The Land Change Monitoring, Assessment, and Projection (LCMAP) initiative uses temporally dense Landsat data and time series analyses to characterize landscape change in the United States from 1985 to present. LCMAP will be used to explain how past, present, and future landscape change affects society and natural systems. Here, we describe a modeling framework for producing high-resolution (spatial and thematic) landscape projections at a national scale, using a unique parcel-based modeling framework. The methodology was tested by modeling 11 land use scenarios and 3 climate realizations for the U.S. Great Plains. Results demonstrate 1) an ability to balance competing land-use demands from quite variable, complex scenarios, 2) urban growth that matches theoretical future patterns, 3) the value of remote sensing data sources for model parameterization and for deriving landscape parcels, and 4) a pragmatic approach that facilitates the development of high thematic- and spatial-resolution projections at a national scale.
|Title||Remote sensing as the foundation for high-resolution United States landscape projections – The Land Change Monitoring, assessment, and projection (LCMAP) initiative|
|Authors||Terry L. Sohl, Jordan Dornbierer, Steve Wika, Charles Robison|
|Publication Subtype||Journal Article|
|Series Title||Environmental Modelling and Software|
|Record Source||USGS Publications Warehouse|
|USGS Organization||Earth Resources Observation and Science (EROS) Center|