Description: This dataset is maintained and created by the Chesapeake Bay Program for use by the Federal Facilities Workgroup. The dataset is used information and resources related to the water quality improvement efforts of federal facilities within the Chesapeake Bay Watershed. Data is compiled from various authoratative data sources including the Protected Areas Database V. 1.4, Federal Agencies, and in some cases States and other jurisdictions.
Description: Lands suitable for commercial development include gently sloped, unprotected, private forests and farmlands that are either zoned for commercial and/or mixed use development or that have very generalized or unspecified zoning designations.
Description: Lands suitable for commercial development include gently sloped, unprotected, private forests and farmlands that are either zoned for commercial and/or mixed use development or that have very generalized or unspecified zoning designations.
Description: Lands suitable for residential development include gently sloped, unprotected, private forests and farmlands that are either zoned for residential and/or mixed use development or that have very generalized or unspecified zoning designations.
Description: Lands suitable for residential development include gently sloped, unprotected, private forests and farmlands that are either zoned for residential and/or mixed use development or that have very generalized or unspecified zoning designations.
Description: The Forecasted Land Use 2025 dataset represents one of 101 equally-likely Monte Carlo (i.e., random) iterations of the “Current Zoning” scenario for the year 2025. New development, from 2013-2025, is illustrated as either Commercial (fuchsia), Residential (yellow), or Mixed Use (purple). While the exact locations of simulated development vary among all 101 equally-likely iterations, the general patterns of growth are the same. Thus, the locations of simulated clusters of new development within a city or county will be similar for all iterations. These general patterns of growth are dictated by zoning, land suitability (e.g., gently sloped, unprotected, and undeveloped), and proximity to recent growth hot spots, urban areas, amenities, sewer infrastructure, and pre-development land cover conditions.
Description: The Forecasted Land Use 2025 dataset represents one of 101 equally-likely Monte Carlo (i.e., random) iterations of the “Current Zoning” scenario for the year 2025. New development, from 2013-2025, is illustrated as either Commercial (fuchsia), Residential (yellow), or Mixed Use (purple). While the exact locations of simulated development vary among all 101 equally-likely iterations, the general patterns of growth are the same. Thus, the locations of simulated clusters of new development within a city or county will be similar for all iterations. These general patterns of growth are dictated by zoning, land suitability (e.g., gently sloped, unprotected, and undeveloped), and proximity to recent growth hot spots, urban areas, amenities, sewer infrastructure, and pre-development land cover conditions.
Description: Created as a base for future projections. A combination of three high-res impervious classes (impervious roads, impervious non-roads, and tree canopy over impervious), resampled to 30-meter resolution, and burned into the 2011 NLCD (2014 edition). Technically, a hybrid land use/cover datasets because agriculture is a land use and imperviousness is land cover. The 2013 projection base represents 2013 imperviousness and 2011 classes for other land cover/use classes. Allows visualization of change between the baseline and future projections.