The yellow areas of these maps, generated from the GIS archive, show the changes in residential development from 1962 (above) and 1998 (below) in a coastal N.H. county. Developed areas increased in Seacoast counties by nearly 80,000 acres from 1962 to 1998; an additional 34,000 acres are forecasted for development by 2035.
Where Do We Grow From Here?
Urban planning tools use historic development patterns to predict future growth.
Challenge
As coastal development increases, so does concern over its impact on watersheds, estuaries, and coastal waters. Parking lots, buildings, and other impervious surfaces threaten water quality by increasing polluted runoff and reducing groundwater recharge. How can coastal managers plan future growth in a way that reduces its impact on water quality? Knowing how development has unfolded in the past is a good place to start.
Response
CICEET-sponsored investigators have created a set of planning tools for New Hampshire’s rapidly growing coastal counties. The researchers have analyzed historic and current aerial photos to generate land use data that is archived in a Geographic Information
Systems (GIS) database. This comprehensive database can be used to track changes in the region’s development patterns
from 1962 to 1998.
A companion spatial trend computer model forecasts the magnitude and location of future development to 2020 and 2035—information that community planners need to better manage watersheds, open land, and other resources. Planners can use the GIS archive as a basis to estimate the extent of current impervious surfaces, and then apply model forecasts to generate estimates of future imperviousness and its potential impact on water resources.
Impact
Researchers have made these tools available to planners and the public: each community has received maps generated from the data; researchers have made presentations at local, regional,
and national venues; and the GIS data archive is available online: www.granit.sr.unh.edu.
Researchers also have created a CD ROM that describes model results and project methodology, and includes core data sets used to support modeling and maps formatted for printing. While the archive and predictive model are tailored to support Seacoast communities, they could be useful to other regions in need of integrated, spatial planning tools.
Learn More
Ms. Fay Rubin
University of New Hampshire
T: 603.862.4240
E: fay.rubin@unh.edu
Dr. William Salas
Applied Geosystems, LLC.
T: 603.868.2369
E: wsalas@agsemail.com
Related Projects
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Engineering Bioretention for Treatment of Storm Water Runoff [Progress Report]