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Dr. Steve Bowman

Synthetic Aperture Radar (SAR) Data from NASA’s ASF DAAC helps scientists like Dr. Steve Bowman provide Utah’s citizens with timely scientific information about the state’s geologic hazards.

Dr. Steve D. Bowman, Geologic Hazards Program Manager with the Utah Geological Survey and member of the ASF DAAC User Working Group.

Research Interests: Geologic emergency response; researching and mapping geologic hazards; and providing technical outreach to local governments and the public. This involves working with local, state, and federal government officials and staff during and after emergencies; providing scientific advice and expertise; securing funding to support hazards mapping and research; working with student volunteers and technicians; and leading a state program focused on geologic hazards.

Research Highlights: Early on the morning of March 18, 2020, a magnitude 5.7 earthquake shook the Wasatch Front, a metropolitan region in the north-central part of the state that is home to more than 85 percent of Utah’s population. The earthquake was centered about eight miles south of the town of Magna, about 10 miles west of Salt Lake City, and widely felt along the Wasatch Front into Idaho and Wyoming. No one died in the earthquake, thankfully, but multiple injuries and damage to buildings and homes were reported. The Magna earthquake was the largest quake along the Wasatch Front since 1847, and a reminder that Utah is a seismically active place.

Earthquakes are perhaps the most dramatic and destructive of Utah’s geologic hazards, but strong earthquakes are rare. Utah has experienced just 17 earthquakes greater than magnitude 5.5 since 1847. There are, however, a variety of other geologic hazards impacting the people of Utah—landslides; avalanches and rockfalls; flooding; radon; and soils that shrink, swell, or compact — that, although not life-threatening, are more frequent and capable of causing considerable damage.

The most common geologic hazards in the Beehive State are landslides and flooding, and given the state’s landscape characteristics, it is easy to see why. According to information from the state’s website, “approximately 45 percent of the state is mountain, hill, and steep-valley terrain conducive to landslides.” Further, this type of terrain exacerbates the risk of flooding from summer storms and rapid snowmelt that cascades down valleys and canyons surrounded by steep mountainous slopes onto normally dry land.

Fortunately, the conditions known to cause landslides, flooding, and other geologic hazards are generally well understood, and the responsible application of geologic information in land-use planning has been shown to reduce the impact of these hazards.

Among the Utah geologists working to spread accurate and reliable geologic information throughout the state is Dr. Steve D. Bowman, manager of the Geologic Hazards Program of the Utah Geological Survey (UGS). The UGS is a non-regulatory, Earth science research agency within the Utah Department of Natural Resources whose mission is to provide timely scientific information about Utah’s geologic environment, resources, and hazards.

“Utah is a geologically active and diverse state,” Bowman says. “Geologic hazards of one type or another affect its entire area.” As a result, he spends much of his time providing technical outreach and assistance to people throughout the state.

“With land-use in Utah regulated at the local level, each community needs to adopt strong geologic hazard ordinances to effectively deal with these hazards,” Bowman says. “By understanding the hazards, where they exist and in what severity, society can learn to better manage them.”

, the UGS created an interactive three-dimensional (3D) visualization of the Magna earthquake using a geographic information system (GIS) data set that represented the main shock and subsequent aftershocks.
Image Caption

On the day of the Magna earthquake, the UGS created an interactive three-dimensional (3D) visualization of the Magna earthquake using a geographic information system (GIS) data set that represented the main shock and subsequent aftershocks. See the visualization online on the UGS website.

To help foster that understanding of Utah’s geologic hazards, along with the state’s efforts to respond to and learn from them, Bowman and his colleagues in the Geologic Hazards Program work to provide Utah’s citizens with the sound scientific information they need to make informed decisions regarding the risks geologic hazards pose.

For example, following the Magna earthquake, Bowman and his colleagues in the Geologic Hazards Program worked to provide emergency managers, first responders, the media, and members of the public with accurate scientific information about the earthquake; collaborated with the University of Utah Seismograph Stations and other entities to identify the fault or faults that caused the earthquake and subsequent aftershocks; and sent out field teams to collect data that might give scientists a better understanding of the structure of the Salt Lake Valley’s subsurface geology. They also provided engineers and materials science researchers with data collected during and after the event to aid investigations of building codes, materials, and construction methods. All of this information can help Utahans prepare for and possibly reduce the impact of future earthquakes.

“The recent Magna earthquake is a reminder that Utah is seismically active and that damaging earthquakes do occur,” write the Geologic Hazard Program staff at the close of an article about the Geologic Hazard Programs response in the UGS publication Survey Notes. “Even with the recent stress relief of the Magna earthquake, enough seismic energy has built up along the Wasatch fault zone that an earthquake up to about M 7.6 could occur at any time.”

