This study evaluates the long-term accuracy of six daily aerosol optical depth (AOD) datasets derived from the Moderate Resolution Imaging Spectroradiometers (MODIS) Dark Target (DT) at 3 and 10 km resolution, Deep Blue (DB), combined DT and DB datasets (DTB) and MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms and the Multi-angle Imaging SpectroRadiometer (MISR) Version 23, by comparing them with ground-based AOD observations in 18 Aerosol Robotic Network (AERONET) sites over the Amazon basin between 2000 to 2022. The AOD retrieval accuracy was also assessed under varying seasons, aerosol loading, particle size, elevation and land cover type. Overall results showed that Terra and Aqua-MODIS DB and MISR algorithms perform better, with about 88% of AOD retrievals within the expected error range. However, MISR presented a systematic high negative bias. MODIS DT 3km overestimated AOD values and indicated unsatisfactory retrieval accuracy in almost all scenarios. MODIS and MISR retrievals showed improved performance under low aerosol loading, whereas Aqua-MODIS MAIAC under intermediate conditions (AOD>0.2). MISR indicated a large dependence on a coarse mode-dominated environment with considerable negative bias. Terra-MODIS MAIAC retrievals exhibited a smaller dependence for aerosol particle size distribution, while Terra-MODIS DB performed better for fine mode and Aqua-MODIS DB for coarse dominance. MAIAC also performed well under polluted scenarios in the dry season in contrast to the majority of satellite-based AOD retrievals, which showed good agreement under clean background conditions in the wet season. Almost all satellite-based retrievals showed higher uncertainty under extremely high altitudes (>3000m) followed by non-satisfactory correlation and significant biases. Additionally, almost all satellite-based AOD retrievals indicated poor performance as vegetation coverage increases. On the contrary, MISR showed higher accuracy under forest type. In general, MODIS and MISR retrieval accuracy demonstrated distinct levels of dependencies that require further improvement in the Amazon Basin.

The present study carries out the systematic performance evaluation of aerosol optical depth (AOD) products retrieved using Visible Infrared Imaging Radiometer Suite (VIIRS) Deep Blue (DB) and Dark Target (DT) onboard Suomi National Polar-orbiting Partnership (S-NPP) satellite over the Amazon Basin. Characteristics and uncertainty were evaluated under distinct air pollution scenarios such as a clean background in the wet season, polluted conditions in the dry season with biomass burning emissions and peak burning season with higher fire activity. VIIRS retrievals were also analyzed under aerosol loading, particle size and surface vegetation coverage against the Aerosol Robotic Network (AERONET) measurements at 9 sites in 2012–2022. VIIRS DB showed good accuracy, with 78% of AOD matchups falling within the expected error, 84% in the wet season, and 71% in the dry and burning seasons. In contrast, VIIRS DT indicated poor accuracy (64%) and trends overestimate the AOD in all air pollution scenarios. Both algorithms were sensitive to AERONET sites with high elevation and dark vegetated coverage characteristics. VIIRS DB and DT systematically overestimated AERONET AOD as increased aerosol loading. DB trends underestimate aerosol under background conditions and overestimate with coarse and fine particle predominance. Additionally, both algorithms indicated poor accuracy under forest type with a large positive bias. VIIRS DB demonstrated the highest accuracy in the presence of aerosol loading in sites characterized by mixed land cover type. This was observed in both coarse and fine mode scenarios for grassland. VIIRS DT demonstrated satisfactory accuracy under background conditions and dominance of coarse particles within grassland land cover type. For mixed land cover, satisfactory accuracy was found under intermediate aerosol loading conditions. DB algorithm showed greater uncertainty associated with the coarse particle aerosol for the full period and all polluted scenarios. Overall, VIIRS DT accuracy was more sensitive to varying air pollution scenarios.

