MODELLING APPROACH FOR PREDICTING LANDSCAPE CHANGES IN EXPANDING EUCALYPTUS PLANTATIONS IN BRAZIL

Abstract This paper combines remote sensing, environmental modeling, and landscape ecology to investigate the impacts of the expansion of eucalyptus reforestation. Using these techniques, a methodology was developed to analyze and predict future land cover and landscape structure trends. The study area was comprised of the river basin municipalities in Rio Piracicaba and the metropolitan region of Vale do Aço (RMVA), a region that is home to large steel, paper, and cellulose industries in Minas Gerais. This major hub of economic development in the state has altered the landscape through deforesting native vegetation and planting eucalyptus trees. Land cover data were taken from satellite image classifications (TM/Landsat) from 1985, 2010 and 2013 in order to study the land cover changes. A number of variables that stimulate or restrict these alterations and the eucalyptus expansion observed between 1985 and 2010 were used to simulate the eucalyptus expansion, through Multi-Layer Perception Neural Networking. The results showed that the areas of Eucalyptus reforestation increased by about 12% between 1985 and 2010, whereas forest areas contracted by approximately 9%, and pasture by 3%. The simulated eucalyptus expansion indicated that by 2035 the structure of the landscape will have changed, with an increased level of isolation of the forest patches and a decrease in their nuclear area.