Geologists in Washington State use lidar to map landslides and faults, to study volcanoes, glaciers and rivers, and to model tsunami inundation. This narrative features over 50 intriguing lidar images that help illustrate how geologists in Washington are using this fascinating technology to study the landscape.

This dataset provides maps of aboveground forest biomass (AGB) of living trees and standing dead trees in Mg/ha across portions of Northwestern United States, including Washington, Oregon, Idaho, and Montana, at a spatial resolution of 30 m. Forest inventory data were compiled from 29 stakeholders that had overlapping lidar imagery. The collection totaled 3805 field plots with lidar imagery for 176 collections acquired between 2002 and 2016. Plot-level AGB estimates were calculated from tree measurements using the default allometric equations found in the Fire Fuels Extension (FFE) of the Forest Vegetation Simulator (FVS). The random forest algorithm was used to model AGB from lidar height and density metrics that were generated from the lidar returns within fixed-radius field plot footprints, gridded climate metrics obtained from the Climate-FVS Ready Data Server, and topographic estimates extracted from Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global elevation rasters. AGB was then mapped from the same lidar metrics gridded across the extent of the lidar collections at 30-m resolution. The standard deviation of estimated AGB of the terminal nodes from the random forest predictions was also mapped to show pixel-level model uncertainty. Note that the AGB estimates are, for the most part, a single snapshot in time and that the forest conditions are not necessarily representative of the larger study area.

Product: Classified LAS 1.4 files, formatted to 628 individual 4500ft x 4500ft covering the Thurston County project area. Geographic Extent: This dataset and derived products encompass an area covering approximately 199,484 acres of Western Washington. Dataset Description: The Thurston County Lidar project called for the planning, acquisition, and processing of lidar data collected to Qualit...

Data was collected in September 2018 for 3-D high resolution geologic mapping of the Goat Rocks Volcano in Washington State. This collection was part of a 2017 Seed Project for Kellie Wall at Oregon State University. Approximately 67 km² of high resolution data were collected for this project.

Publications associated with this dataset can be found at NCALM's Data Tracking Center

RTK (real time kinematic) ground control points collected for the PSLC King County Delivery Lidar dataset. RTK ground control points are used during the calibration process to help refine the vertical accuracy of the LiDAR data. Data was processed in reference to NAD83 (CORS96), however the horizontal datum for this dataset is defined as NAD83 (HARN) as the difference is generally small and allows for greater ease of use with data in different datums. The vertical datum is NAVD88, Geoid 03, and the data is projected in Washington State Plane North. Units are in US Survey Feet. Quantum Spatial collected the PSLC King County Delivery Lidar data for the Puget Sound LiDAR Consortium between 02/24/16 and 05/25/17.

This is a tiled collection of the 3D Elevation Program (3DEP) and is one meter resolution. The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Scientists and resource managers use 3DEP data for hydrologic modeling, resource monitoring, mapping and visualization, and many other applications. The elevations in this DEM represent the topographic bare-earth surface. USGS standard one-meter DEMs are produced exclusively from high resolution light detection and ranging (lidar) source data of one-meter or higher resolution. One-meter DEM surfaces are seamless within collection projects, but, not necessarily seamless across projects. The spatial reference used for tiles of the one-meter DEM within the conterminous United States (CONUS) is Universal Transverse Mercator (UTM) in units of meters, and in conformance with the North American Datum of 1983 ...

These data cover a popular area for field geologic mapping courses called the Poleta Folds. The area is at the southern end of Deep Springs Valley, southeast of Bishop, CA. The purpose of collecting the data was to provide a good topographic base map for students to learn to map complex geologic structures.

Fragile geologic features (FGFs) are elements of the landscape that are vulnerable to destruction during sufficiently strong earthquake ground shaking. As result, the observation of extant FGFs on the landscape may constrain the maximum intensity of past earthquake shaking. McPhillips and Scharer (2022, Survey of fragile geologic features and their quasi-static earthquake ground motion constraints, southern Oregon, Bulletin of the Seismological Society of America 112 (1)) demonstrated the potential to derive useful ground motion constraints from rock towers, such as sea stacks, in the Pacific Northwest region of the United States. The data set presented here extends the survey of McPhillips and Scharer (2022) along the length of the Oregon and Washington coasts and locally inland. Rock towers were remotely surveyed using freely available oblique aerial imagery (https://www.oregonshorezone.info/ and https://apps.ecology.wa.gov/shorephotoviewer/Map/ShorelinePhotoViewer, last accessed 16 September 2022) and lidar point clouds (without filtering by classification; https://portal.opentopography.org/datasets, last accessed 16 September 2022). A total of 78 new, and potentially fragile, features were identified. Geometrical parameters for these features were extracted from the lidar data using methods described in McPhillips and Scharer (2022). The quasi-static failure accelerations and first resonance modes of the features were calculated from the geometrical parameters using Equations Two and Three, respectively, from McPhillips and Scharer (2022). These equations also require for material properties of the features. For the purpose of this remote survey, we used average values from McPhillips and Scharer (2022): 2.4 grams per cubic centimeter, bulk density; 1.7 megapascals, tensile strength; and 8.0 gigapascals, Young's Modulus. The sea stacks in this survey are composed of rocks similar to southern Oregon, including marine sandstone, basalt, and basaltic melange (https://www.dnr.wa.gov/geologyportal and https://gis.dogami.oregon.gov/maps/geologicmap/, accessed 10 July 2022). Bulk density and tensile strength estimates were also measured in the field for sandstone at Toleak Point, in Washington State, in April 2022. There, tensile strength was measured in situ using a rebound hammer, using methods from McPhillips and Scharer (2022), and found to be approximately 1.5 megapascals. Bulk density was estimated by measuring the displacement (volume) and mass of cobbles on the beach and found to be approximately 2.3 grams per cubic centimeter. These values are interpreted to support the choice to use average values from McPhillips and Scharer (2022). Among the 78 surveyed features, 55 are likely old enough to have experienced at least two megathrust earthquakes. Following McPhillips and Scharer (2018), we estimated the ages of sea stacks as a function of distance from sea cliffs, in this case using a threshold of greater than 94 m. We also assumed that all inland features are sufficiently old. Among these 55 features, the average failure acceleration is 2.29 g and the 20th percentile value is 0.77 g. McPhillips and Scharer (2022) showed that the uncertainty for individual failure acceleration estimates is frequently greater than 50%, and similar uncertainties are expected for the data reported here. The average first resonance mode is 0.11 seconds. The fragility accelerations presented here may be suitable for comparison with spectral accelerations derived from earthquake ground motion simulations near the periods of the first resonance modes; these data are maximum constraints, and should not be taken to represent the most likely shaking intensities.