Noise Contours

Determining noise pollution near airports.

Challenge

Mapfluence, Urban Mapping's embedded geographic technology, is used by customers across a wide range industries and business functions. These customers expose the company to a broad collection of ‘wants' around data, ranging from well-defined technical needs to ambiguous reflections of business requirements. So in 2009 when a real estate customer inquired about data to help determine noise pollution near airports, the UMI data acquisition team faced a real challenge.

Solution

The first step was defining the problem: does a solution exist? After brainstorming and initial research, the tea began to uncover reports conducted by airport authorities detailing noise exposure around runways. After identifying the correct departments within operating authorities and making numerous public record requests, the data acquisition team followed the paper trail and discovered a program administered by the US Federal Aviation Administration (FAA).

The FAA acts as the country's enforcer for commercial airline travel. In addition to running air traffic control, the FAA is charged with administration of the airport noise compatibility planning process under Federal Aviation Regulations (FAR) Part 150. After pouring over copious federal regulations, the team uncovered a well-defined data model. In short, whenever a new airport runway is constructed, federal law requires a comprehensive study of surrounding noise levels and mitigation plans. This is submitted to the FAA for approval and also resides with each airport authority. This results in a detailed report describing how each airport authority will comply with federal regulations. Noise contour maps are included - a hidden gem for Urban Mapping's data sourcing group.

While the FAA acts as a public overseer, it only approves these reports. Strangely, the substance of the reports is available only from the operating authority. Enter the first phase of data sourcing - contacting individual airport authorities. In doing so, the team aimed to understand the potential scale of the project. With over 1,000 commercial runways nationwide, the project team needed to narrow the scope. Do all airports matter? What about restricting to airports with only regularly-scheduled flights or only those serving turboprop and jet aircraft? Does the FAA policy apply to all airports? What about heliports? What precision is acceptable?

After muddling through these questions UMI was able to come up with a manageable list by focusing on airports where noise is an actual concern. This means there must be regular jet service and a nearby population to affect. With over 200 airports meeting these constraints, the team began the process of sourcing data. The FAA does not maintain a library of reports from airport operators, so each authority was contacted to request the underlying data. Some airports had publicly posted the reports submitted to the FAA, others were available upon request, and some denied the public record request citing vague concerns about security.

After overcoming numerous administrative challenges, we began the sourcing in earnest. When possible, UMI always seek source data - in this case spatial data in a machine-readable format. However, because many airport operators engaged outside engineering firms to conduct the studies, source data was not always available. This meant ingesting data in a variety of media formats - digital images (PNG, JPG, PDF etc…), large five by seven foot posters, and sometimes even scanned photocopies of reports.

The ingestion process is made up of several steps, and the underlying media drives each set of workflows. At a high level, this means digitizing, extracting or tracing contours, creating comprehensive metadata (to describe our process and explain the FAA requirements to the layperson) and testing the database by creating a variety of maps and spatial queries to better understand how the data behaves.

Finally, after defining the problem, acquiring raw data, ingesting appropriate format(s), creating descriptive metadata, and testing the database, Urban Mapping was able to release the project into a production database available to Mapfluence customers. These skills in custom sourcing high-value data allow Mapfluence to tackle inquiries from noise pollution to demographics and everything in between.