Bev Wilson

Associate Professor
Unit: School of Architecture
Department: Department of Urban and Environmental Planning
Office location and address
Peyton House #106
110 Bayly Dr
Charlottesville, Virginia 22903
PLAN 5500: Special Topics in Planning
Credits: 1–4
Varies annually to meet the needs of graduate students.
PLAC 5616: Civic Technology Principles and Practice
Credits: 3
This course familiarizes students with current technical, ethical, and regulatory aspects of Smart Cities development. It introduces the civic technology framework and ethos as a bridge between emerging technologies, local governance, and community priorities. Students will design and deploy a web application in collaboration with partners outside the university that advances the public interest. Tools may include R, shiny, MySQL, Git, AWS.
PLAC 5863: Climate Adaptation Planning
Credits: 3
Adaptation refers to actions taken at the individual, local, regional, and national levels to reduce the risks posed by a changing climate. This course contrasts the theory and academic research of climate adaptation planning with the state of practice in communities around Virginia. Anticipated impacts such as sea level rise, heat waves, and coastal storms will be explored as well as implications for natural ecosystems & urban infrastructure.
PLAC 6090: Planning Practicum
Credits: 4
This course serves as the fourth semester integrative class for the MUEP. Students work on a group project for a community client. Course entails understanding and drafting MOUs, creating concrete work plans, engaging with the public, gathering data and investigating strategies and alternatives. Final product should be a meaningful, implementable planning document for community use.
PLAN 6120: Digital Technology for Planning and Design II - GIS
Credits: 4
Required second semester technology class introducing students to the fundamental applications of geographic information systems central to planning analysis and practice.
PLAN 6122: Urban Analytics
Credits: 3
Urban analytics draws upon statistics, visualization, and computation to better understand and ultimately to shape cities. This course emphasizes geospatial data, familiarizes students with statistical computing using R, and introduces principles and techniques of data science. Students learn to communicate the results of visualization and analysis for use in decision-making and policy development and to critique those processes. No prerequisite.