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Tuesday 18 October 2005: Session 1, 9:00:00 AM
Managing Very Large LIDAR Point Clouds in an Enterprise Database
Presentation Abstract
Airborne LIDAR sensors are quickly becoming one of the most effective methods of collecting high resolution terrain data – in many cases rivaling photogrammetric collection in both accuracy and cost. Each of the laser returns from these sensors represent the three dimensional coordinates of an object on or near the earth’s surface and, when collected over even a moderately large area, can easily number in the billions. Only a few specialized software applications are able to load and view this massive amount of data. Even fewer applications allow interpolation to a grid and eventual classification of returns as surface, tree canopy, building, water, etc. However, even these generally expensive applications don’t allow easy integration of laser returns with existing GIS data such as building footprints, street centerlines and land use polygons which could be used to help understand the returns. One possible solution to integrating this data with existing desktop GIS clients is to store and/or analyze the laser returns in an enterprise geospatial database. CAST, working with the one billion (plus) laser returns from the Northwest Arkansas Regional Planning Commission orthophotography project in Washington and Benton counties, has developed several storage and indexing schemes in Oracle 10g to evaluate its ability to quickly perform attribute and spatial queries against these laser returns and perform complex spatial analysis. The results of these investigations will be presented along with an example of how these capabilities can be used to select all returns in a specified geographic area, classify those returns as surface, canopy, or building, interpolate the irregular surface points using various algorithms that involve nearest neighbor selection, and deliver the results to a desktop GIS client. Successful implementation of an enterprise LIDAR return processing system will potentially allow local governments and smaller engineering firms more economical access to and analysis of this important source of surface data.
Speaker Biographical Information
Jackson Cothren Assistant Professor, Geosciences: RGIS Mid-South Center for Advanced Spatial Technologies (CAST) - University of Arkansas
Dr. Jackson Cothren is an Assistant Professor in the Department of Geosciences at the University of Arkansas and a research scientist at the Center for Advanced Spatial Technologies (www.cast.uark.edu), also at the University of Arkansas. He has worked extensively with Quickbird imagery as a source of imagery to update aging orthophotos and quickly generate impervious surface maps. Dr. Cothren has worked with high school students across seven states to introduce fundamental and advanced GIS and remote sensing technical and planning skills as a member of the EAST Geospatial Support team at CAST (www.cast.uark.edu/cast/east and www.eastproject.org), develop curriculum for more than seven different two to five day short courses and visited more than 50 EAST labs in schools across California and Arkansas. Before joining CAST and the University of Arkansas, Dr. Cothren spend almost 12 years as an Air Force officer and as a civilian photogrammetric engineer working for the Air Force responsible for the direction and management of all photogrammetric and geodetic research at the National Air Intelligence Center. He has worked as professional consultant to private industry to develop digital photogrammetry software.
