USGS Awarded Grants for Landslide Mapping
Federal funding supports 16 local governments in building hazard databases using lidar and machine learning.
Updated on Sept. 24, 2026 in Geography
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In September 2026, the U.S. Geological Survey (USGS) awarded $1 million to 16 state, local, and tribal governments for landslide mapping initiatives. This funding aims to accelerate the creation of digital hazard infrastructure across the United States.
Why it matters
These grants establish the essential baseline data required for disaster mitigation in regions where millions of residents face potential geological instability. Mapping projects enable local authorities to quantify landslide susceptibility and secure future resources for protective infrastructure.
A University of Washington database launched in July 2026 identified 6.5 million Americans living in landslide-risk areas. Current projects leverage lidar—a remote sensing method using light pulses to map surface topography—to delineate features for hazard modeling.
The players
U.S. Geological Survey
A federal bureau providing scientific data on natural hazards, ecosystems, and climate impacts.
University of Washington
A research institution focused on data-driven geological monitoring and hazard modeling.
The details
Recipients are integrating high-resolution lidar data with machine-learning algorithms to automatically detect landslide signatures. By analyzing topographic features, these models can identify both shallow and deep-seated movements that are often difficult to map manually. Pennsylvania, for instance, is using this process to build a comprehensive landslide database for Washington County, while Nevada is developing its first statewide inventory.
Timeline
2020: Pennsylvania collected initial lidar data for Washington County.
July 2026: The University of Washington launched a nationwide landslide-risk database.
September 2026: The USGS awarded $1 million in landslide project grants.
The Tech Race
This program aligns with the ongoing expansion of the University of Washington's nationwide landslide database, which recently highlighted the scale of geological risks across the country. Governments are now racing to build local datasets that integrate with these national modeling frameworks.
Residents in target areas like Washington County, Pennsylvania, will see the results of these mapping projects as states release public dashboards for hazard inventory information. These resources will eventually provide homeowners and planners with localized landslide susceptibility data.
The takeaway
Quantifiable hazard data is the primary barrier to effective disaster mitigation and federal resource allocation. Watch the status of the two-year Pennsylvania initiative as it serves as a pilot for incorporating machine learning into state-level geological safety standards.
Further reading
For broader trends in mapping and topography, see the Geography section.
Source note: This article includes information reported by StateScoop.
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