The Amazon is the largest rainforest on the planet and was an important carbon sink. The carbon sink is declining, mainly due to an increase in tree mortality as a result of deforestation, degradation, and local, regional and global climate change. In addition, deforestation and forest degradation reduce the ability of the Amazon rainforest to act as a carbon sink. CO2 Vertical Profiles (VP) were performed from 2010 to 2021 (805), using small aircraft at 4 locations: SAN (2.86° S 54.95° W), ALF (8.80° S 56.75° W), RBA (9.38° S 67.62° W) and from 2010 to 2012 on TAB (5.96° S 70.06° W) and since 2013 at TEF (3.39° S 65.55° W). The question if Amazonia is a carbon source or sink is an important role in the global carbon budget. Amazonia vertical profile annual mean derived from CO2 annual mean vertical profiles (VP subtracted from the background concentration: ∆VP) from the 4 studied sites can help to clarify this important question. The sampling frequency was approximately 2 times per month in each location, from 4.4 km height (a.s.l.) until near surface 300 m (a.s.l.), and usually carried out between 12:00 and 13:00 local time. The CO2 samples were analyzed at INPE's LaGEE (Greenhouse Gas Laboratory), in São Jose dos Campos. This result is a direct indication of the regional source in the global carbon budget, indeed there are well-known discrepancies from many studies using different methodologies (bottom-up, top-down techniques, and a wide variety of global, regional, and inversion models). In this study, we will present Carbon flux from the time series for the 4 sites and Amazon Carbon balance using the column budget technique, and analyze the correlations with various parameters related to climate, vegetation, deforestation, and biomass burning.

The Amazon forest carbon sink is declining, mainly as a result of land-use and climate change 1 – 4 . Here we investigate how changes in law enforcement of environmental protection policies may have affected the Amazonian carbon balance between 2010 and 2018 compared with 2019 and 2020, based on atmospheric CO 2 vertical profiles 5 , 6 , deforestation 7 and fire data 8 , as well as infraction notices related to illegal deforestation 9 . We estimate that Amazonia carbon emissions increased from a mean of 0.24 ± 0.08 PgC year −1 in 2010–2018 to 0.44 ± 0.10 PgC year −1 in 2019 and 0.52 ± 0.10 PgC year −1 in 2020 (± uncertainty). The observed increases in deforestation were 82% and 77% (94% accuracy) and burned area were 14% and 42% in 2019 and 2020 compared with the 2010–2018 mean, respectively. We find that the numbers of notifications of infractions against flora decreased by 30% and 54% and fines paid by 74% and 89% in 2019 and 2020, respectively. Carbon losses during 2019–2020 were comparable with those of the record warm El Niño (2015–2016) without an extreme drought event. Statistical tests show that the observed differences between the 2010–2018 mean and 2019–2020 are unlikely to have arisen by chance. The changes in the carbon budget of Amazonia during 2019–2020 were mainly because of western Amazonia becoming a carbon source. Our results indicate that a decline in law enforcement led to increases in deforestation, biomass burning and forest degradation, which increased carbon emissions and enhanced drying and warming of the Amazon forests.

Lightning ignition is the major cause of natural wildfires in several regions worldwide. Determining if wildfires in remote uncontrolled areas result from natural lightning as opposed to anthropic action is a relevant and yetunsolved challenge for large regions of the planet, with scientific and management implications ranging from environmental conservation to mitigation of climate-related emissions of gases and aerosols. Brazil is the country with one of the highest occurrences of lightning (50 to 100 million/year) and which is also subject to numerous and vast wildfires (up to -600 x 103 km2/year) affecting all its biomes. To quantify natural fires we combined cloud-to-ground (CG) lightning and CG dry-lightning (CGDL) detected by a ground network, with fire pixels mapped by satellite remote sensing (AQUA, S-NPP and NOAA-20) over -1,8 x 106 km2 in Central Brazil, between 2015 to 2019. Lightning ignition candidates were selected based on the distance between fires and lightning in time and space. The selected cases were investigated according to annual and monthly distributions in space and time, to local weather at the time of occurrence and, electrical characteristics related to ignition. Space-time distributions of CG lightning, CGDL and of active fires were also analyzed. Results showed that the CGDLs pattern is not different from that of the overall CG lightning, with both presenting similar kernel density, polarity and peak current. The lightning candidates indicated predominance of negative polarity and peak current frequency below 20 kA. In this range, average values for weather conditions for CG lightning matched to fires (CGDL matched to fires) had: precipitation 6 mm (< 1 mm), relative humidity 57 % (48 %), and temperature -30 degrees C and wind speed of - 2 m.s- 1 for both. The results showed that satellite detection of active fires is a useful tool to identify lightning-induced wildfires.

