Masters Thesis

Geospatial modeling of population growth scenarios for the Humboldt Bay, California region: adapting SLEUTH to a rural environment

Humboldt County is a modestly populated region on the northern coast of California. Much of the county is held in State and National parks and unavailable for development. While growth rates remained steady for several decades, the region is not immune to population growth and poorly-planned expansion. Geospatial modeling provides a means to explore various development scenarios examining the likelihood of urban sprawl encroaching upon agricultural lands and other protected areas. Communities surrounding Humboldt Bay are particularly susceptible to rapid growth, representing approximately 60 percent of the population. Understanding impacts of growth around existing population centers is necessary to assess potential benefits of regional smart growth strategies. The SLEUTH urban growth model uses cellular automata, terrain mapping, and land cover modeling to generate potential population growth scenarios. It has been successfully applied to numerous metropolitan areas; however, its application to rural environments has not been fully explored. Using SLEUTH, I generated multi-scenario population growth estimates projecting 100 years into the future. These will inform city and county planning departments in developing smart and sustainable growth strategies and provide resource managers information useful in selecting an optimal expansion plan for the region.

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