High-Resolution Digital Topography in Arizona

Light Detection And Ranging (LiDAR) is revolutionizing our understanding of the tectonic and geomorphic processes that build and sculpt our planet’s surface. In an age where scientific and societal decision making depends on technologies such as the Global Positioning System (GPS) and remote sensing satellites, LiDAR is proving to be a powerful addition to our arsenal of observational tools that document the dynamic nature of Earth.  LiDAR enables us to accurately measure Earth’s topography at submeter scales, thus allowing us to characterize geologic processes in scales at which they develop and operate.

Figure 1. A LiDAR-equipped twin-engine Cessna Skymaster aircraft at the Prescott Regional Airport. The aircraft and its support crew are operated and managed by the National Center for Airborne Laser Mapping (NCALM; www.ncalm.org).

The basic operation of LiDAR is similar to Radio Detection And Ranging (RADAR), only it uses invisible laser pulses instead of radio waves to measure the distance between a laser source and an object (e.g., topography, outcrops). The laser pulses, called "shots", are emitted from a laser scanner at 10s to 100s kHz depending on the type of scanner. The travel times of the laser shots from the scanner to the object and back are measured and converted to ranges, essentially making the LiDAR scanner act like a laser rangefinder on steroids. By knowing the position and orientation of the scanner we can produce a “point cloud” of the reflected laser pulses that represents the scanned object. The point cloud can then be used to create a high-resolution 3-dimensional (3D) model of the object.

Two laser scanning systems are used in geoscience research and education: airborne and terrestrial LiDAR. Airborne LiDAR, known also as Airborne Laser Swath Mapping (ALSM), employs an aircraft-mounted scanner (Fig. 1) that scans the topography in side-to-side swaths perpendicular to the aircraft's flight path (featured banner image, above). The aircraft’s absolute location and orientation (yaw, pitch, and roll) are corrected for by inertial navigation measurements and high-precision GPS. This places the LiDAR data in a global reference frame. The point cloud that represents the topography can then be converted to a grid of elevations known as a digital elevation model (DEM) which may represent all of the data (including vegetation) or the ground surface alone (a “bare earth” model). Seeing through vegetation and measuring the surface topography at meter to submeter scales allows us to characterize topographic features in great detail. Terrestrial LiDAR, also known as Terrestrial Laser Scanning (TLS), employs a similar workflow but instead uses a tripod-mounted laser scanner to scan complex objects at close ranges and ultra-high resolutions (Fig. 3).

Figure 3. A tripod-mounted terrestrial laser scanner (TLS) in action. The University of Texas at Dallas Riegl LPM 321 scanner is shown here as part of the INTERFACE collaboration (http://facility.unavco.org/project_support/tls/tls.html#interface).

Both ALSM and TLS are conventionally used in industrial applications, including 3D mapping of mine shafts, oil and gas refineries, pipelines, tunnels, airports, and even crime scenes. However, increased affordability of LiDAR scanners and improved open-source data processing tools are making airborne and terrestrial LiDAR data products more accessible to the geoscientific research and education communities. In Arizona, some geoscience applications of LiDAR include hydrologic modeling of flooding in urban areas, assessing the geomorphology of landslides and debris flows in the Santa Catalina Mountains, and understanding the structural control of metamorphic core complexes on drainage network patterns and channel morphology.

Recently, TLS and ALSM LiDAR were used to characterize the geomorphic settings of precariously balanced rocks in the Granite Dells near Prescott (see Nature's Balanced Seismometers in Arizona Geology, v. 39). Precariously balanced rocks rest on bedrock pedestals and are used as negative indicators for earthquake-generated strong ground motions to physically assess the spatial extent of ground shaking due to earthquakes. Three-dimensional characteristics of a PBR, such as its shape, center of mass, moment of inertia, and the pedestal surface on which it rests, are highly sought after parameters in its application as a natural seismometer; they provide information on how a PBR will respond to earthquake-induced ground shaking. Previous attempts to document these characteristics employed photogrammetry, where multiple photographs are taken from different viewpoints to generate a 3D model of the PBR and its pedestal. However, the nature of the PBR’s form and its pedestal is often too complex for photogrammetry to sufficiently capture, thus limiting the quality of the PBR shake models. This is where TLS comes in. The PBR is scanned from multiple vantage points to create a dense point cloud from which a detailed 3D surface model can be created (Fig. 4). The results are accurate computations of the PBR’s geometric parameters (e.g., volume, center of mass, moment of inertia) and detailed imaging of the PBR-pedestal contact, both of which would otherwise not be accurately determined without toppling and destroying the PBR.

