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Urban development, forestry, agriculture, mining, and other land uses can substantially alter the Earth's surface. Land use and the resultant change in land cover have important effects on ecological systems and processes

An animated gif of land cover change in the Washington, D.C. area under a high-growth scenario
An animation of land cover change in the Washington, D.C. area under a high-growth scenario, as projected by researchers at the USGS Earth Resources Observation and Science (EROS) Center. The model was built based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A2's scenario. The A2 scenario emphasizes economic growth and fragmented, heterogeneous socioeconomic conditions. The A2 scenario has extremely high population growth, with global population reaching 15 billion by 2100. 

USGS scientists have a long tradition of providing high-quality, consistent, and relevant land-cover data for the United States, using our archive of current and historical remote sensing data. The National Land Cover Database (NLCD) provides consistent, spatially explicit, periodically updated maps of land cover for the United States, with mapped dates for 1992, 2001, 2006, and 2011 (in progress). The USGS Land Cover Trends project has mapped and analyzed historical land-cover change from 1973 to 2000 using the Landsat satellite image archive. The Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) provides multiple landscape attributes to support land managers and modelers. Together, these data provide a suite of data and information on current and recent historical land-cover change for the United States.

Scientists at EROS are using their experience in mapping land cover and their knowledge of land-cover change processes to temporally extend these databases beyond the dates of available remote sensing data. Using the EROS FOREcasting SCEnarios of Land-Cover (FORE-SCE) model, EROS scientists are modeling land-cover change both into the future, using scenario-based modeling approaches, and for "backcasting" land cover for historical periods. In combination with USGS remote sensing based land-cover data, EROS' modeling efforts result in consistent, annual land-cover maps from 1938 through 2100, with multiple scenarios of potential land cover for future periods.

Modeling Examples