Visualizing gentrification trends in Boston, targeting neighborhoods for green-building retrofits, tracing urbanization through time, assessing the risk of sinkholes in a community, quantifying access to fresh food for low-income communities, measuring the loss of glacial snow in the Cascades – these are just a handful of projects carried out by Tufts students over the past year using geospatial technology tools. This year’s annual Tufts GIS Poster Expo had over 60 student participants and highlighted the diversity of work being done by students across a variety of disciplines.

This past year Tufts students could choose from one of several GIS (geographic information systems) classes, and for the first time a course in Remote Sensing was offered. GIS is a set of digital tools that allow a researcher to visualize, interpret, and quantify spatial patterns, trends, and relationships. Remote Sensing focuses on the interpretation and use of satellite- or aircraft-derived imagery to understand earth processes, conditions, and trends. Together these are powerful tools for exploring social and environmental issues. The following examples highlight work this past year by students in Urban and Environmental Policy and Geology. The full set of 60+ posters can be viewed online at

Estimating Erosion Rates after the 2008 Santa Barbara Wildfire – Mack Carlson


Geology student Mack Carlson looked at the impact of last year’s large wildfire in Santa Barbara, nicknamed the “Tea Fire,” which destroyed over 200 homes. Carlson used soil map data, digital elevation models, satellite-derived land cover data, and a water erosion prediction program to estimate the risk of soil erosion and thus potential landslides, road washouts and structure damage, both before and after the fire. He found that potential soil loss rates were five times higher after the fire than before.


Assessing the Feasibility of New Transmission Lines for Wind Power in Vermont – Silas Bauer


There is a growing market and consumer interest in wind power, but to accommodate increased wind farm production and demand, new transmission lines have to be built. Locating corridors for these new lines will be a very controversial issue – few people want a transmission line near where they work or live. UEP student Silas Bauer demonstrated how suitability criteria can be used in GIS to help visualize potential locations in Vermont, which has committed to having alternative energy make up 20% of energy sales by 2017. Bauer first used wind data to locate prime locations for large windfarms, then created “cost” surfaces based on land use, topography, and distance to substations to find the “least cost” path of a transmission line from wind farm to substation. Bauer’s analysis is purely a demonstration of technique, but it shows the importance of geospatial analysis and visualization for providing citizens with science-backed information on transmission line alternatives.


Urban Sprawl in Travis County (Austin), Texas – Kaiba White


We now have nearly 40 years of satellite imagery available for studying our changing environment at high resolution, much of it now freely available for download via the internet. UEP student Kaiba White used Landsat images of the area around Austin, Texas, from 1984 and 1999 to look at how the urban/suburban area expanded in that time. Her analysis visualizes the sprawling low density character of much of the development during that period and also discusses the potential for error in this kind of analysis and how to assess the degree of error.


Mapping Neighborhood Change: Three Decades of Gentrification in Boston – Matt Hammer


The Boston metropolitan area suffers from a low supply of affordable housing, and many neighborhoods that were once affordable have gentrified over the last few decades. UEP student Matt Hammer decided to capture the history of gentrification in Boston between 1970 and 2000 by mapping four indicators of neighborhood change for each decade in that period as compared with the previous decade – increase in median household income, increase in the number of people with Bachelor degrees, increase in the amount of remodeling, and increase in the construction of new buildings. The resulting map series shows the individual factors and the combined analysis to highlight high, medium, and low zones of gentrification through time.

Barbara Parmenter, GIS Teaching and Research Consulting, Department of Urban and Environmental Policy and Planning, UIT Academic Technology

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