Figure 4. Scanning a precariously balanced rock (PBR) using a terrestrial laser scanner (TLS). Because of the complex form of the PBR, complete 3D mapping must be accomplished using multiple scan vantage points.  The final merged point cloud (bottom left inset) contains over 3.4 million laser points.

At a larger scale, the ALSM LiDAR coverage of the Granite Dells proved useful in documenting the geomorphic location of PBRs in drainage basins. Understanding their geomorphic context is an essential prerequisite to assessing their reliability as natural seismometers over thousands to hundreds of thousands of years. The ALSM scans produced a point cloud that spans the entirety of the Granite Dells (~33 km2 represented by ~360 million laser points; Fig. 5). The point cloud was gridded to produce a DEM at 0.25 m resolution (Fig. 6). To document where the PBRs are preserved, landscape metrics (e.g., terrain slope and drainage area) were computed using elevation values from the DEM at scales appropriate to the geomorphic processes that act on the PBRs. This analysis told us that moderately steep hillslopes between 10° and 45° are conducive to forming and preserving PBRs. Knowing this improves our understanding of where PBRs are likely to form and how long they are likely to remain balanced since their formation, both of which are critical parameters in the utility of PBRs as natural seismometers in seismic hazard research.

The above anecdote is only one demonstration of how the versatility of LiDAR makes it a valuable tool in geoscience research and education. From addressing Arizona's geoscientific questions to enhancing our students’ learning experiences, LiDAR paves the way to an exciting venue for the digital exploration of Earth’s surface. And continued interest in using LiDAR as an effectual observational and teaching tool will undoubtedly sprout many creative LiDAR applications in our topographically diverse state.

Figure 5. Oblique views of a subset of the airborne LiDAR point cloud of the Granite Dells. The dense nature of the data (~9 points per m2) captures geologic structures and geomorphic features in fine detail.

Figure 6. High-resolution digital elevation model (DEM) of the Granite Dells near Prescott. The DEM’s resolution is 0.25 m, meaning there is one elevation value for every 0.25 by 0.25-meter square.

Suggested LiDAR web resources:


The TLS component of this project is funded by a National Science Foundation grant: EAR 0651098 Collaborative Research: Facility Support: Building the INTERFACE Facility for Cm-Scale, 3D Digital Field Geology.

The ALS data were acquired by the National Center for Airborne Laser Mapping (NCALM) at the University of Houston and the University of California, Berkeley, for a graduate student Seed Grant.  NCALM is funded by the National Science Foundation.  Digital elevation models (DEMs) were generated using the GEON LiDAR Workflow in the Active Tectonics, Quantitative Structural Geology and Geomorphology research lab at Arizona State University, Tempe.

Suggested readings:
Arrowsmith, J R., and Zielke, O., 2009. Tectonic geomorphology of the San Andreas Fault zone from high-resolution topography: An example from the Cholame segment.  Geomorphology, v. 113, p. 70-81

Carter, W. E., Shrestha, R. L., and Slatton, K. C., 2007.  Geodetic laser scanning.  Physics Today, v. 60, no. 12, p. 41-47.

Haddad, D. E., 2009. Nature's Balanced Seismometers: Arizona Geology, v. 39, no. 1.

Lefsky, M. A., Cohen, W. B., Parker, G. G., and Harding, D. J., 2002. Lidar remote sensing for ecosystem studies. BioScience, v. 52, no. 1, p. 19-30.

Pelletier, J. D., Engelder, T., Comeau, D., Hudson, A., Leclerc, M., Youberg, A., and Diniega, S., 2009. Tectonic and structural control of fluvial channel morphology in metamorphic core complexes: The example of the Catalina-Rincon core complex, Arizona. Geosphere, v. 5, p. 363-384.

Tarolli, T., Arrowsmith, J R., and Vivoni, E. R., 2009. Understanding earth surface processes from remotely sensed digital terrain models: Geomorphology, v. 113, p. 1-3.


DAVID E. HADDAD,Graduate Student

Arizona State University
Tempe, AZ

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