to-day variability in smoke extent closely tracks fluctuations in fire activity. Biomass burning is a distinct biogeochemical process with links to the biosphere, atmosphere, and geosphere. The effects of biomass burning activities on the global environment are not well understood. In recent years the scientific research com- munity has recognized the need to gain a better understanding of the extent of global biomass burning activities to assess the impact of these activities on surface and atmospheric processes and other biogeochemical interactions. Studies have suggested that biomass burning associated with deforestation and sa- vanna management in the tropics is responsible for a signifi- cant portion of global trace gas emissions and aerosols (Crutzen
A procedure has been developed to locate and estimate the area of heavy forest burning based on the frequency of DMSP-OLS (US Air Force Defense Meteorological Satellite Program Operational Linescan System) fire detection from time series of observations across the fire season. A calibration was developed for Roraima, Brazil, using Landsat Thematic Mapper (TM) data acquired near the end of the 1998 burn season and analysed to identify unburnt, partially burnt and heavily burnt forest areas. A fire detection frequency threshold of five nights was used to map heavily burnt forest using the 3 months of DMSP-OLS observations. The threshold of five fire detections, which could occur anytime during the 3-month time period, was selected to constrain errors of commission involving unburnt forest to 10% of the total area for unburnt forest in the calibration area. At this threshold setting the DMSP-OLS estimate of heavily burnt forest area covered 79% of the Landsat measured area. It was found that 77% of the 1998 heavily burnt forest area was outside of the state's protected areas (national parks, reserves, indigenous areas). Two of the protected areas sustained a substantial increase in heavily burnt forest in 1998 relative to 1995 (Reserva Biologica Mucaja and Parque Ind gena Yanomami). The 1998 forest burning in these two areas was concentrated in their eastern-most sections. The core of the Yanomami area did not sustain extensive burning in 1998. Protected areas in the north-eastern section of the state, where forests are mixed with cerrado, had moderate increases in heavily burnt forest in 1998. Other protected areas were largely free of the heavy forest burning, which was concentrated to the west of the state's primary cerrado zone.
The local observing time of the sensor on National Oceanic and Atmospheric Administration (NOAA) satellites is discussed and a strategy is recommended for maintaining relatively constant time of afternoon observations by the Advanced Very High Resolution Radiometer (AVHRR) over the satellite lifetime. The NOAA current orbital strategy is shown to be very conservative and a re-examination of the problem is recommended.
Major advances have been made in the last decades estimating deforestation by using satellite data. This has been mostly done by detecting differences in a time series of high resolution data. However, the interpretation of the images and the detection of change is cumbersome and expensive. Furthermore, the area covered by a high resolution image is relatively small and only available on a monthly bases.This work investigates if detected fire of the low resolution (AVHRR) sensor can be used as a quick and inexpensive way of locating areas of rapid forest cover change. It tests the hypothesis that vegetation fires, as detected by earth orbiting satellites, are a reliable indicator of “hot spots” of deforestation in tropical South America. Fine spatial resolution satellite data were used to measure the deforestation that occurred in the mid 1990s in 41 sites spread across the tropical forests of South America. These data were then compared to the number of fires occurring in these sites, as detected by the NOAA-AVHRR satellite between April 1992 and December 1993. At the individual site level, 25 of the test sites showed a significant statistical relationship between the fires and the deforestation occurring in the following years. A further 6 sites showed neither fire activity nor significant deforestation. When aggregated to the regional level, only the set of sites lying in relatively dry areas with the same land use practices (located in Brazil) showed a significant correlation between fire and deforestation. This correlation enabled us to produce a map of high deforestation risk occurring in 1992 in the Brazilian Amazon, which showed close correspondence to the actual deforestation fronts of the year 1992.
