Is LiDAR Disruptive Technology?

by | Feb 14, 2014

By Patrick Cunningham, president, Blue Marble Geographics (, Hallowell, Maine.

The use of light detection and ranging (LiDAR) data has taken center stage in geospatial technology during the last few years. LiDAR data collection hardware vendors and service providers, who historically supplied imagery or survey services, have teamed to offer numerous options for collecting and delivering highly precise data.

Now business consumers are requisitioning LiDAR data with greater frequency, and public entities are starting to offer the data for free. Such data mark a paradigm shift for survey and geographic information system (GIS) professionals for good reason”one pass of a LiDAR camera can collect tens of thousands of individual survey points. Similarly, a street intersection can be scanned with a vehicle-mounted LiDAR camera in a few minutes, collecting hundreds of thousands of points to complete the job quickly and accurately. Not long ago such work would take surveyors with tripods hours to complete, and they'd never have as many points or such comprehensive coverage.

LiDAR data collection is a complex process (see Designing Effective QC for LiDAR Projects, page 12), but the final deliverable provides real 3-D survey data and GIS post-processing at users' fingertips. Now it is common to receive a GIS deliverable that's top-down 2-D and virtually immersive 3-D. Other common consumer GIS solutions have pushed the envelope, forcing traditional GIS vendors to compete with 3-D simply because it is so common in our daily Web browsing. LiDAR, combined with 3-D consumer GIS, is pushing GIS software vendors to innovate in new and exciting ways.

Innovation Insights

There are many ways to think about technology innovation and the changes that result. Many analysts say disruptive technology is the sort of game changer needed to force innovation in an industry. What defines disruptive technology is a matter of opinion, but there's a pattern that emerges after a technology becomes relevant in a particular industry. Making the call on whether something is disruptive takes a bit of hindsight and thus the passage of time.

Traditional disruptive technologies include things like the automobile and its predecessor the manufacturing assembly line, the light bulb and its partner electricity, and the Internet and the personal computer. But there are lesser yet important disruptive technologies within industries, such as the television and telephone.

It may be early yet, but it feels like LiDAR may be a mini-disruptive technology for GIS software. A great example of how LiDAR is disrupting the geospatial industry is the recent popularity of LiDAR point-cloud data support in almost every commercial GIS solution.

To determine if this is true disruption, consider whether a software solution supports the full point cloud or just displays a 3-D version of the data. To truly support point clouds, software needs to be able to scale, manage memory and allow a user to properly work with all of that great data. There's no innovation if a software package trims or decimates the data without giving a user the ability to choose how, what or if decimation occurs. To process LiDAR data, software must be able to manage all of the data.

Driving the Need for 3-D Data

3-D data push the envelope in a lot of ways, forcing software companies to innovate. If you're a GIS software developer today, gone are the handcuffs of a limited 2-D GIS universe. Developers used to get excited about extension writing, custom GIS scripting and Web-based mapping. After being involved in software for several decades, I'm now seeing the tremendous influence gaming has had on today's software developers. It seems almost every software developer I've hired recently is into gaming in his/her spare time. This isn't to be confused with playing video games”it's gaming, which today is figuratively and literally a world unto itself.

So developers are ready to embrace LiDAR for their own nefarious reasons. But let's get realistic here. LiDAR data aren't video-game data, and consumers need to be aware of that distinction for most GIS solutions. If you acquire LiDAR data, identify your end deliverable and goals to make the right decisions about managing and post-processing the data.

LiDAR is a dense format. With at least one point for every return and a typical file having millions of points, you quickly end up with a massive amount of data. LiDAR deliverables are presented in terabytes and require huge hard drives.

The problem with the gaming-engine perspective is that the data either need to be translated into a proprietary format or decimated to a point where a lot of the power of the data is limited and less useful for analysis. And the truth is many GIS software solutions can handle these large files only if they decimate them. That's why consumers should pick their post-processing software carefully, or they will not be able to access the full range of the dataset they put so much time into collecting or acquiring.

Selecting LiDAR Software

LiDAR is still new, but it is so compelling that it is highly visible in the media and at tradeshows. Many software developers have stepped forward to provide high-end, overly expensive yet incomplete solutions for GIS professionals who need to process LiDAR data into a deliverable format.

The commonly held perception is that a cutting-edge solution should be expensive, but there's a divide such expensive solutions generally fall along that software consumers need to know about. There are the traditional GIS or computer-aided design solutions that have added a LiDAR tool. These solutions tend to lack real post-processing tools and quickly and automatically decimate LiDAR data into smaller files that are more easily consumed by a GIS.

Then there are the higher end, more technically powerful tools that often are tied to vendors' data-collection solutions. The tools in the first set are overly simplified and misleading to consumers, and those in the second set are overly complicated and offer too much functionality for GIS generalists to use.

LiDAR consumers must be aware of the need to post-process the entire dataset. LiDAR data users need to look for software that can give them the option to decimate the data if they want to without automatically doing so behind the scenes. Data rendering is only one step in the process. LiDAR data's value comes from the accuracy, quality and range of the points supplied in each file. Yes, software vendors need to innovate to truly support LiDAR data, but I encourage LiDAR users to continue to push the GIS envelope with tools that innovate with them.               



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