Product Overview: GeoEye’s RoadTracker

By Christopher J. Andrews

Ask industry professionals to list the directions in which the boundaries of geospatial technology are being pushed and the first answers are likely to include 3D visualization, the Internet, and wireless or mobile technology. Probe a little deeper, however, and the discussion quickly turns to the core issue of data pricing, access and delivery.

Although issues of timeliness, quality and data availability predate the entire geospatial field, these issues continue to constrain the applications and technologies that are available to potential data consumers. Readily available mapping Web services have presented geospatial applications to consumers in new ways; those mapping services are also generating more questions, ranging from data licensing to the accessibility of up-to-date spatial features.

The increasing use of satellite imagery, street map and point of interest (POI) data within mapping Web services is creating pressure to commoditize geospatial data, and is pulling the market away from its traditional services-based business model, which was focused on high-end consumers. These new pressures identify gaps in the market and have created the perfect environment to drive innovation in geospatial business models, data delivery mechanisms and applications. Users need better raster image processing tools, like RoadTracker.

RoadTracker Background
Enter Zachary Bergen and the R&D team at GeoEye. Bergen and his coworkers are the kinds of people who recognize opportunity, have the technical acumen to implement their ideas, and have a management team that lets them work and deliver with confidence. In 2006, Bergen joined GeoEye as a principal geodetic engineer and was given the enviable challenge of picking a task and running with it. Hired for his long experience in the industry, breadth of knowledge and reputation for building complex high-quality products, Bergen realized that he could improve upon an existing GeoEye linear feature detection tool.

After some deliberation, Bergen and his team decided that the best way to realize the full potential of the GeoEye linear feature detection tool, RoadTracker, would be to re-architect it into a componentized plug-in that would operate as part of a standard geospatial application toolkit. They accomplished this task by leveraging a strategic partnership with Visual Learning Systems (VLS). The GeoEye R&D team took advantage of VLS' Feature Analyst toolkit, which can be used as a programming interface for adding advanced imagery analysis tools to a number of geospatial packages, such as IMAGINE, ArcGIS and Socet Set. RoadTracker is not yet officially a product, but will be released soon via VLS.

RoadTracker Key Features
  • High degree of automation speeds centerline detection
  • Automatic detection of intersections and adjustment of existing centerlines improves network accuracy
  • Automatic centerline feature attribution based on imagery analysis removes manual rework
  • 'Smart editing' simplifies feature correction workflow
  • Complements any geospatial environment that supports VLS' Feature Analyst
RoadTracker is a proprietary application built on top of Feature Analyst. It is a semi-automated tool that detects road centerlines in orthophotos and automatically computes road attribute data when the centerlines are extracted as vector features. The tool changes the traditional workflow for centerline creation from manually intensive point-and-click digitizing to an efficient process that automates centerline creation, attribution, intersection insertion and topology cleaning.

Because automation is rarely perfect, the tool provides an additional capability for “smart editing,” which allows users to follow an intuitive, semi-automated process to correct errors in a network of linear features without manipulating individual vertices. RoadTracker is already in use by GeoEye clients. In testing and production, GeoEye has discovered that RoadTracker's technology dramatically reduces the manual effort required for feature extraction. Further refinement of the technology carries with it the potential for RoadTracker to detect not only road centerlines, but also other curvilinear features, such as railroad tracks, streams and more.

After selecting a RoadTracker editing tool from within a standard geospatial package, the user collects two pixels that approximate a new centerline's endpoints (A). RoadTracker creates an initial solution (B). Existing road features are suppressed so that when the same two endpoints are used, a new path is found that completes the loop (C). (Click for larger image)


What's Next
The potential of the new generation of tools like RoadTracker extends far beyond improving individual analysts' daily workflows. In my opinion, the capability to quickly and accurately extract vector features and attributes from imagery may be a lead-in technology that enables companies like GeoEye to begin delivering just-in-time packages of vector and image data to clients who desire more than the mapping services currently available on the Web can offer. The right combination of technologies, such as automated feature detection, spatially intelligent databases and compressed data serving, may allow data providers to bridge the timing and cost gaps that limit the rapid adoption of imagery data in enterprise applications today. These technologies may enable data providers to offer just-in-time data as a subscription service. This would create an ongoing revenue source for data providers while giving clients access to high-resolution, accurate and timely packages of imagery and vector data.

Market pressures are pushing data providers to offer richer datasets on demand. Providers would like to retain control over data licensing and access while tracking data usage. In a truly commoditized market, experienced clients will push back against proprietary technologies that limit use or access to multiple providers' imagery services. These clients will demand that imagery providers serve data through standardized Web interfaces and use common tools to query data by attributes such as date, resolution, cloud percentage and much more. In fact, the industry is already moving in these directions. In addition to published imagery data models coming on the market in the form of tools such as Feature Analyst, companies such as ITT Visual Information Systems (ITT) are building high-throughput data serving tools. Harris Corporation built a first generation high-speed imagery delivery system on top of ITT's Image Access Solutions (IAS) for its government clients. When the next generation of packaged imagery and vector data merges with standardized high-speed data delivery packages, the potential will emerge to serve richer data to a broader set of users.

The real market test will be to see if geospatial digital rights management technologies can be created and integrated with emerging just-in-time data services within a pricing model that will provide more accurate and immediate data to a broader set of consumers, while limiting data producers' loss of revenue to unauthorized data use. That road will surely be a bit rocky, as the industry evolves to simultaneously accommodate both those who want more open and accessible data and the data providers who will continue to need to realize revenue. The good news is that the market is driving geospatial technology applications and data providers to provide better workflows, improved data, and more functionality to an increasingly diverse set of mapping technology users.


Published Thursday, May 10th, 2007

Written by Christopher J. Andrews



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