Abstract The Amazon Forest is a major locus for carbon and water cycling in the climate system whose function has been degraded in recent decades by land use and climate change. Most studies of Amazonia’s carbon balance have been limited by sparse sampling. We measured 742 atmospheric vertical profiles of CO2 and CO over four regions of Amazonia from 2010 through 2020. We estimate that Amazon carbon emissions increased from 0.24±0.19 PgC y-1 in 2010-18 to 0.44±0.22 in 2019 and 0.52±0.22 PgC y-1 in 2020. During these years, increases were also observed in deforestation (79% and 74%) and forest burned area (14% and 42%). Field notifications for illegal deforestation and related crimes dropped by 42%, while fines paid for judgments held fell by 89%. Carbon losses during 2019 and 2020 were comparable to losses in the record warm El Nino event of 2015-16, but this time with usual to moderate Oceanic Ninõ Index. 2020 showed 12% decrease in precipitation indicating also a climate impact in carbon emissions. The changes during 2019 and 2020 were mainly due to the western Amazonia becoming also a carbon source. We hypothesize that the consequences of the collapse in enforcement led to increase in deforestation, biomass burning and degradation producing net carbon losses and enhancing drying and warming of forest regions.

This paper documents an increase in the number of observed explosive cyclones (EC) at King George Island, South Shetland Islands, Antarctica, over the 1989‒2020 period. In ECs at 60o latitudes the surface atmospheric pressure drops ≥24 hPA in 24 hours. The annual EC frequency time series shows a significant positive trend of ~2.7 cyclones/decade, with a break in 2003 and average numbers of 7.3 and 11.8 events before and after that break, respectively. The increase follows closely earlier documented global sea surface temperature (SST) anomaly trends for the 1981‒2018 period, partially attributed to global warming and to the Pacific Decadal Oscillation (PDO). Connections between EC frequency and SST might occur through variations in SST in the southeastern Pacific and southwestern Atlantic, with anomalous cold conditions favoring an increase in ECs. We also found close relations between the number of ECs with simultaneous occurrences of PDO and Atlantic multidecadal oscillation in opposite phases, so that after 2003 they were in the cold and warm phases, respectively, and vice-versa before 2003. Both low-frequency modes seem to modulate the number of ECs. As per the authors knowledge these results have not been discussed before and may help climate modeling studies and weather forecasts.

Fire incidence has been linked to multiple factors such as climate conditions, population density, agriculture, and lightning. Recently, fire frequency and severity have induced health problems and contributed to increase atmospheric greenhouse gases. Based on atmospheric susceptibility to fire, this study evaluates the use of a Potential Fire Index (PFIv2) to identify regions prone to fire development, as demonstrated by the satellite detected‐fire in the 2001–2016 interval. It is demonstrated that PFIv2 delivers an efficiency by up to 80% in matching the observed fires from Terra/MODIS satellite. The PFIv2 is also able to reproduce more accurately areas with fire activity with respect to its previous version, the PFI. This better performance is linked to the implementation of parameterization of water pressure deficit and atmospheric stability in the lower troposphere, and a new term to represent the effect of surface temperatures, particularly in mid‐latitudes and extra‐Tropics. To evaluate the performance of the PFIv2 in more details, its comparison to MODIS burned areas demonstrated correlations values higher than 0.6 over the most susceptible regions such as Africa and South America, slightly lower correlation is found where fire does not primary follows the climate annual cycle, and is dominated by high frequency events. These findings indicate that the PFIv2 can be an important tool for decision makers in predicting the potential for vegetation fires development and fire danger.

