Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil.

High costs of tree planting are a barrier to meeting global forest restoration targets. Natural forest regeneration is more cost‐effective than tree planting, but its potential to foster restoration at scale is poorly understood. We predict, map, and quantify natural regeneration potential within 75.5 M ha of deforested lands in the Brazilian Atlantic Forest. Of 34.1 M ha (26.4%) of current forest cover, 2.7 M ha (8.0%) regenerated naturally from 1996 to 2015. We estimate that another 2.8 M ha could naturally regenerate by 2035, and a further 18.8 M ha could be restored using assisted regeneration methods, thereby reducing implementation costs by US$ 90.6 billion (77%) compared to tree planting. These restored forests could sequester 2.3 GtCO2 of carbon, reduce the mean number of expected species at risk of extinction by 63.4, and reduce fragmentation by 44% compared to current levels. Natural regeneration planning is key for achieving cost‐effective large‐scale restoration.

Widespread in the subtropics and tropics of the Southern Hemisphere, savannas are highly heterogeneous and seasonal natural vegetation types, which makes change detection (natural vs. anthropogenic) a challenging task. The Brazilian Cerrado represents the largest savanna in South America, and the most threatened biome in Brazil owing to agricultural expansion. To assess the native Cerrado vegetation (NV) areas most susceptible to natural and anthropogenic change over time, we classified 33 years (1985–2017) of Landsat imagery available in the Google Earth Engine (GEE) platform. The classification strategy used combined empirical and statistical decision trees to generate reference maps for machine learning classification and a novel annual dataset of the predominant Cerrado NV types (forest, savanna, and grassland). We obtained annual NV maps with an average overall accuracy ranging from 87% (at level 1 NV classification) to 71% over the time series, distinguishing the three main NV types. This time series was then used to generate probability maps for each NV class. The native vegetation in the Cerrado biome declined at an average rate of 0.5% per year (748,687 ha yr−1), mostly affecting forests and savannas. From 1985 to 2017, 24.7 million hectares of NV were lost, and now only 55% of the NV original distribution remains. Of the remnant NV in 2017 (112.6 million hectares), 65% has been stable over the years, while 12% changed among NV types, and 23% was converted to other land uses but is now in some level of secondary NV. Our results were fundamental in indicating areas with higher rates of change in a long time series in the Brazilian Cerrado and to highlight the challenges of mapping distinct NV types in a highly seasonal and heterogeneous savanna biome.

Understanding the dynamics of native forest loss and gain is critical for biodiversity conservation and ecosystem services, especially in regions experiencing intense forest transformations. We quantified native forest cover dynamics on an annual basis from 1990 to 2017 in Brazil’s Atlantic Forest. Despite the relative stability of native forest cover during this period (~28 Mha), the ongoing loss of older native forests, mostly on flatter terrains, have been hidden by the increasing gain of younger native forest cover, mostly on marginal lands for mechanized agriculture. Changes in native forest cover and its spatial distribution increased forest isolation in 36.4% of the landscapes. The clearance of older forests associated with the recut of 27% of younger forests has resulted in a progressive rejuvenation of the native forest cover. We highlight the need to include native forest spatiotemporal dynamics into restoration programs to better estimate their expected benefits and unexpected problems.

Highlights Pandemics can become a new indirect driver of tropical deforestation. Halting illegal deforestation should be considered an essential activity during the pandemic. Forest fires could aggravate the health risks of COVID-19. Tropical deforestation will increase the risks of emerging zoonotic diseases. Indigenous people should be especially protected during the current pandemic.