In addition to helping Utah citizens prepare for and mitigate the effects of geologic hazards, Bowman also works to locate and map geologic hazards on the landscape. Bowman is currently working to complete the Utah Aerial Imagery Database, a new web-based application to replace the UGS’s 13-year-old legacy web application, the UGS Aerial Imagery Collection. The new database contains aerial photography in the Utah area of interest (i.e., the state of Utah, plus a 0.2-degree buffer) dating from 1935 to 2020. The collection includes more than 150,000 individual photographs, 96,000 of which have been digitized and are now available online. Associated index sheets, orthophotomaps (i.e., aerial photographs geometrically corrected so the scale is uniform), camera calibration reports, and other materials are also available, along with more than 237,000 images from the U.S. Geological Survey EarthExplorer system.

This table shows the different wavelengths of SAR, which are often referred to as bands and given a letter designation, such as X, C, L, and P. Each band is associated with a frequency, wavelength, and the application typical for that band.
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This table shows the different wavelengths of SAR, which are often referred to as bands and given a letter designation, such as X, C, L, and P. Each band is associated with a frequency, wavelength, and the application typical for that band.

“Historical aerial imagery is integral to nearly all our geologic hazard and geologic mapping projects, particularly in urbanized areas, where the ground surface is often obscured or extensively modified,” Bowman said. “This data is also extensively used by the engineering and environmental consulting community and the public.”

Remotely sensed data are important to Bowman’s work too. Satellite imagery, lidar (an acronym for Light Detection and Ranging, laser-based radar), and Synthetic Aperture Radar (or SAR) all play a role in the detection and mapping of geologic hazards. SAR in particular is, in Bowman’s words, “well-suited to detecting and monitoring ground deformation” and can be useful in investigations of large, complex landslides, land subsidence, and earth fissures.

Whereas optical imagery from aircraft and satellites is akin to taking a photo of Earth’s surface from above, and lidar uses the light in the form of a pulsed laser to measure ranges or variable distances to Earth, SAR sensors bounce microwave radar signals off target areas on Earth’s surface, measuring the time it takes the signal to travel there and back. Further, unlike optical technology, SAR sensors do not require reflected light to “see,” so they can obtain measurements in darkness. And unlike both reflected imagery and lidar, SAR signals can penetrate clouds and rain, enabling it to detect alterations of Earth’s surface despite the weather.

The secret of SAR’s geologic hazard detecting success lies in the variability of its wavelengths. Radar sensors use wavelengths at the centimeter scale. These different wavelengths are often referred to as bands and are given letter designations (e.g., X, C, L, etc.) and which one is used determines how the signal will interact with an object. For example, whereas an X-band SAR signal, which operates at a wavelength of 2.4 to 3.8 centimeters, offers only slight penetration of vegetation, an L-band SAR signal, which ranges from 15 to 30 cm, can shallowly penetrate Earth’s surface in certain soils, making it ideal for use in geophysical monitoring.

This interferogram from Sentinel-1 SAR data acquired on 2/5 and 2/17/2018 shows earthquake fault slip on a subduction thrust fault causing up to 40 cm of uplift of the ground surface. The motion has been contoured with 9 cm color contours, also known as fringes. Credit: NASA Disasters Program
Image Caption

This interferogram from Sentinel-1 SAR data acquired on 2/5 and 2/17/2018 shows earthquake fault slip on a subduction thrust fault causing up to 40 cm of uplift of the ground surface. The motion has been contoured with 9 cm color contours, also known as fringes. Credit: NASA Disasters Program.

Further, SAR’s ability to penetrate to the ground surface allows researchers to take advantage of an additional method of detecting geologic change known as Interferometric synthetic aperture radar (or InSAR). InSAR uses two SAR images of the same area acquired at different times to produce a map called an interferogram. If the ground has moved away from (subsidence) or toward (uplift) the satellite between the times the two images were obtained, a slightly different amount of the wavelength is reflected back to the sensor. This difference results in a measurable phase shift that is proportional to displacement on the surface. The resulting map of these displacements — the interferogram — uses a repeating color scale to show the amount of displacement between the first and the second acquisition. The line-of-sight direction of displacement, be it subsidence or uplift, is indicated by the color scale fringe sequence from the edge(s) toward the center of a deformed feature on the land.