Landscape fire is a widespread, somewhat unpredictable phenomena that plays an important part in Earth's biogeochemical cycling. In many biomes worldwide fire also provides multiple ecological benefits, but in certain circumstances can also pose a risk to life and infrastructure, lead to net increases in atmospheric greenhouse gas concentrations, and to degradation in air quality and consequently human health. Accurate, timely and frequently updated information on landscape fire activity is essential to improve our understanding of the drivers and impacts of this form of biomass burning, as well as to aid fire management. This information can only be provided using satellite Earth Observation (EO) approaches, and remote sensing of active fire is one of the key techniques used. This form of EO is based on detecting the signature of the (mostly infrared) electromagnetic radiation emitted as biomass burns. Since the early 1980's, active fire (AF) remote sensing conducted using low Earth orbit (LEO) satellites has been deployed in certain regions of the world to map the location and timing of landscape fire occurrence, and from the early 2000's global-scale information updated multiple times per day has been easily available to all. Geostationary (GEO) satellites provide even higher frequency AF information, more than 100 times per day in some cases, and both LEO- and GEO-derived AF products now often include estimates of a fires characteristics, such as its fire radiative power (FRP) output, in addition to the fires detection. AF data provide information relevant to fire activity ongoing when the EO data were collected, and this can be delivered with very low latency times to support applications such as air quality forecasting. Here we summarize the history of achievements in the field of active fire remote sensing, review the physical basis of the approaches used, the nature of the AF detection and characterization techniques deployed, and highlight some of the key current capabilities and applications. Finally, we list some important developments we believe deserve focus in future years.

Fires are intrinsic disturbances in ecosystems functioning and structure in fire-prone biomes. In recent decades there has been an increase in the number of fire events in Brazilian biomes, especially due to misuse of fire in the land use and deforestation. The spatial and temporal pattern fire risk is a important way to understanding the seasonality and intensity of fire in different climate and fuel conditions. However, consistent long-term assessment at biome level is only possible with the support of remote sensing and modeling information. Thus, the objective of this work was to evaluate the fire risk patterns for the Brazilian biomes in the last years (2015-2018), using the new version of INPE’s fire risk (FR, v2). Regarding the temporal and spatial FR patterns by this new version from FR model, we evaluated that elevation and latitude correction factors, as well as the meteorological and land cover datasets with finer spatial scales can be contributed to adjust better the fire season vulnerability, notably in the less prone-biomes, such as Mata Atlantica, Pampa and Pantanal. However, there is still a need for adjustment to match the spatial active fire distribution, considering a biomass (fuel) map and the vegetation water status indicators. These improvements help to inform with more accuracy the most fire prone areas to define the strategies and decisions for fire combat and management.

This study aims to present the Geospatial Transmission Management System as a way to monitor the burning and forest fires that occur under power transmission lines. Burns contributes very severely to forced shutdowns, becoming during 2017 the main cause of this type of event. The agents of the electric sector are required by Aneel Normative Resolution 669/2015 at least once a year to inspect the safety bands, wich are bands where the size has been defined in the respective operating licenses by the competent environmental agency. Despite that, shutdown events with consequent blackouts are recurrent during the dry season in Central Brazil, from July to November of each year. This planned maintenance is precisely to ensure system security and prevent fire shutdowns. That is why, in 2017, an Agreement was signed between Aneel and the Inpe. The system uses geospatial technologies in satellite imagery to monitor safety bands. The Normalized Difference Vegetation Index (NDVI) index detects maintenance by the difference in values between images on T1 and T2. The lower the value, the greater the certainty that the company performed the maintenance. Experts in the field have developed research using this index satisfactorily, which allows the development of expertise in the field of fire monitoring research. Preliminary published results demonstrate that the developed methodology is adequate to detect changes in the landscape and to prevent future forest fires and burns and to prevent disconnections

