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Abstract Managing fuels is a key strategy for mitigating the negative impacts of wildfires on people and the environment. The use of satellite‐based Earth observation data has become an important tool for managers to optimize fuel treatment planning at regional scales. Fortunately, several new sensors have been launched in the last few years, providing novel opportunities to enhance fuel characterization. Herein, we summarize the potential improvements in fuel characterization at large scale (i.e., hundreds to thousands of km²) with high spatial and spectral resolution arising from the use of new spaceborne instruments with near‐global, freely‐available data. We identified sensors at spatial resolutions suitable for fuel treatment planning, featuring: lidar data for characterizing vegetation structure; hyperspectral sensors for retrieving chemical compounds and species composition; and dense time series derived from multispectral and synthetic aperture radar sensors for mapping phenology and moisture dynamics. We also highlight future hyperspectral and radar missions that will deliver valuable and complementary information for a new era of fuel load characterization from space. The data volume that is being generated may still challenge the usability by a diverse group of stakeholders. Seamless cyberinfrastructure and community engagement are paramount to guarantee the use of these cutting‐edge datasets for fuel monitoring and wildland fire management across the world. 

With deforestation and associated fires ongoing at high rates, and amidst urgent need to preserve Amazonia, improving the understanding of biomass burning emissions drivers is essential. The use of orbital remote sensing data enables the estimate of both biomass burning emissions and deforestation. In this study, we have estimated emissions of particulate matter with diameter less than 2.5 µm (PM2.5) associated with biomass burning, a primary human health risk, using the Brazilian Biomass Burning emission model with Fire Radiative Power (3BEM_FRP), and estimated deforestation based on the MapBiomas dataset. Using these estimates, we have assessed for the first time how deforestation drove biomass burning emissions in Amazonia over the last two decades at three scales of analysis: Amazonia-wide, country/state and pixel. Amazonia accounted for 48% of PM2.5 emitted from biomass burning in South America and current deforestation rates have reached values on par with those of the early 21st Century. Emissions and deforestation were concentrated in the Eastern and Central-Southern portions of Amazonia. Amazonia-wide deforestation and emissions were linked through time (R = 0.65). Countries/states with the widest spread agriculture were less likely to be correlated at this scale, likely because of the importance of biomass burning in agricultural practices. Concentrated in regions of ongoing deforestation, in 18% of Amazonia grid cells PM2.5 emissions associated with biomass burning and deforestation were significantly positively correlated. Deforestation is an important driver of emissions in Amazonia but does not explain biomass burning alone. Therefore, future work must link climate and other non-deforestation drivers to completely understand biomass burning emissions in Amazonia. The advance of anthropogenic activities over forested areas, which ultimately leads to more fires and deforestation, is expected to continue, worsening a crisis of dangerous emissions. 

While the climate and human-induced forest degradation is increasing in the Amazon, fire impacts on forest dynamics remain understudied in the wetter regions of the basin, which are susceptible to large wildfires only during extreme droughts. To address this gap, we installed burned and unburned plots immediately after a wildfire in the northern Purus-Madeira (Central Amazon) during the 2015 El-Niño. We measured all individuals with diameter of 10 cm or more at breast height and conducted recensuses to track the demographic drivers of biomass change over 3 years. We also assessed how stem-level growth and mortality were influenced by fire intensity (proxied by char height) and tree morphological traits (size and wood density). Overall, the burned forest lost 27.3% of stem density and 12.8% of biomass, concentrated in small and medium trees. Mortality drove these losses in the first 2 years and recruitment decreased in the third year. The fire increased growth in lower wood density and larger sized trees, while char height had transitory strong effects increasing tree mortality. Our findings suggest that fire impacts are weaker in the wetter Amazon. Here, trees of greater sizes and higher wood densities may confer a margin of fire resistance; however, this may not extend to higher intensity fires arising from climate change. 

Neste relato de experiências trazemos uma breve revisão da literatura, em sua maioria de artigos e relatórios técnicos produzidos pelos projetos de Pesquisa MAP-FIRE e Acre-Queimadas sobre a ocorrência e impactos de incêndios florestais na Amazônia, com detalhamento para a região MAP (Madre de Dios - Peru, Acre – Brasil e Pando-Bolívia). Os incêndios em áreas de agropecuária ou de floresta trazem impactos socioeconômicos e ambientais, e vem aumentando sua ocorrência nos últimos anos, sendo intensificadas em anos em que há seca extrema ou flexibilização da fiscalização. Enquadra-se nesse último caso o ano de 2019, em que se observou no Estado do Acre um aumento de 80% da área queimada em relação ao ano anterior, impactando a qualidade do ar por mais de 30 dias em alguns municípios. Para entendermos como prevenir ou mitigar as consequências a ocorrência de tais eventos, é necessário realizar um diagnóstico da governança, envolvendo as comunidades locais. Estas, uma vez incluídas na elaboração de planos estratégicos para monitorar, mitigar e combater as queimadas e incêndios florestais terão sua vulnerabilidade reduzida e sua capacidade de autoproteção aumentada. Para isso, o diálogo entre ciência e sociedade é imprescindível. Convidamos o leitor interessado em participar do projeto a entrar em contato com os autores. 

Abstract The restoration and reforestation of 12 million hectares of forests by 2030 are amongst the leading mitigation strategies for reducing carbon emissions within the Brazilian Nationally Determined Contribution targets assumed under the Paris Agreement. Understanding the dynamics of forest cover, which steeply decreased between 1985 and 2018 throughout Brazil, is essential for estimating the global carbon balance and quantifying the provision of ecosystem services. To know the long-term increment, extent, and age of secondary forests is crucial; however, these variables are yet poorly quantified. Here we developed a 30-m spatial resolution dataset of the annual increment, extent, and age of secondary forests for Brazil over the 1986–2018 period. Land-use and land-cover maps from MapBiomas Project (Collection 4.1) were used as input data for our algorithm, implemented in the Google Earth Engine platform. This dataset provides critical spatially explicit information for supporting carbon emissions reduction, biodiversity, and restoration policies, enabling environmental science applications, territorial planning, and subsidizing environmental law enforcement.