Given the importance of InSAR data to his work, Bowman regularly uses of datasets from NASA’s Alaska Satellite Facility Distributed Active Archive Center (ASF DAAC), which specializes in the acquisition, processing, archiving, and distribution of SAR data, tools, and resources for NASA’s Earth Observing System Data and Information System (EOSDIS). ASF DAAC’s SAR datasets originate from sensors on several satellite missions, including the European Space Agency’s (ESA) Sentinel-1, ERS-1 and -2, and ENVISAT satellites; the Japan Aerospace Exploration Agency’s Japanese Earth Resources Satellite (JERS) and Advanced Land Observing Satellite (ALOS)-1 and -2 satellites; the Canadian Space Agency’s RADARSAT-1 satellite; and NASA’s Soil Moisture Active Passive (SMAP) and Seasat satellites. ASF DAAC also acquires SAR data from the Spaceborne Imaging Radar-C (SIR-C), which flew aboard NASA’s Space Shuttle Endeavor, and NASA’s Airborne SAR (AIRSAR) and Uninhabited Aerial Vehicle SAR (UAVSAR) aircraft.

This InSAR image of data from Sentinel 1A shows levels of ground subsidence in southwestern Utah between April 22, 2015 and August 2016. Credit: Alaska Satellite Facility. Image courtesy of Utah Geological Survey
Image Caption

This InSAR image of data from Sentinel 1A shows levels of ground subsidence in southwestern Utah between April 22, 2015 and August 2016. Credit: Alaska Satellite Facility. Image courtesy of Utah Geological Survey.

Differential InSAR has been used to detect and monitor ground subsidence throughout the Intermountain West and, as Bowman writes in Guidelines, “SAR data suitable for use in differential interferometric processing is available for many areas of Utah from the ERS-1 and -2, ENVISAT, and ALOS-1 and -2 satellites.”

As Bowman writes in Guidelines for Investigating Geologic Hazards and Preparing Engineering- Geology Reports, with a Suggested Approach to Geologic-Hazard Ordinances in Utah, a publication he co-edited along with his Geologic Hazard Program colleague William Lund, there are two types of interferometry: differential and topographic. Differential InSAR measures small-scale ground displacements due to subsidence, earthquakes, glacier movements, landslides, and other ground movement with the effects of topography removed. Conversely, Topographic InSAR measures ground topography with no ground displacement, resulting in a digital elevation model.

Given the increasing availability of InSAR data, the technology has become a valuable tool for investigating geologic hazards and, its use (along with lidar) in land-subsidence and earth-fissure investigations has become, in Bowman’s words, “the state of practice.”

“InSAR’s chief advantage for subsidence monitoring is that it offers an accurate, rapid and cost-efficient way to determine the horizontal and vertical extent of land subsidence and subsidence rate variability over a large area to an accuracy of about 1 centimeter,” he says.

Bowman’s assessment has been born-out by previous studies conducted in southwest Utah that showed how InSAR can be used to detect and measure long-term subsidence over large areas.

All of this leads Bowman to characterize InSAR as a useful and effective technology for researchers in the geologic hazard community.

“InSAR is a valuable, evolving tool for detecting, mapping, and understanding geologic hazards, particularly related to ground deformation, such as that caused by seismic deformation and groundwater-withdrawal- or mining-induced land subsidence,” he writes in the Guidelines. “Large surface areas can be covered with repeat coverages, allowing time-series analysis of deformation. InSAR has allowed the mapping of ground deformation at unprecedented levels of detail over large regional areas that was not possible previously using traditional methods.”

Further, given the time Bowman spends providing technical outreach and assistance to people throughout the state, any tool that can aid the understanding of geologic hazards is a benefit to his efforts. After all, as Bowman stated above, understanding these hazards is the first step toward helping Utahans better manage them.

Representative data products used or created:

Available through ASF DAAC:

Other Data Products Used:

*NASA’s provision of the complete ESA Sentinel-1 synthetic aperture radar (SAR) data archive through the ASF DAAC is by agreement between the U.S. State Department and the European Commission. Content on ASF’s Sentinel web pages is adapted from the ESA Sentinel-1 website.

Read about the Research:

Bowman, S.D. & Lund, W.R., editors (2020). Guidelines for investigating geologic hazards and preparing engineering-geology reports with a suggested approach to geologic-hazard ordinances in Utah, Second Edition: Utah Geological Survey Circular 128, 170 p. + appendices. Available online (PDF).

Bowman, S.D. & Geologic Hazards Program (2020). The UGS response to the March 18, 2020, magnitude 5.7 Magna, Utah, earthquake and aftershock sequence. Utah Geological Survey, Survey Notes, 52(3): 1-5. Available online (PDF).

Kleber, E.J., Hiscock, A.I., McKean, A.P., Hylland, M.D., Hardwick, C.L., McDonald, G.N., Castleton, J.J., Bowman, S.D., Erickson, B.A., Willis, G.C., Anderson, Z.W., & Clark, D.L. (2020). Geologic setting, ground effects, and proposed structural model for the March 2020 M 5.7 Magna earthquake sequence. Seismological Research Letters, 92(2A): 710-724. doi:10.1785/0220200331

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