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Monday 17 October 2005: Session 2, 3:30:00 PM
Using SLEUTH Model for Forecasting Urban Growth
Presentation Abstract
Urban growth forecasting is an important issue for local urban/community growth planners. Various models have been developed to address this issue with different degrees of success. SLEUTH model developed by Keith C. Clarke at the University of California, Santa Barbara (http://www.ncgia.ucsb.edu/projects/gig/project_gig.htm) is one of such models. The acronym SLEUTH comes from model image input requirements (Slope, Land cover, Exclusion, Urbanization, Transportation, and Hillshade). SLEUTH model is based on cellular automaton simulation methodology, which uses a set of prescribed cell transition rules to determine cell state transitions. The model contains two separate but tightly coupled components: Urban Growth Model (UGM) and Land Cover Deltatron model (LCD). The UGM can run independently to only simulate urban growth, but the two model components can run seamlessly to simulate land use changes. The model should be calibrated using historical urban development conditions before it is used for forecasting urban growth. SLEUTH model has been successfully implemented in San Francisco, Chicago, Washington-Baltimore area, Sioux Falls, and other cities/communities in the United States and in the other countries. However, most of those predictions used satellite imagery-derived land use data as the model inputs. The imagery derived land use data contain various imagery interpretation errors, which may resulted in additional forecasting errors. We are using this model for predicting growth for the Centre Region of Centre County, Pennsylvania using parcel based urban data sets. We expect that the simulation results will aid urban planners for future growth planning.
Speaker Biographical Information
Rick Day Director, Associate Professor: RGIS Penn State - Geospatial Technology Program, Land Analysis Lab
Dr. Day is an Associate Professor of Soil Science and Environmental Information Systems in the Department of Crop and Soil Sciences, College of Agricultural Sciences, Penn State University. His current position is divided among cooperative extension, resident education, and research. He serves as Director of the Land Analysis Laboratory, Director of the Cooperative Extension Geospatial Technology Program, and Director of the Penn State – Chesapeake site of the National Consortium for Rural Geospatial Innovations (RuralGIS). Dr. Day has over 24 years of experience in geospatial sciences. Dr. Day’s extension activities focus on technology transfer of geospatial information system technologies to users throughout Pennsylvania and the surrounding region for use in environmental assessment, agriculture, K-12 education, local government, and land use planning and management. Dr. Day’s research interests include (1) the development of new applications of advanced geospatial technologies in natural resource, agricultural, and environmental studies, and (2) field soil science emphasizing soil physical properties and processes. Basic research interests have been in spatial data analysis, soil morphology, soil hydrologic processes, watershed hydrology, and nutrient and sediment transport modeling. Applied research is focused on the application of advanced information system technologies such as geographic information systems, remote sensing, terrain analysis, global positioning systems and computer modeling, to environmental assessment and management.
Yuanhong Zhu Research Associate: RGIS Penn State - Geospatial Technology Program, Land Analysis Lab
Yuanhong Zhu is a Research Associate in the Department of Crop and Soil Sciences, The Pennsylvania State University. He works with Dr. Rick Day for the research project “Estimating ground water recharge rates using geographic information system techniques”. He received a Ph.D. degree in Soil Science and M.S. degree in Computer Science and Engineering from the Pennsylvania State University in 2002. His research interests include GIS applications in landing use planning, soil fertility and nutrient management, modeling, water management, and solute transport and fate in soil and water.
