Lidar surveys contracted by the Puget Sound Lidar Consortium (PSLC, includes local government staff and USGS and NASA researchers, http://pugetsoundlidar.org) will have covered 8,000 km² of the central, western, and southern Puget Lowland by May 2002, barring bad weather and equipment failure. Topography with 6 ft (2 m) X-Y resolution and Z accuracy of ~30 cm, except in areas of extremely dense second-growth forest, is calculated from data obtained with a small-footprint, discrete-return airborne laser scanner that generates 1 pulse/m² and records up to 4 returns/pulse. We began late in 1999 with a shared goal of identifying Holocene fault scarps to be trenched for seismic hazard studies. To date we have identified 5 probable Holocene fault scarps. Harding and others (this meeting) describe details of Holocene deformation extracted from lidar topography of the Seattle fault zone. Lidar topography has other geologic uses, including: 1) Landslide inventory: large deep-seated slides can be mapped consistently. Small shallow slides are not mappable, but the steep slopes and contributing areas that control their occurrence are. 2) Geomorphic mapping that assigns origins and relative ages to all topographic surfaces. Where constructional landforms dominate, such a map is an excellent proxy for a geologic map. 3) A topographic base for detailed conventional geologic mapping at scales as large as 1:6,000. 4) Quantitative geomorphology: one can extrapolate to end-Vashon (15 ka) landforms and quantify changes since then. Long-term rates of stream erosion, landsliding, and other processes can be evaluated. Lidar data are also being used to address non-geologic concerns including hydrology, transportation planning, and endangered species habitat. Characterization of forest canopy from vegetation returns (2/3 of the total) may eventually prove to be the most valuable use of the data.

We hope to cover the entire Puget Lowland, but face several challenges. Funding is not sustained. Strategies for surveying high-relief areas need to be developed. Tools to monitor data completeness, consistency, and accuracy are incomplete. Procedures for classifying returns as forest, structure, ground, or blunder need to be improved and automated. Delivery of voluminous lidar data to the public is daunting.