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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When soil surveys are not available for land use planning activities, digital soil mapping techniques can be of assistance. Soil surveyors can process spatial information faster, to assist in the execution of traditional soil survey or predict the occurrence of soil classes across landscapes. Decision tree techniques were evaluated as tools for predicting the ocurrence of soil classes in basaltic steeplands in South Brazil. Several combinations of types of decicion tree algorithms and number of elements on terminal nodes of trees were compared using soil maps with both original and simplified legends. In general, decision tree analysis was useful for predicting occurrence of soil mapping units. Decision trees with fewer elements on terminal nodes yield higher accuracies, and legend simplification (aggregation) reduced the precision of predictions. Algorithm J48 had better performance than BF Tree, RepTree, Random Tree, and Simple Chart.

The Brazilian Cerrado is a global biodiversity hotspot with notoriously high rates of native vegetation suppression and wildfires over the past three decades. As a result, climate change can already be detected at both local and regional scales. In this study, we used three different approaches based on independent datasets to investigate possible changes in the daytime and nighttime temperature and air humidity between the peak of the dry season and the beginning of the rainy season in the Brazilian Cerrado. Additionally, we evaluated the tendency of dew point depression, considering it as a proxy to assess impacts on biodiversity. Monthly increases of 2.2−4.0℃ in the maximum temperatures and 2.4−2.8℃ in the minimum temperatures between 1961 and 2019 were recorded, supported by all analyzed datasets which included direct observations, remote sensing, and modeling data. The warming raised the vapor pressure deficit, and although we recorded an upward trend in absolute humidity, relative humidity has reduced by ~15%. If these tendencies are maintained, gradual air warming will make nightly cooling insufficient to reach the dew point in the early hours of the night. Therefore, it will progressively reduce both the amount and duration of nocturnal dewfall, which is the main source of water for numerous plants and animal species of the Brazilian Cerrado during the dry season. Through several examples, we hypothesize that these climate changes can have a high impact on biodiversity and potentially cause ecosystems to collapse. We emphasize that the effects of temperature and humidity on Cerrado ecosystems cannot be neglected and should be further explored from a land use perspective.