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The Brazilian tropical savanna (Cerrado), encompassing more than 204 million hectares in the central part of the country, is the second richest biome in Brazil in terms of biodiversity and presents high land use pressure. The objective of this study was to map the land cover of the Cerrado biome based on the segmentation and visual interpretation of 170 Landsat Enhanced Thematic Mapper Plus satellite scenes acquired in 2002. The following land cover classes were discriminated: grasslands, shrublands, forestlands, croplands, pasturelands, reforestations, urban areas, and mining areas. The results showed that the remnant natural vegetation is still covering about 61% of the biome, however, on a highly asymmetrical basis. While natural physiognomies comprise 90% of the northern part of the biome, only 15% are left in its southern portions. Shrublands were the dominant natural land cover class, while pasturelands were the dominant land use class in the Cerrado biome. The final Cerrado's land cover map confirmed the intensive land use pressure in this unique biome. This paper also showed that Landsat-like sensors can provide feasible land cover maps of Cerrado, although ancillary data are required to help image interpretation.

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.

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Resumo -O objetivo deste trabalho foi mapear o uso da terra do Bioma Cerrado na escala de 1:250.000. As seguintes classes de uso da terra foram consideradas: culturas agrícolas, pastagens cultivadas, reflorestamentos, áreas urbanas e áreas de mineração. A metodologia envolveu a segmentação de imagens do satélite Landsat, a classificação visual dos segmentos e a análise da exatidão global do mapa final. Aproximadamente 39,5% do Cerrado apresentaram algum tipo de uso de terra. Pastagens cultivadas e culturas agrícolas foram as classes predominantes, com 26,5 e 10,5%, respectivamente.Termos para indexação: Landsat, PROBIO, segmentação de imagens, sensoriamento remoto. Semidetailed land use mapping in the CerradoAbstract -The objective of this work was to map the land use in Cerrado at the 1:250,000 scale. The following classes of land use were considered: croplands, planted pasturelands, reforestations, urban settlements and mining areas. The methodological approach involved Landsat image segmentation, visual classification of the segments and analysis of the global accuracy of the final map. Approximately 39.5% of Cerrado presented some type of land use activity. Planted pasturelands and croplands were the dominant classes, with 26.5 and 10.5%, respectively.

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.

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