Interests: Professor Radke teaches Geographic Information (GI) Science and related courses in both the Department of Landscape Architecture and Environmental Planning, and the Department of City and Regional Planning. He has lead an effort to bring GI System technologies to the campus and promote its use in the Bay area.
Professor Radke is recognized for his contributions to pattern recognition, specifically the development of metrics and methods for characterizing spatial structure, association and relationships between objects embedded in the landscape. His metrics, embedded in graph theory, attempt to eliminate scale and density constraints common to many popular spatial metrics and produce a more sophisticated definition. The applied results of his research occur within Geographic Information Science and seek to solve real world problems common in planning and design. His spatial decomposition metrics delineate boundaries and transition zones (or ecotones) in complex heterogeneous distributions and aid in the classification of spatial data by generalizing notions of neighborly and providing tools for defining entire spectrums of neighborhoods where spatial relationships between objects (plants) are complex. Where measuring and delineating neighborliness was once difficult and often impossible, we can now easily grow, map and measure sophisticated neighborhoods.
The success of Radke's spatial decomposition project will help designers, planners and geographers better measure, track and document spatial structure and change in complex landscapes where sophisticated sensors record and log spatial distributions of phenomena beyond human comprehension. As these sensors and computers evolve, our ability to measure minute and accurate changes in the landscape will rapidly increase producing a data rich environment. Metrics, like those developed by Radke, look hopeful for characterizing the morphology of landscape.
Professor Radke applies these methods to the field of Environmental Planning where he designs and constructs hazard models in attempts to predict and assess risk. One such study mapped the risk of firestorms in the East Bay Hills, another detected potential erosion threats to the coastal zone in St. John (USVI), and another automatically generated street centerlines in the City of Berkeley.
Radke, J. and Mulan, 2000 "Spatial Decompositions, Modeling And Mapping Service Regions To Predict Access To Social Programs", in Geographic Information Sciences, Vol. 6, No.2, pp 105-112.
Radke, J. T. Cova, M.F. Sheridan, A.Troy, MuLan, and R. Johnson. 2000 "Application Challenges for GIScience: Implications for Research Education, and Policy for Risk Assessment, Emergency Preparedness and Response (RAEPR)" URISA Journal, Vol 12, No. 2.
Radke, J. and A. Flodmark. 1999. "The Use of Spatial Decompositions for Constructing Street Centerlines" in Geographic Information Sciences, Vol. 5, No.1, pp 15-23.
Radke, J. 1999. "Geographic Information Science at the University of California, Berkeley" Geographic Information Sciences, Vol. 5, No.1, pp i-ii.
Radke, J. 1998. "Boundary Generators for the 21st Century: A Proximity Based Classification Method" Department of City and Regional Planning 50th Anniversary.
Radke, J. 1997. "Detecting Potential Erosion Threats to the Coastal Zone: St. John, USVI" " International Journal of Marine Geodesy, Vol. 20, pp 235-254.
Radke, J. 1995. "Modeling Urban/Wildland Interface Fire Hazards within a Geographic Information System" in Geographic Information Sciences, Vol. 1, No.1, pp 7-20.