This paper provides a comparison of selected algorithms that have been proposed for global active fire monitoring using data from the NOAA Advanced Very High Resolution Radiometer (AVHRR). A simple theoretical model was used to generate scenes of AVHRR infrared channel 3 and channel 4 data containing fires of various sizes and temperatures in a wide range of terrestrial biomes and climates. Three active fire detection algorithms were applied to the simulated AVHRR images and their performance was characterized in terms of probability of fire detection and false alarm as functions of fire temperature and area, solar and viewing geometry, visibility, season and biome. Additional comparisons were made using AVHRR imagery. Results indicate that while each algorithm has a comparable probability of detecting large (1000m2) fires in most biomes, substantial differences exist in their ability to detect small fires, their tolerance of smoke and neighbouring fires, the number of false alarms, and their overall suitability for global application. An improved automatic algorithm is finally presented. It offers enhanced active fire detection with comparable or reduced false alarm rates in most biomes.
Smoke particles from biomass burning can modify cloud characteristics by
acting as condensation nuclei; cloud albedo is also decreased, and cloud
absorption increased. Attention is presently given to particles'
radiative characteristics, in view of the preeminently important smoke
plume parameters of average optical depth at solar wavelengths and
average single-scattering albedo. Additional parameters discussed, in
order of decreasing importance, are the asymmetry factor and the
vertical profile of the extinction coefficient.
Previously published values of pre-launch Advanced Very High Resolution Radiometer (AVHRR) 3.7 m channel saturation brightness temperatures (Robinson 1991) show inter-satellite differences as large as 10 K between AVHRRs on board National Oceanic and Atmospheric Administration (NOAA) satellites from TIROS (Television Infrared Observation Satellite)-N to NOAA-11. We redid the computations using pre-launch AVHRR calibration data up to NOAA-14. Our results show that 3.7 m channel pre-launch saturation temperatures for the TIROS-N, NOAA-6, -8, -9, -10, -11, -12 and-14 satellites are within ~0.5 K of each other while NOAA-7 differs by ~1 K from the others. We believe that the AVHRR 3.7 m channel pre-launch saturation temperatures listed in Robinson (1991) are actually the ypre-launch saturation temperatures for the AVHRR 10.8 m channel. To check our hypothesis, we computed TIROS-N to NOAA-11 10.8 m channel pre-launch saturation temperatures; the values are within 0.5 K of the values listed in Robinson (1991).
Recent studies suggest that deforestation rates in the Brazilian Amazon could increase sharply in the future as a result of over US$ 40 billion in planned investments in highway paving and major new infrastructure projects in the region. These studies have been challenged by several Brazilian ministries, which assert that recent improvements in environmental laws, enforcement and public attitudes have fundamentally reduced the threat posed to forests by such projects. The notion that hazards to Amazonian forests have declined over the last decade was assessed using available data on deforestation rates from 1978 to 2000. Although the alarmingly high rate of forest loss during 1978–1989 (1.98 million ha yr−1) declined somewhat in 1990–1994 (1.38 million ha yr−1), it rebounded to a high level in the period 1995–2000 (1.90 million ha yr−1). Moreover, correlation and regression analyses reveal that both absolute and per caput rates of forest loss accelerated significantly over the last decade. These trends fail to support the assertion that deforestation pressure in Amazonian forests has been brought under control. Poor enforcement of existing environmental laws, rapidly expanding logging and mining industries, increasing population pressure and other challenges are greatly hindering efforts to limit the environmental impacts of development activities in Brazilian Amazonia.
Field measurement programs in Brazil during the dry seasons in August and September 1979 and 1980 have demonstrated the large importance of the continental tropics in global air chemistry. Many important trace gases are produced in large amounts over the continents. During the dry season, much biomass burning takes place, especially in the cerrado regions, leading to a substantial emission of air pollutants, such as CO, NO
x
, N2O, CH4 and other hydrocarbons. Ozone concentrations are enhanced due to photochemical reactions. The large biogenic organic emissions from tropical forests play an important role in the photochemistry of the atmosphere and explain why CO is present in such high concentrations in the boundary layer of the tropical forest. Carbon monoxide production may represent more than 3% of the net primary productivity of the tropical forests. Ozone concentrations in the boundary layer of the tropical forests indicate strong removal processes. Due to atmospheric supply of NO
x
by lightning, there is probably a large production of O3 in the free troposphere over the Amazon tropical forests. This is transported to the marine-free troposphere and to the forest boundary layer.