No Brasil as queimadas são caracterizadas por extensas linhas de fogo de rápida propagação que causam a mortalidade de espécies da flora e da fauna. Para mitigar estes danos, políticas públicas foram implementadas. Para correto funcionamento delas, entretanto, é necessário compreender a variabilidade do fogo e os elementos que o afetam para aperfeiçoar as estratégias de prevenção e combate. Neste sentido, este trabalho teve como escopo analisar a dinâmica das queimadas no Brasil, nos anos de 2003 a 2018, através da climatologia de precipitação e dos acumulados e das anomalias de focos de queima de vegetação. Os resultados demonstraram que há três padrões espaciais de queimadas no Brasil que se relacionam com dois sistemas de precipitação: a Zona de Convergência Intertropical e a Zona de Convergência do Atlântico Sul. Na maioria dos estados foi detectada uma tendência de redução de uso do fogo. Para outros, uma estabilização das taxas de detecção. Apesar destes resultados, as detecções ainda têm maior ocorrência na estiagem, quando tendem a contribuir significativamente para a degradação ambiental e para o dispêndio do orçamento público em operações de combate. Cabe aos entes federativos investirem em atividades de fiscalização, de monitoramento, de educação ambiental e de manejo preventivo para reduzi-las.Space-Time Dynamics of the Burns in Brazil in the Period 2003 to 2018 A B S T R A C TIn Brazil, vegetation fires are characterized by extensive and rapidly spreading fire lines that cause the mortality of flora and fauna species. Public policies were implemented to mitigate these damages, and for their correct enforcement it is necessary to understand the variability of the fire regime and the elements that affect it to improve prevention and combat strategies. In this sense, this work aimed to analyze the dynamics of burning in Brazil from 2003 to 2018 through the accumulated number of active fires and their anomalies as detected in satellite images with the precipitation climatology. The results showed that there are three spatial burning patterns in Brazil that relate with two precipitation systems: the Intertropical Convergence Zone and the South Atlantic Convergence Zone. A tendency to reduce the use of the fire was detected in most states; some indicated a stabilization of detection rates. The detections are still more frequent in drought periods, when the fires tend to contribute significantly to environmental degradation and to public budget expenditure in combat operations. It is up to the federal and state governments to invest in activities of enforcement, monitoring, environmental education and preventive management to reduce the use of fire in the country.Keywords: Variability of fire, climatology precipitation, public policies, active fire.

Emissions from vegetation fires are relevant in the atmosphere-biosphere interaction. Nevertheless, fire is still intensely used as a tool in land management, modifying natural fire patterns in fire-prone ecosystems. The Brazilian Cerrado has shown increased anthropogenic fire ignitions, especially due to deforestation that removed ~50% of its original cover and unusual droughts. Fire risk (FR) models using meteorological and vegetation parameters have been used to estimate fire patterns at biome level. The aim of this study was to evaluate the performance of INPE’s FR model using different climate and land cover (LC) datasets (versions 0 and 1) to estimate FR patterns in the Cerrado. Meteorological datasets from CoSch and MCD12Q1-IGBP V006 land cover data represent v0 while v1 is composed by IMERG and Mapbiomas v3.0 datasets. The analyses were performed in the wet (W: November-March) and dry (D: May-September) seasons from 2015 to 2018 at 1km of spatial resolution. The versions were compared using the seasonal predominance of FR (PFR) and evaluated in five categories: “minimum”, FR<=0.15; “low”, 0.15<FR<=0.40; “medium”, 0.40<FR<=0.70; “high”, 0.70<FR<=0.95 and “critical”, 0.95<FR<=1.0. The main fire pattern differences between v0 and v1 were observed in D, when the PFR remains “high” during all season according to v0, while v1classifies “critical” PFR from July to September. In W, differences were not observed, except for November, classified as “low” PFR by v0 and “minimum” PFR in v1. These differences can be related to the higher LC spatial resolution and definition of vegetation types in v1 such as woody savannas; v1 is based on Landsat medium resolution spectral images (~30m) while v0 uses MODIS low resolution (~500m). Concerning precipitation, the information has a higher spatial consistency using 10 km of spatial resolution in v1 while v0 uses 25 km of spatial resolution. With new Mapbiomas editions and revisions released every year, INPE’s FR will be updated accordingly, allowing a realistic temporal modeling of the vegetation; including terrain data in this condition will allow a new FR product at 30m resolution for protected areas – our next goal.

