Case Study: A Remote Sensing Approach to Site Selection for an Urban Deployment of Nodal Seismometers

Delton A. Samuel, Heather A. Ford, & Joseph Byrnes

Submitted September 7, 2025, SCEC Contribution #14885, 2025 SCEC Annual Meeting Poster #TBD

Assessing seismic hazards is critical for mitigating loss of life and property damage. Though seismometers themselves have become more compact and simpler to deploy, distributing them in urban environments presents a separate set of logistical challenges. The design of an urban seismic array often relies on collaboration between local governments and communities to gain access to these sites. When siting, we must identify a suitable location, then obtain permission to install a seismometer. It is critical that a nodal seismometer, or “node,” is deployed where sufficient coupling to the surface can occur non-invasively. These logistical factors incur a significant time cost that increases with area, number of instruments, and array complexities. We offer a remote sensing solution, implemented in open-source QGIS, that optimizes the search for potential sites and spatial distribution when designing a passive source study. The motivation for this effort is to utilize the collected passive source seismic recordings to understand the Las Vegas, Nevada basin fault structure employing ambient noise tomographic methods and explore new denoising algorithms. We identify potential node sites based on the desired spacing and research interests sharing a common feature of interest (FOI). For this study, we define a FOI to be sparse, relatively healthy green vegetation in a desert urban environment where a cultural source of upkeep is likely. We associate these areas with an increased potential for collaboration with the community and gaining permission to install a seismometer for ~30 days. Using the RGB and infrared (IR) spectral bands obtained from the Sentinel-2 satellite, we can calculate the Normalized Difference Vegetation Index (NDVI). We extract a layer that classifies the pixels within the NDVI range of our FOIs for further post-processing. We perform a raster transversal to search and locate the classified pixels, logging the latitude and longitude at the centroid of each pixel. We set conditions where each potential station is randomly plotted on a pixel at least 3 km apart, with a 5 km² buffer, to increase acquisition opportunities and help maintain spacing. Between July 8th and 12th, 2025, we deployed 91 of 106 available seismometers with a three-team effort. We achieved an average spacing of ~4 km between the three nearest stations, with a minimum station spacing of ~1.6 km and a maximum station spacing of ~12 km, over an area of ~1200 km².

Key Words
Remote Sensing, Urban Seismology, Seismology, Array Design

Citation
Samuel, D. A., Ford, H. A., & Byrnes, J. (2025, 09). Case Study: A Remote Sensing Approach to Site Selection for an Urban Deployment of Nodal Seismometers. Poster Presentation at 2025 SCEC Annual Meeting.

Related Projects & Working Groups
Community Capability Building (CCB)