Remote sensing measurements provide a vauable means of determining the extent of burning areas and of estimating the overall distribution of pollutant sources (identified from experimental studies) in time and space. This distribution has to be taken into account in the boundary conditions of chemistry atmospheric models.
Recent methods developed for the remote sensing of active fires in tropical or temperated forest zones, have been found to be completely inadequate for fire detection on West African savannas. In order to accurately estimate the active fire distribution in the function of different sorts of West African savannas (Sahelian, Sudanian and Guinean) and forests, a multispectral methodology has been developed based on NOAA/11-AVHRR satellite data, with the purpose of eliminating as much as possible the problems related to large surface heterogeneity, confusion and bias, produced by clouds, smoke, haze, background emissivities, etc.
Unlike other methods, the results show that the multispectral method, in spite of its selectivity, provides realistic results, and does not under- or over-estimate the number of fires that can be sensed by the satellite. Consequently, this methodology is more appropriate than the simplest ones for a systematic sensing of this phenomenon.
Fire products are now available from the Moderate Resolution Imaging Spectroradiometer (MODIS) including the only current global daily active fire product. This paper describes the algorithm, the products and the associated validation activities. High-resolution ASTER data, which are acquired simultaneously with MODIS, provide a unique opportunity for MODIS validation. Results are presented from a preliminary active fire validation study in Africa. The prototype MODIS burned area product is described, and an example is given for southern Africa of how this product can be used in modeling pyrogenic emissions. The MODIS Fire Rapid Response System and a web-based mapping system for enhanced distribution are described and the next steps for the MODIS fire products are outlined.
The Moderate Resolution Imaging Spectroradiometer (MODIS) was launched in December 1999 on the polar orbiting Terra spacecraft and since February 2000 has been acquiring daily global data in 36 spectral bands—29 with 1 km, five with 500 m, and two with 250 m nadir pixel dimensions. The Terra satellite has on-board exterior orientation (position and attitude) measurement systems designed to enable geolocation of MODIS data to approximately 150 m (1σ) at nadir. A global network of ground control points is being used to determine biases and trends in the sensor orientation. Biases have been removed by updating models of the spacecraft and instrument orientation in the MODIS geolocation software several times since launch and have improved the MODIS geolocation to approximately 50 m (1σ) at nadir. This paper overviews the geolocation approach, summarizes the first year of geolocation analysis, and overviews future work. The approach allows an operational characterization of the MODIS geolocation errors and enables individual MODIS observations to be geolocated to the sub-pixel accuracies required for terrestrial global change applications.
Experience with the first 2 years of high quality data from the Moderate Resolution Imaging Spectroradiometer (MODIS) through quality control and validation has suggested several improvements to the original MODIS active fire detection algorithm described by Kaufman, Justice et al. [Journal of Geophysical Research 103 (1998) 32215]. In this paper, we present an improved replacement detection algorithm that offers increased sensitivity to smaller, cooler fires as well as a significantly lower false alarm rate. Performance of both the original and improved algorithm is established using a theoretical simulation and high-resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes. In general, the new algorithm can detect fires roughly half the minimum size that could be detected with the original algorithm while having an overall false alarm rate 10–100 times smaller.
Accidental surface fires are emerging as one of the most pervasive threats to tropical forests. Although unimpressive in appearance, these fires can have surprisingly potent impacts on rainforest plant and animal communities, as demonstrated by recent studies led by Jos Barlow and Carlos Peres in central Amazonia. Even worse, surface fires greatly increase the likelihood of far larger conflagrations that can lead to complete forest destruction.
