USING AIRBORNE LIDAR AND GIS TECHNOLOGIES FOR FIELD VERIFIED VIRTUAL LANDSLIDE HAZARD MAPPING— A NEW APPROACH TO AN OLD PROBLEM WITH EXAMPLES FROM PAPUA NEW GUINEA AND SAN FRANCISCO

The increasing availability of LiDAR digital elevation models (DEMs) as practical geological tools calls for a re-evaluation of traditional landslide mapping practices. In many projects, LiDAR data are underutilized by geologists who limit themselves to shaded relief images and topographic contour maps. In other cases, inappropriate data collection or processing by LiDAR vendors yields results of limited utility in steep and heavily forested terrain. As illustrated using examples from consulting projects in Papua New Guinea and San Francisco, the value of LiDAR data can be leveraged by collaborating with the vendor to ensure that data meet project needs, using ancillary data such as laser ground strike and return intensity maps, creating suites of shaded relief images and geomorphic derivative maps (e.g., topographic slope, curvature, and roughness) to help delineate landforms, and integrating the results of empirical qualitative maps with empirical or process based quantitative maps to perform holistic hazard analyses. Working with bare earth xyz(i) point cloud data rather than pre-gridded DEMs gives practitioners the flexibility to experiment with interpolation methods that create geologically realistic, rather than mathematically expeditious, DEMs. The methods discussed in this presentation in many cases allow useful provisional virtual maps to be prepared and vetted in the office. This is accomplished by creating a multi-layered and geo-referenced assemblage of all available LiDAR data layers, orthophotos, published geologic maps, infrastructure maps, and borehole location maps. The uppermost layer is a drawing layer that serves as a blank sheet for the provisional virtual map. Virtual maps can arguably allow landforms of interest to be identified and mapped more accurately than might be done in the field, particularly if terrain is rough and GPS coverage is limited, thereby maximizing the value of-- but never eliminating-- expensive and time-consuming fieldwork.