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Location Intelligence: What Does City Data Look Like?

Whatever action is taken by today's resident, most likely it leaves a digital footprint. Morning run? The fitness tracker will remember the route. Taking a taxi to the office? Uber will keep its address. Meeting a friend in a bar? Google will use your location and time spent there to estimate the busiest hours for the place.

Huge amount of data is being generated in cities every day, and municipalities are increasingly seeking to use them to make important decisions. So far, it's a complicated and time-consuming process which involves a huge number of barriers and constraints. But suppose the city authorities sorted things out with corporations and local business, and already got access to big, very big data. What’s next?

Obviously, the raw data can't be interpreted just like that, therefore, there are a number of visualization tools, which make understanding of insights and trends easier. And since the physical space is one of the key dimensions for the city, location intelligence brings very useful value.

Location intelligence (LI) is the way of using geospatial data to identify and solve various, in our case, city’s problems. To put it simply, it's a way of data visualization using maps. Despite the complexity, this method is becoming more popular due to its undeniable advantages. In particular, spatial analysis can reveal previously hidden patterns and relationships, showing real-time changes within the city boundaries. But first of all, Location Intelligence is the most visual and intuitive which drives stronger decision-making.

Municipalities use LI to launch and improve projects in widely different areas. One of the most progressive city in terms of using LI solutions is New York, which deployed a new tool for data-driven decision making across city agencies about a year ago. The system collects the data from different departments, including information on safety and traffic, and visualize it as a dashboard with a series of individual indicators, statistical measures on current conditions and data trends to predict and resolve issues faster.


At the same time this tool is used not only by city authorities, but also by city residents – for instance, to illustrate the important issues for locals. One example to be mentioned is the map of toxic spills in Brooklyn made by a web developer Jill Hubley, who once became curious about what pollution fouls up her neighbourhood. Using open data from the New York State Department of Conservation to log 486 spills, she managed to demonstrate the problem, provoking a resonant discussion.


Some urban data visualization projects are not just useful for gaining new insights about the city life, but also incredibly interesting in content and aesthetics. For example, MIT Senseable City Lab just recently published the interactive map of actual walking, running and cycling routes in San Francisco and Boston to show how people move in those cities. The data for the study was collected via activity monitoring apps, its results can give us a better understanding of the factors that influence outdoor human activity (weather, urban morphology, topography, traffic, the presence of green areas, etc.).


LI technologies are essential for the issues, that still can’t be solved with traditional city management tools, and also are extremely useful for the purposes of city growth planning. Visualizing even just key demographic and economic indicators, urban planners now can identify and understand the need of schools, hospitals, parks and other public and private services in specific areas, let alone obtain deeper insights that can be gained from more sophisticated combinations of data.

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