Geology ReportsSearch

USGS · 70218289

Amateur radio operators help fill earthquake donut holes

Abstract

If you’ve ever seen tall antennas rising from everyday residences in your community and wondered what they are for, it could be that those homes belong to ham radio enthusiasts who enjoy communicating with each other over the airwaves. In addition to having fun with their radios and finding camaraderie, many ham radio operators are also prepared to help neighbors and authorities communicate during disasters. One such group of radio enthusiasts is poised now to serve yet another important role: They will be contributing to a more robust delivery mechanism for critical seismic intensity reports after major earthquakes through the U.S. Geological Survey’s (USGS) Did You Feel It? (DYFI) system.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 40.60144147645398° to 40.90936126702326° latitude; -112.1099853515625° to -111.6925048828125° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

David J. Wald, Vince Quitoriano, Oliver Dully. 2021. Amateur radio operators help fill earthquake donut holes. https://doi.org/10.1029/2021eo155013

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

How to accelerate advances in ecological forecasting

Ecological forecasting offers critical insights for managing natural resources and safeguarding public well-being. Despite growing demand for these forecasts, progress is hindered by fragmented systems, redundant workflows, and limited interoperability. Drawing lessons from weather forecasting and recent successes like the NEON Ecological Forecasting Challenge, shared cyberinfrastructure is important for advancing ecological prediction. By adopting common standards, open-source tools, and scalable architectures, and fostering transdisciplinary collaboration, the ecological forecasting community can overcome technical and institutional barriers. Such investments could accelerate scientific understanding, improve forecast reliability, and empower decisionmakers to anticipate environmental change and respond effectively.

Eos, American Geophysical Union

A hybrid approach for revealing headwater hydrology

Coordinated work to compile existing data and apply models pairing physical understanding with machine learning could substantially improve streamflow predictions for little-known headwater basins.

Eos, American Geophysical Union

Planting seeds for thriving data management

The volumes and varieties of data coming from all types of scientific instrumentation around the globe and beyond are rapidly growing. To reuse and capitalize on these data effectively, scientists must be able to share and access them efficiently, which requires the data to be well managed. Many scientists intuit that research data management (RDM) done well does not mean using dusty USB drives or aging laptops for storage. Yet the path to strong data management is not always clear. How is RDM done? Who does it? For science to advance, we need to bolster cyberinfrastructure and human capacity to ensure that the data being collected are reusable by both humans and machines.

Eos, American Geophysical Union