Capitalizing on Local Governments Investment in LiDAR

In the movie Field of Dreams an Iowa farmer (played by Kevin Costner) sees a vision of a baseball field and hears a voice whisper, If you build it, he will come. His neighbors think he is crazy when he decides to plow over his corn field and replace it with a baseball diamond.

To some extent local governments have taken a similar approach when it comes to LiDAR. In this Field of Dreams scenario the hope is that if LiDAR data are purchased, great things will happen with it. The reality is that unlike in the movie, the equivalent of Shoeless Joe Jackson never appears and the data often are underutilized.

The blame cannot, and should not, be placed on local government as there are substantial challenges in working with LiDAR data. First and foremost, LiDAR is significantly different from other sources of geospatial data. While local governments have mastered working with vector (e.g. road centerlines) and raster (e.g. aerial imagery) data sets, it is highly likely that no one on staff has ever worked with a LiDAR point cloud. This challenge is compounded by the fact that the vast majority of GIS software packages are not well suited to working with LiDAR datasets that may contain hundreds of millions or even billions of points.

In my work using LiDAR data sourced from local government to map land cover in urbanized areas, I find that even in major cities with well-established GIS departments, the point cloud has never been looked at and the term LiDAR is typically taken to mean a high-resolution bare earth Digital Elevation Model (DEM).

I believe that we as the LiDAR community have a stake in insuring that local governments get the most out of their investment in LiDAR. In these challenging economic times, funding for data acquisition projects that do not improve the local decision making process will dry up. Federal government agencies and academia need to provide local governments with unbiased advice, guidance, and training. LiDAR vendors need to take the time to adequately explain the deliverables to the client and provide easily understandable, yet comprehensive documentation. Local governments that purchase LiDAR data should budget the necessary funds to insure that they can visualize, analyze, manage, and distribute the data.

Specifically, there are three things local governments can budget for that will enable them to get the most out of their LiDAR data.
1. The first is LiDAR-specific software, such as Quick Terrain Modeler, that allows one to view and work with the point cloud.
2. The second is derived raster products. Unlike point clouds, raster datasets, even those in the tens of gigabytes, display with ease in most standard GIS software packages. In addition to a bare earth Digital Elevation Model (DEM) I recommended budgeting funds (either through staff time or paying the contractor) to generate a Digital Surface Model (DSM), a Normalized Digital Surface Model (nDSM), and intensity images.
3. Thirdly, an organization should insure that they have the hardware to store and distribute the LiDAR data along with specialized LiDAR workstations should they plan to generate the derived raster products themselves or analyze large data sets. Collectively, these investments typically amount to a fraction of the cost of the LiDAR data itself.

Larger governments may want to consider hosting a LiDAR workshop once the data are delivered. The City of New York hosted such a workshop this past summer to prepare the dozens of city agencies for LiDAR data acquired in spring 2010. Formal presentations from the vendor (Sanborn), federal and local government, and academia covered a broad set of topics ranging from the technical details surrounding the acquisition of the data to a review of commercial LiDAR software packages.

In my next article I will discuss the techniques my team and I have developed, fusing LiDAR, imagery, and GIS datasets to extract detailed land cover information, generating a return on investment from existing data acquisitions.

About the Author

Jarlath ONeil-Dunne

Jarlath O'Neil-Dunne ... Jarlath O'Neil-Dunne is a researcher with the University of Vermont's (UVM) Spatial Analysis Laboratory (SAL) and also holds a joint appointment with the USDA Forest Service's Northern Research Station. He has over 15 years experience with GIS and remote sensing and is recognized as a leading expert on the design and application of Object-Based Image Analysis Systems (OBIA) for automated land cover mapping. His team at the SAL has generated billions of pixels worth of high-resolution land cover data from a variety of aerial, satellite, and LiDAR sensors in support of urban forestry planning, ecosystem service estimation, and water quality modeling. In addition to his research duties he teaches introductory and advanced courses in GIS and remote sensing using ArcGIS, ERDAS IMAGINE, eCognition, and QT Modeler. He earned a Bachelor of Science in Forestry from the University of New Hampshire, a Masters of Science in Water Resources from the University of Vermont, and certificates in hyperspectral image exploitation and joint GIS operations from the National Geospatial Intelligence College. He is a former officer in the United States Marine Corps where commanded infantry, counter-terrorism, and geospatial intelligence units.
Contact Jarlath Article List Below