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An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area
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1994
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EngineeringGeomorphologyLand UseLand CoverLand DegradationEnvironmental PlanningPhysical GeographyChange AnalysisEarth ScienceSocial SciencesUs Geological SurveySierra FoothillsLand-use PlanningClimate ChangeLand Use PlanningLandscape ProcessesLand DevelopmentGeographyUrban PlanningLandscape ChangeLandscape Evolution ModelLand Cover MapClimatologyHuman-induced Land TransformationsUrban GeographyMan-land RelationshipLand Surface Modeling
Part of the US Geological Survey's Global Change Research Program involves studying the area from the Pacific Ocean to the Sierra foothills to enhance understanding of the role that human activities play in global change. The study investigates the ways that humans transform the land and the effects that changing the landscape may have on regional and global systems. To accomplish this research, scientists are compiling records of historical transformations in the region's land cover over the last 140 years, developing a simulation model to predict land cover change, and assembling a digital data set to analyze and describe land transformations. The historical data regarding urban growth focus attention on the significant change the region underwent from 1850 to 1990. The historical change is being used to calibrate a prototype cellular automata model, developed to predict changes in urban land cover 100 years into the future. These data aid in documenting and understanding human-induced land transformations from both historical and predictive perspectives. A descriptive analysis of the region is used to investigate the relationships among data characteristic of the region. These data consist of multilayer topography, climate, vegetation, and population data for a 256-km[sup 2] region of central California. Amore » variety of multivariate analysis tools are used to integrate the data in raster format from map contours, interpolated climate observations, satellite observations, and population estimates.« less