The National Aeronautic and Space Administration (NASA) plans to launch the moderate resolution imaging spectroradiometer (MODIS) on the polarorbiting Earth Observation System (EOS) providing morning and evening global observations in 1999 and afternoon and night observations in 2000. These four MODIS daily fire observations will advance global fire monitoring with special 1 km resolution fire channels at 4 and 11 μm, with high saturation of about 450 and 400 K, respectively. MODIS data will also be used to monitor burn scars, vegetation type and condition, smoke aerosols, water vapor, and clouds for overall monitoring of the fire process and its effects on ecosystems, the atmosphere, and the climate. The MODIS fire science team is preparing algorithms that use the thermal signature to separate the fire signal from the background signal. A database of active fire products will be generated and archived at a 1 km resolution and summarized on a grid of 10 km and 0.5°, daily, 8 days, and monthly. It includes the fire occurrence and location, the rate of emission of thermal energy from the fire, and a rough estimate of the smoldering/flaming ratio. This information will be used in monitoring the spatial and temporal distribution of fires in different ecosystems, detecting changes in fire distribution and identifying new fire frontiers, wildfires, and changes in the frequency of the fires or their relative strength. We plan to combine the MODIS fire measurements with a detailed diurnal cycle of the fires from geostationary satellites. Sensitivity studies and analyses of aircraft and satellite data from the Yellowstone wildfire of 1988 and prescribed fires in the Smoke, Clouds, and Radiation (SCAR) aircraft field experiments are used to evaluate and validate the fire algorithms and to establish the relationship between the fire thermal properties, the rate of biomass consumption, and the emissions of aerosol and trace gases from fires.
Fires are major disturbances for ecosystems in Amazonia. They affect vegetation succession, alter nutrients and carbon cycling, and modify the composition of the atmosphere. Fires in this region are strongly related to land-use, land-cover and climate conditions. Because these factors are all expected to change in the future, it is reasonable to expect that fire activity will also change. Models are needed to quantitatively estimate the magnitude of these potential changes. Here we present a new fire model developed by relating satellite information on fires to corresponding statistics on climate, land-use and land-cover. The model is first shown to reproduce the main contemporary large-scale features of fire patterns in Amazonia. To estimate potential changes in fire activity in the future, we then applied the model to two alternative scenarios of development of the region. We find that in both scenarios, substantial changes in the frequency and spatial patterns of fires are expected unless steps are taken to mitigate fire activity. Pages: 656-669
The way in which seismicity calculations which are based on the concept of fault segmentation incorporate the physics of faulting through static dislocation theory can improve earthquake recurrence statistics and hone the probabilities of hazard is shown. For the Middle America Trench, the spread parameters of the best-fitting lognormal or Weibull distributions (about 0.75) are much larger than the 0.21 intrinsic spread proposed in the Nishenko Buland (1987) hypothesis. Stress interaction between fault segments disrupts time or slip predictability and causes earthquake recurrence to be far more aperiodic than has been suggested.
Results are presented on measurements of the trace gas and particulate matter emissions due to biomass burning during deforestation and grassland fires in South America, conducted as part of the Biomass Burning Airborne and Spaceborne Experiment in the Amazonas in September 1989. Field observations by an instrumented aircraft were used to estimate concentrations of O3, CO2, CO, CH4, and particulate matter. Fires were observed from satellite imagery, and the smoke optical thickness, particle size, and profiles of the extinction coefficient were measured from the aircraft and from the ground. Four smoke plumes were sampled, three vertical profiles were measured, and extensive ground measurements of smoke optical characteristics were carried out for different smoke types. The simultaneous measurements of the trace gases, smoke particles, and the distribution of fires were used to correlate biomass burning with the elevated levels of ozone.
The method is based on remote sensing of particulates. The visible (0.63μm) and near-infrared (0.84μm) bands are used to determine the mass of particulates in the emitted smoke and to estimate the relative contribution of flaming and smoldering fires to the resulting smoke. The detected mass of emitted particulates is converted into a mass of emitted trace gases. Analysis of the 1987 burning season shows that in Brazil (in a limited area between 6.5°-15.5°S and 55°-67°W) during the 3 months of the dry season (July 1 to September 30) there are up to 8000 fires a day (observed from space) each contributing 4500t of CO2, 750t of CO, and 26t of CH4 to the atmosphere. During the dry season of 1987, it is estimated that 240 000 fires were burning in this area resulting in the emission of 1×1013g of particulates, 7×1012g of CH4, 2×1014g of CO, and 1×1015g of CO2. -from Authors