GIS in Urban Planning

Urban planning is greatly enhanced by the use of modern technology such as geographic information systems (GIS), which are uniquely suited to capture the many spatial layers and dimensions of the contemporary city and provide analytical tools to model its growth and change. Cities, counties, regional planning agencies, and other planning units frequently undertake what-if analysis and problem solving with GIS. GIS are a helpful tool for urban planners because it not only goes beyond just forecasting the magnitude of a problem but also visually displays the spatial distribution of the phenomena being examined.

GIS has been especially popular for smart growth initiatives, sometimes called new urbanism or neo-traditional planning, which encourage compact development with mixed uses, redevelopment of infill areas, pedestrian-friendly walkways, public transportation, open space connecting neighborhoods, and architectural designs that encourage social interaction. The principles of smart growth are articulated with terms such as compactness, connectedness, and interaction, which are all spatial terms, and therefore, GIS becomes the natural tool for implementing such plans.

Consider the contrasting example of what-if planning applied to population growth impacts in an urban fringe watershed west of Chicago (Figure 1, next page). The urban fringe of Chicago has been affected by many negative consequences of sprawl due to rapid population growth. The Chicago Metropolitan Agency for Planning (CMAP) has developed GIS data sets and tools to cope with the impacts of this growth on metropolitan Chicago's environment, land use, and economic development. Inputs from federal, state, and local planning agencies included cadastral land parcels, land use, extent of prime agricultural land, and open space. In the watershed example, assumptions were entered into the GIS about how growth would occur in the future. For instance, assumptions were made about the nature and policies of land use and whether new development should be kept compact or allowed to be scattered throughout the watershed.

In the first scenario, the GIS assumed no land use controls, and the growth continued to occur in a scattered fashion. In the smart growth scenario, the growth was made compact and took place adjacent to existing development, particularly filling in many bypassed sites from an earlier development period and protecting prime farmland and other green areas. Similarly, the CMAP has undertaken a more comprehensive study of available infill areas throughout the entire Chicago metropolitan area and has held community meetings encouraging a participatory planning process aided by GIS.

Urban planning researchers often apply more complex GIS modeling and simulations referred to as cellular automata. Cellular automata models in a GIS are designed as a grid of cells where the state of each cell depends on the previous state of the cells within a neighborhood according to a set of transition rules. For instance, Jose Barredo and Luca Demicheli, working with the European Commission's MOLAND (Monitoring Land Cover/Use Dynamics) project, developed a large-scale cellular automata urban growth model for the megacity of Lagos, Nigeria. The city was divided into grid cells of 100 m (meters) by 100 m, with particularly strong land use factors that could be calibrated through the use of time series data. As a developing-world megacity, Lagos experienced very rapid growth in its population and land extent from 1962 to 2000. The model was run, and the city's urban spatial distribution was projected for 20 years, from 2000 to 2020. It projected that Lagos in 2020 would become a megacity with 27 million persons, encompassing an area of 969 square kilometers, which is more compact than Mexico City today. The model projected rapid growth of the urban area, although with considerable consolidation and infill. The model demonstrated the need for better infrastructure to provide the key needs of water, energy, and communications.

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