Coarse spatial resolution of remote sensing imagery still hampers a comprehensive representation of long-term fire patterns at the regional level, in particular in areas characterized by small and sparse fire scars. The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor launched in 2011 upgrades the spatial resolution (375 m) and gives continuity to the Earth long-term monitoring initiated by Advanced Very High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Therefore, aiming to assess VIIRS 375 m imagery capabilities to improve the accuracy and reliability of fire scars mapping over the Brazilian Cerrado, we developed a burned area detection algorithm (VIIRS-SVM) based on machine learning techniques. For this purpose, the (V, W) burnt index adjusted to VIIRS near-infrared and middle-infrared channels and the One-Class Support Vector Machine algorithm were used for burned area identification. The VIIRS-SVM algorithm was applied over the Brazilian Cerrado and evaluated against reference scars from 15 Landsat-8 scenes during the fire season of 2015, covering a large area with substantial variability in terms of fire scars characteristics. We also performed a comparison with the MCD64A1 collection-6 product over the validation sites. Relying on VIIRS 375 m imagery, the VIIRS-SVM algorithm allows an enhancement of 25% in discrimination of small and medium fire scars (25 to 1000 ha), when compared to the MODIS-derived product. Results have demonstrated that the enhancement of medium and small fire scars mapping over the Cerrado is possible using VIIRS sensor capabilities.

La combustion natural de biomasa, y las emanaciones antropicas de contaminantes a la atmosfera son fenomenos muy poco estudiado en Cuba y los principales resultados de estudios y productos en este campo para America Latina, con el empleo de informacion satelital han sido realizados por CPTEC-INPE. La metodologia empleada se corresponde con la desarrollada por el INPE, basada en un modelo 3-D de transporte CATT-BRAMS acoplado a un modelo de emision. En este metodo, la ecuacion de conservacion de masas es solucionada para el monoxido de carbono (CO) y el material particular PM2.5 y las emisiones de gases y particulas asociadas con la biomasa activa ardiente. CATT-BRAMS, el modelo de transporte que calcula las fuentes de emision de combustion de biomasa, por actividades urbanas, industriales y autos, para gases y particulas de aerosol. El modelo esta basado en el Sistema de Modelado Regional Atmosferico (RAMS), usado para simular el monoxido de carbono y el material particular (PM2.5) y el transporte atmosferico. Se describe la tecnica de estimacion de emisiones por quema de biomasa sobre la base de una combinacion de productos de sensoramiento remoto para incendios.

Forest fires annually destroy extensive areas of vegetation, causing great environmental and economic damages. Many products derived from satellite observations have been used to monitor fire events. In Brazil, the Queimadas Program from INPE develops applications for the daily operational monitoring of hot spots detected by satellites. These detections are obtained with measurements from different sensors, which require specific algorithms and calibration parameters. The use of thermal sensor coupled to drone allows obtaining parameters with adequate spatial resolution. However, there are still no defined routines for obtaining these measures. The aim of this work is to propose a procedures protocol for the use of thermal sensor coupled to drone in experiments for validate the detection of hot spots by satellites. Based on our field experiences it is first necessary to have support from brigadiers, to instruct the teams with safety procedures to carry out the experiments. Secondly, i) to request authorization for the drone flights, in the SARPAS / DECEA system; ii) to check the weather conditions (cloud cover, wind speed and direction, etc.); iii) to determine the size of the burned area, which is inversely proportional to the spatial resolution of the satellite sensor studied; iv) to define the height of the drone's positioning, depending on the dimension of the chosen area and the sensor's field of view, and; v) to determine the sequence of the drone activation time, the start of the burning and the satellite imagery over the location. Finally, it is necessary to obtain quality thermal measures: i) to start the fire in advance for arrive to high temperatures during satellite imaging in the place of interest; ii) to consider the time to stabilize the drone and start acquiring the thermal data, before and after the peak of the satellite passage, and; iii) after the satellite has passed, to use the drone for measure the surrounding temperature (radius = ~ 200m), obtaining a temperature reference in the surrounding areas. This protocol aims to standardize the experiments, improving the detection algorithms and providing improvements in the products presented in the Queimadas Program database.

