Launch Slideshow

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Truth in stormwater billing

Truth in stormwater billing

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    Digital surface models of downtown Columbus, Ohio, as captured from light detection and ranging (LiDAR) instruments. Photos: City of Columbus and Woolpert Inc.

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    Data from Woolpert Inc.'s automated feature extraction process indicates that Columbus, Ohio's impervious surface maps left out nearly 29,000 square feet of impervious surface at the Eastland Mall pilot area. Source: Columbus (Ohio) Public Utilities, Operational Support Office

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    By combining digital orthoimagery with light detection and ranging (LiDAR) datasets to recalculate the Eastland Mall pilot area's existing impervious surface, the Columbus Public Utilities Department increased monthly stormwater billing revenue by $76 (nearly $1,000/year). Source: Columbus (Ohio) Public Utilities, Operational Support Office

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    This photo represents existing AutoCAD data of parking lot islands delineated using as-built drawings.

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    This photo shows new impervious surfaces delineated using remote-sensing techniques (digital orthoimagery and LiDAR data). Conclusion: Far fewer impervious islands exist than originally thought.

How do you get city officials excited about impervious surfaces? Tell them that by mapping these areas properly, the city can potentially recoup substantial amounts of revenue.

Such was the case for the Columbus Public Utilities Department in Ohio, which recently completed a comprehensive evaluation of roads, sidewalks, and parking lots in commercial and industrial zones throughout the city's entire stormwater surface area. The resulting up-to-date impervious surface maps enabled staff to accurately evaluate and assess stormwater billing and develop a fair, equitable billing system.

Public Utilities GIS Analyst Larry Moore says the goal is not to justify increased charges, but to make charges more accurate. “In some cases the city may be undercharging, but in others it may find it has been overcharging. Our aim is to be as fair and accurate as possible,” explains Moore.

The increased accuracy also helps fulfill EPA's National Pollutant Discharge Elimination System (NPDES) mandate that requires municipalities to have an established stormwater management program.

HISTORICAL MAPPING METHODS LACK PRECISION

The last time Columbus performed a full impervious surface mapping (ISM) analysis was in the early 1990s. At the time, the photogrammetric techniques used were state-of-the-art and relied on 3D stereo mapping protocols — including aerial film and analytical stereo compilation workstations — to capture impervious surfaces.

Since then, the city experienced an 18% population growth. Updating the maps to keep them current proved to be both labor-intensive and costly, since the process requires substantial manual “heads-up” digitizing within AutoCAD — i.e., using orthoimagery as a background, which provides a top-down view of land surfaces created by rectifying aerial imagery to a surface model.

Because these now-traditional ISM methods are largely manual and subject to human error, they're laden with potential inaccuracies. Plus, the quality of the orthoimagery is subject to variances due to weather conditions, seasonal factors (onset of vegetation, etc.), density of objects, and scale of the target area.

“Regardless of the quality of the aerial photography, impervious surfaces are often obscured by building structures, areas of shadow, and tree canopies, so the resulting ISMs suffer from blind spots,” explains Aaron Lawrence, remote-sensing specialist with Woolpert Inc., a geospatial firm specializing in remote sensing and automated feature extraction techniques.

Three-dimensional stereo imagery techniques offer some improvements over orthoimagery, but human error, costs, and extended analysis time frames are still potential issues.


















NEW TECHNOLOGY SHEDS LIGHT ON ISMS

In 2008, Woolpert approached the Operational Support Group within the Columbus Public Utilities Department with an offer to perform a pilot project using the firm's newly automated feature extraction technology: an object-oriented software program that combines digital orthoimagery with light detection and ranging (Li-DAR) datasets.

LiDAR is a remote-sensing technology that uses pulses from an aerial laser-scanning unit to create digital surface models, which provides a level of accuracy that was previously unattainable. This automated feature extraction process relies on software (i.e., automation), rather than manual input, to perform analysis. In essence, the automated feature extraction process teaches high-level computer programs to identify ground features that have been traditionally identified by a human being, thereby providing a substantial reduction in time and associated costs, but at the same time increases the accuracy and consistency of the resultant data set.

“We knew that our technology would be a dramatic improvement in the precision of their data models,” says Lawrence. The new remote-sensing technologies also offer reduced cost and time to execute — especially over large land areas.

With the Eastland Mall (located on the eastern side of Columbus) as the first target area, Woolpert clearly delineated the impervious surfaces and uncovered discrepancies in the city's existing ISMs. Areas previously identified as pervious grass islands were in actuality impervious asphalt. The findings painted a new picture of stormwater runoff for the city.

“Many of the parking islands that were drawn up in the CAD file [to depict grassy areas] were never actually part of the construction project,” says Lawrence. “There were far fewer pervious areas than originally thought, which equated to an undercharge to the property owners.”

“The assessment opened everyone's eyes to the opportunity before us,” Moore adds.” Regardless of financial ROI [return on investment], the political cache that comes with improving accuracy and equity to our commercial and industrial clients is invaluable.”

After the pilot was completed and benefits identified by the city, Woolpert extended its project area to include an approximate 600-square-mile area that includes all of Franklin County and portions of four adjacent counties. In April 2009, the broader ISM process began in earnest with new digital orthoimagery and refreshed LiDAR datasets. Completed in December 2009, the project cost $320,000 and was funded through the city's stormwater utility fund. The city plans to update citywide impervious surfaces within the next two years.

THE PROOF IS IN THE BOTTOM LINE

The public utilities department continues to use the newly developed ISM database to support the billing of its commercial and industrial clients for stormwater charges. “It allows us to verify our past processes while embracing improved technological opportunities to ensure the accurate billing of our customers,” says Public Utilities GIS Manager Todd Pulsifer.

While immediate ROI data from the 2009 project is not yet available, information from the 2008 Eastland Mall pilot program is a good indicator of the returns the city can hope to expect with the citywide effort. Columbus is gaining nearly $1,000 in annual revenue from the pilot area alone. Eastland Mall is one of approximately 45,000 commercial and industrial parcels within the city's storm-water service area.

While the assumption is that not all parcels will provide an increase in impervious surface area and thus additional storm-water revenue, it is anticipated that the process will provide a more fair assessment to the land owners in Columbus.

— Stevens (brian.stevens@woolpert.com) is a project manager at Woolpert Inc., Dayton, Ohio.


Web Extra

For more about automated feature extraction, visit here.


The benefits of automated feature extraction.
  • High degree of accuracy. By reducing human error and reliance on software rule sets to identify impervious surfaces, you can develop a consistent and fair stormwater billing approach.
  • Cost effective. Remote-sensing techniques that use light detection and ranging (LiDAR) and digital orthoimagery are less costly than traditional methods, so you can perform automated feature extraction on a more frequent (even yearly) basis.
  • Shorter completion time frame. Using LiDAR and orthoimagery within an automated feature extraction process cuts analysis time by at least half. This permits faster processing and more frequent analysis of impervious surfaces, allowing a city to benefit from more up-to-date information contained within it's billing system.
  • Change detection analysis. Once a baseline impervious surface mapping (ISM) database is set, subsequent change detection analysis is easily performed and recommended to preserve accurate data sets.
  • Inegration of historic data. The ISM process incorporates historical data into the LiDAR-based data set to preserve the value of a city's previous investments. Parcel, zoning, road centerline, and land-cover maps all can be used to contribute to the analysis.
  • Additional data leverage. The same data used for the creation of impervious surfaces can also be leveraged to create additional data layers, including but not limited to woodland delineation, building extraction, and a citywide land-cover layer.
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