Academic journal article Cityscape

Forewarned: The Use of Neighborhood Early Warning Systems for Gentrification and Displacement

Academic journal article Cityscape

Forewarned: The Use of Neighborhood Early Warning Systems for Gentrification and Displacement

Article excerpt


Neighborhoods change continually because of the movement of people and capital, both private and public. Change is often visible, as newcomers walk the streets or buildings and infrastructure are built and demolished. At the same time, change may be hard to discern, as property transfers and even the arrival of new tenants are not publicized. The process may take decades to unfold and may be nonlinear; change can stall or reverse, and the neighborhood may never fully transform.

As local residents and policymakers struggle to discern the nature and extent of changes, researchers have devised "neighborhood early warning systems" to describe change processes and even predict future transformation. These toolkits, which take the form of either reports or online guides, tend to focus on economic and racial/ethnic change at the neighborhood scale via demographic and property data. The idea of early warning is that, by tracking investment, disinvestment, and population flows at the local level, policymakers can design cost-effective interventions before the pace of change accelerates and patterns become entrenched (Snow, Pettit, and Turner, 2003). In the case of neighborhood decline, early warning might mean identifying crime hotspots or abandoned properties. For neighborhoods that are revitalizing, toolkits tend to focus on areas of housing sales, racial transition, and new amenities, among other factors.

The first generation of toolkits from the 1980s and 1990s has now disappeared,1 but both the overheating of the housing market and the planning of new transit systems have led to new interest in understanding neighborhood change, specifically in the form of gentrification and displacement. New early warning systems with an online presence have emerged in Portland, Oregon; the San Francisco Bay Area in California; Chicago, Illinois; and Minneapolis-St. Paul, Minnesota. Many other regions also have conducted analyses. This new generation of toolkits has the potential to transform policies to stabilize and/or revitalize neighborhoods, especially if, this time around, they find more permanent homes. One pathway might be to expand the "smart cities" movement beyond its current focus on efficiency to proactive policymaking around inclusion (Pettit and Greene, 2016).

Little is understood, however, about precisely how stakeholders are using the systems and what impact those systems have on policy. Early warning systems have complex and multiple goals in contrast with smart cities systems, which primarily attempt to make city systems more responsive to constituents. To make the case for integrating early warning systems into city operations, it is important to understand their value. This article describes the intent and use of these toolkits, assessing their ability to make policy more effective, their potential sustainability, and, for a few, their predictive capability.

The following section discusses the evolution of urban data capabilities and then describes the first generation of early warning toolkits. The next section presents a survey of the landscape of current toolkits, including the Urban Displacement Project tool in the San Francisco Bay Area, which the authors developed. The next section, using information from a dozen interviews with developers and users and also from a survey conducted in one region, explores the different ways that toolkits have been used. The final section lays out next steps for system development, suggesting ways to increase the relevance of toolkits to the planning and development decisions that elected officials and communities face.

Perspectives on Smart Cities, Neighborhood Change, and Early Warning Toolkits

The current generation of neighborhood early warning systems dates from the emergence of Geographic Information Systems (GISs). A movement to democratize data resulted in broad experimentation with data portals that characterize neighborhood change. …

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