Global biomass burning impacts millions of hectares annually resulting in high social, environmental and economic costs. Satellite-based active fire detection products provide key information in support of land management and science applications and are available routinely from a variety of sources. Data validation is an important aspect guiding product development and characterization and is addressed in this study with the use of miniaturized sensors paired to unmanned airborne vehicles, or drones. Specifically, we deployed a custommade broadband spectral radiometer along with a commercial off-the-shelf infrared camera (FLIR Zenmuse XT) mounted to small consumer drones (DJI's Phantom3 and Inspire) flown over small prescribed burns implemented so as to coincide with the overpass times of different earth observing satellites (e.g., NASA Terra & Aqua, NOAA/NASA S-NPP, USGS Landsat-8, and ESA Sentinel-2). Near-simultaneous fire radiative power retrievals were obtained using the airborne and spaceborne data acquired during prescribed fires conducted in grasslands and savannas plots in the Brazilian states of Rio de Janeiro, Tocantins and Mato Grosso do Sul between July 2017 and September 2018. A set of standard operating procedures were defined with attention to satellite active fire data validation requirements (e.g., reference data calibration) and subsequently adopted for each of the fires sampled. Airborne and spaceborne observations were co-located and temporally paired to within 2sec, and path transmittances calculated in order to account for atmospheric attenuation of fire retrievals. Our results showed good agreement (differences as low as 5%) between drone and satellite-based fire retrievals while also serving to demonstrate the potential for fully reproducible satellite data validation protocols using small sensor and drone technologies.

O planejamento das operações seja de combate ao fogo ou de manejo do fogo requerem o conhecimento da meteorologia e do clima local, além do tempo associado a cada incêndio. O objetivo essencial da previsão meteorológica para o combate à s queimadas é suprir toda a cadeia de comando e ação de informações de tempo e clima que sejam relevantes aos serviços de planejamento, análise e ações práticas do combate ao fogo, pois proporcionam dados primordiais como vento (direção e velocidade), temperatura, umidade, chuvas, etc. que variam constantemente afetando o comportamento e a duração do fogo. Para que os brigadistas pudessem estar supridos dessas informações meteorológicas, foi criado o Boletim de Risco de Fogo (BRF) para Brigadas que é emitido diariamente com previsões detalhadas para cada brigada atuante no combate ao fogo, com previsões futuras (dois dias) contendo informações simples, diretas e objetivas aos coordenadores das operações com dados de nascer e por do sol, previsão de chuvas, temperatura máxima, umidade mínima, ventos em superfície, risco de fogo e condições gerais à s operações aéreas. Além dessas previsões também são informadas as previsões de mais longo prazo como Risco de Fogo de até 5 dias à frente. Desde que foi implementado em 2016, mais de 350 Boletins de Risco de Fogo para Brigadas foram emitidos no âmbito do Ciman. Para elaboração do BRF são feitas análises meteorológicas de diversas fontes como a NOAA, Cptec, Inmet, etc. porém o mais complexo são os dados observados, que são necessários para a validação dos modelos utilizados nessas análises. Em geral, as queimadas no Brasil ocorrem em áreas desprovidas de informações meteorológicas em tempo real, que servem para fazer o monitoramento, por exemplo, da variação da direção do vento, que pode colocar em risco a segurança do brigadista até alterar completamente o estado do fogo. Com o intuito de auxiliar as tomadas de decisões no teatro de combate ao fogo, os BRF têm se tornado uma ferramenta cada vez mais solicitada pois percebeu-se que sua importância à tática operacional, na economia de recursos e segurança dos envolvidos no combate aos grandes incêndios.  Â

