Developments in Location Intelligence Changed Our Cities For The Better

August 17, 2022

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This article brought to you by CoreLogic.

Imagine living in a place that features the right mix of homes, parks, public transit, libraries, restaurants, and shops – and roads with the capacity to handle traffic, even on stormy days or during rush hour. We’ve all seen the opposite: metropolitan areas overrun by traffic jams, dense urban areas with a dearth of moderately priced housing and suburbs with plenty of homes but a severe shortage of stores and restaurants. The solution: carefully considered urban planning based on data-driven analysis.

Urban planning, typically handled by local governments, involves a variety of decisions that influence the viability of a community and the satisfaction of residents and business owners. Decisions that planners make, including where to build public amenities such as schools and libraries, how to manage traffic flow, and what zoning should be implemented to manage housing and business needs, can all be informed with in-depth demographic data, hazard risk analysis and trend data that can be both forward-facing and historical.

Location intelligence and mapping have played a pivotal role in urban planning for decades, if not centuries, and that role is accelerating and bringing deeper insights. Urban planners can now use historical and near real-time data about foot and auto traffic, changing demographics, property valuation, as well as existing and planned infrastructure, to better understand the complex interrelated spatial relationships that will enable them to make smarter decisions for the long term and create more vibrant and sustainable communities.

Historical lessons

Whether a planning professional is working in an existing city that requires evaluating potential redevelopment of neighborhoods and business districts or assessing possibilities for a new development on previously unimproved land in a rural or suburban location, lessons can be learned from other communities or from past actions within the same community to determine what works and what doesn’t. Leveraging historical data and trends is a key item for the urban planner to consider as they plan the future of their community.

Planners can gain insight into these historic trends by utilizing data from “lookalike” communities. For example, planners in Boerne, Texas, a small town about 30 minutes northwest of San Antonio, can review the experience of Kyle, a similarly growing community south of Austin which has nearly doubled in size over the past decade. A quick review of population change in these two communities available from the US Census Bureau indicates that Boerne has a near identical growth rate to Kyle since 2010 but is about 15-20 years behind their current population. For planners in Boerne, evaluating what has and hasn’t worked in communities like Kyle is relevant and allows more insightful decision-making for their own plans. Leveraging this type of historical data and comparisons across similar jurisdictions is now available to planners in a manner that was more difficult to obtain in the past.

While it may seem easier to plan a community from the ground up, such as when a massive parcel of farmland is converted to housing, data analysis is needed to inform those decisions, too. More and more frequently, developers are working directly with urban planners to estimate who will live in the community based on employment information, demographics, and employment trends. Roads and schools are being planned based not just on population changes and tax revenue estimates, but also by analyzing location-based information, historic growth rates, and both historic and real-time traffic information based on analysis of who the new homeowners and businesses are going to be.


Meeting needs through planning

Economic, social, and environmental forces influence housing and urban planning decisions, and government officials need the best possible tools and data to understand the complicated nature of these sometimes-competing forces to arrive at the best solutions for their communities. Insights enhanced with machine learning can help to determine solutions to pressing needs, such as the housing shortage.

Faster development of these much-needed homes can be facilitated through mapping tools and other platforms that evaluate where to build new affordable housing in close proximity to employment, or to rehabilitate existing housing while maintaining affordability. Heat maps that show structures, foot and automobile traffic, and empty parcels can be aligned with evolving demographic information and property valuation to inform planners, as well as developers and investors. Understanding the permitting process, existing zoning in specific areas and the availability of investment incentives, such as opportunity zones for developers or buyers, can be instantly incorporated into analysis with software.

Understanding the risks associated with a location, including exposure to natural disasters, climate change and hazardous waste from existing or former industrial use, is essential to the planning process. It is also worth mentioning that understanding impacts from outside your community that could ultimately impact your community are important to consider. Data and content that is accurate, consistent, and current is an important component for planners to consider as they address where to locate future housing, businesses, and infrastructure. 


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