Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

By C. Souza, J. Shimbo, M. Rosa, L. Parente, A. Alencar, B. Rudorff, Heinrich Hasenack, M. Matsumoto, L. Ferreira, P. W. M. S. Filho and 23 more. Remote Sensing, 2020

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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.

Subfields: Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/3c71f47e84021421ecee20af907e4d9cbf02f35e

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Citations in the corpus

Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal (2021, background): “(a) Location of Pantanal within Brazil (left) and the nine hydrological subregions with land cover and land use information from the MapBiomas Collection 5 [61, 62] (right).”
Dynamic World, Near real-time global 10 m land use land cover mapping (2022, methodology): “…for Dynamic World, shown in Table 1, was determined after a review of global LULC maps, including the USGS Anderson classification system 18 , ESA Land Use and Coverage Area frame Survey (LUCAS) land cover modalities 19 , MapBiomas classification 20 , and GlobeLand30 land cover types 13 .”