A queima da biomassa emite gases e partículas na atmosfera, muitos dos quais prejudiciais à saúde humana ou relevantes como forçantes climáticas. O número de queimadas no Brasil apresenta média anual superior a duzentos mil ocorrências, de acordo com o monitoramento por satélites do Programa Queimadas do Instituto Nacional de Pesquisas Espaciais (INPE). Análise do IBGE para os 5.570 municípios brasileiros indicou que em 2005 as queimadas eram a principal fonte de poluição atmosférica, com 93% deles na região norte indicando esta condição. Com o aumento dos focos e a ocorrência mais frequente de estiagens intensas, resultando no dobro das detecções, as concentrações ambientais de poluentes atingem e ultrapassam os níveis críticos definidos na legislação ambiental. Estudos epidemiológicos e dados hospitalares, sobretudo em grupos mais vulneráveis de crianças e idosos, levaram o Ministério da Saúde (MS) a incluir as queimadas a partir de 2006 entre os indicadores na vigilância em saúde pública. Consequentemente, a localização dos focos de queima e as estimativas de poluentes de suas emissões passaram a ser relevantes na análise de seus efeitos na saúde humana. Nesse contexto, o INPE, o MS, a Fiocruz, a FIOTEC, e a UNEMAT desenvolveram em 2008 o Sistema de Informações Ambientais Integrado à Saúde Ambiental (SISAM), concebido para integrar o Painel de Informações em Saúde Ambiental da Coordenação Geral de Vigilância em Saúde Ambiental e o Sistema de Informações Geográficas Aplicadas ao Meio Ambiente do INPE. Assim, o SISAM se tornou uma ferramenta de análise que fornece concentrações de poluentes oriundos de estimativas de emissões de queimadas e emissões urbanas, dados de monitoramento de focos de queimadas, dados meteorológicos e limites de índices de risco à saúde e índices de qualidade do ar, definidos na legislação nacional, para todos os municípios brasileiros. Dessa maneira, o SISAM fornece subsídios para um melhor prognóstico da concentração dos poluentes e de seus efeitos na saúde humana e apoia a identificação de cenários de exposição e os seus fatores de risco de cada região do Brasil. Seu acesso é em http://www.inpe.br/queimadas/sisam

Os incêndios florestais destroem anualmente extensas áreas de vegetação, causando grandes prejuízos ambientais e econômicos. Muitos produtos derivados das observações de satélites têm sido utilizados para monitorar eventos de fogo. No Brasil, o Programa Queimadas/INPE desenvolve aplicações para o monitoramento operacional diário dos focos de queimadas detectados por satélites. Estas detecções são obtidas com medidas de diferentes sensores, os quais requerem algoritmos específicos e parâmetros de calibração. O uso de sensor termal acoplado em drone permite obter parâmetros com resolução espacial adequada. Porém, ainda não existem rotinas definidas para a obtenção dessas medidas. O objetivo deste trabalho é propor um protocolo de procedimentos para o uso de drone com sensor termal em experimentos de validação da detecção de focos de calor, obtidos por satélites. Com base na experiência de campo, para realizar os experimentos é necessário ter apoio de Brigadistas, instruir as equipes com procedimentos de segurança e: i) solicitar autorização para os voos, no sistema SARPAS/DECEA; ii) verificar as condições meteorológicas (cobertura de nuvens, velocidade e direção do vento, etc); iii) determinar o tamanho da área de queima, que é inversamente proporcional à resolução espacial do sensor do satélite de interesse; iv) definir a altura do posicionamento do drone, em função da dimensão da área escolhida e do campo de visão do sensor, e; v) determinar a sequência do horário do acionamento do drone, do início da queima e do imageamento do satélite sobre o local. Para obter as medidas termais com qualidade é necessário: i) iniciar o fogo com antecedência, para tentar alcançar temperaturas elevadas durante o imageamento pelo satélite sobre o local de interesse; ii) considerar o tempo para estabilização do drone e início da aquisição dos dados termais, antes e depois do ápice da passagem do satélite, e; iii) após a passagem do satélite, utilizar o drone para realizar as medidas da temperatura do entorno (raio = ~200m), obtendo referência da temperatura nas áreas circunvizinhas. Este protocolo visa a padronização dos experimentos, para aprimorar os algoritmos de detecção e proporcionar melhorias nos produtos apresentados no banco de dados do Programa Queimadas.