Turning streams of data--demographic information, population projections, number etc.--into meaningful and easily visualized information can be challenging and time consuming for planners. Likewise, figuring out land use and population projections as well as economic and social conditions can be maddeningly difficult. Urban planners and designers can greatly benefit from three types of data visualization that have emerged over the past few years.
The City Form Lab at MIT has released a new data visualization ESRI ArcGIS toolbox. It allows users to analyze urban street networks with greater precision by utilizing five graph analysis measures of street networks: Reach, Gravity, Betweenness, Closeness, and Straightness. Three features make this data visualization tool unique from others. First, either or geometry or topology can be accounted for, meaning that units can be set to distance (meters, etc.) or to topological features, such as turns. This results in a wider variety of inputs and outputs. Second, instead of solely using two common forms of analysis (nodes and edges), the Urban Network Analysis tool adds buildings to the mix, thus making it possible for two different accessibility outcomes for two adjacent buildings to occur. Similarly, the third important addition to this tool is its ability to weight buildings according to their different characteristics. Because of its precision and detail, this tool is suited to small-scale as well as large-scale network analyses.The versatility and expanded ways to visualize the urban form are what distinguish Urban Street Networks from other data visualization methods.
Urban Interactive Studio, in conjunction with PlaceWays and RKG Associates, developed an online tool under the auspices of the New Hampshire Office of Energy and Planning. This tool, Cost of Sprawl, was specifically designed to incorporate existing land use information, infrastructure, and financial attributes with sprawl-related conditions in order to assess the future impact of development in any of New Hampshire’s 239 municipalities. Combating urban sprawl is becoming more imperative as its environmental, social, and economic consequences become alarmingly apparent. However, projecting how new development will specifically impact the amount of infrastructure needed, new residents, and other variables is extremely difficult. The Cost of Sprawl saves planners valuable time and provides an accurate baseline from which they can plan growth in New Hampshire municipalities.
UrbanSim is another tool used for modeling potential future impacts of sprawl and is based on analyzing interactions between economy, the environment, transportation, and land use. In doing so, it allows users (generally metropolitan planning organizations, cities, counties, private firms, and students) to see how policy decisions may affect land use and sprawl conditions. UrbanSim is designed to account for many interrelated intricacies that constitute urban sprawl, therefore maximizing reality. Unlike Cost of Sprawl, which is purely used to estimate future land use impacts in New Hampshire, where current data is already incorporated into the model, UrbanSim requires that the user input population forecasts, economic forecasts, transportation system plans, and other information to generate the most accurate model. In then outputs future population distributions, households by type, businesses by type, land use, development densities, and several other outputs that can inform plans.
While no program can obviously predict future conditions, each of these three tools can greatly aid planners in making sense of vast amounts of data. Urban Street Networks, Cost of Sprawl, and UrbanSim can save planners time, money, and increase accuracy of data. Also, because these tools save planners time, they can spend more time analyzing different models and finding the best solutions for the greatest number of citizens.