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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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1,687 records · Page 74Linked to original sources

USGS2025

Slow rupture, long rise times, and multi-fault geometry: The 2020 M6.4 southwestern Puerto Rico mainshock

The M 6.4 mainshock of the southwestern Puerto Rico seismic sequence on 7 January 2020, was one of the most impactful modern earthquakes in the northeastern Caribbean. Due to its offshore location and complex aftershock distribution, its source kinematics remain poorly constrained. This active sequence illuminated a complex set of previously unrecognized structures that indicate multiple causative faults may have slipped during its rupture. Here, we utilize seismic and geodetic observations to enhance model resolution, estimate the finite slip of the mainshock, and test a multi-segment, geologically realistic fault geometry. Our refined model finds a lower rupture velocity and longer rise times than typical for an event of this magnitude. This indicates a slow-evolving rupture process that resembles characteristics of a tsunami earthquake. Although this normal/strike-slip faulting event was not tsunamigenic, these qualities, if pervasive for this region, have important implications for future seismic monitoring and hazards in southwestern Puerto Rico.

Puerto Rico↗

USGS2024

Earthquake-triggered ground-failure inventory associated with the M7.1 2018 Southcentral Alaska earthquake

The 30 November 2018, magnitude (Mw) 7.1 earthquake in Southcentral Alaska triggered substantial landslides, liquefaction, and ground cracking throughout the region, resulting in widespread geotechnical damage to buildings and infrastructure. Despite a challenging reconnaissance and remote-sensing environment, we constructed a detailed digital inventory of ground failure associated with the event from several sources. Sources included information derived from remotely sensed data, and data compiled from literature, social media postings, and earthquake damage information compiled by local, state, and federal agencies. Each instance of ground failure within the inventory contains information on the location and type of observed ground failure, and the methods and data used to document the occurrence. Where high-quality data, such as LIDAR or satellite imagery, were available and showed the ground-failure instance clearly, the extent is mapped as a polygon or polyline. All other locations are mapped as points. There are a total of 886 ground-failure instances documented within the inventory (400 landslides, 286 liquefaction features, and 200 features unattributed to specific processes). A semi-quantitative confidence scheme is used to describe mapping certainty associated with each ground-failure feature. This inventory represents a relatively moderate ground-failure-triggering event that occurred in a subarctic environment. This data paper describes the content within the inventory, the inventory data collection procedures, and limitations of the data. Events of this type are not often documented in detail; thus, adding the inventory data to the US Geological Survey Open Repository of Earthquake-Triggered Ground-Failure Inventories further diversifies the datasets available to the scientific community to be used to better understand and model earthquake-triggered ground failure.

Alaska↗

USGS2025

Metal fingerprints of Eocene rhyolite magmas coincident with Carlin-type gold deposition in Nevada USA

Eocene magmatic systems contemporaneous with world-class Carlin-type Au deposits in Nevada (USA) have been proposed by some researchers as a key ingredient for Au mineralization, though evidence conclusively demonstrating their genetic relationship remains tenuous. This study provides the first direct evidence of the pre-eruptive metal budget of volatile- and metal-charged silicic magmas coincident in time (~41 to 34 Ma) and space (within 5 km) with Carlin-type Au deposits. We characterize the pre-eruptive metal fingerprints of these diverse magmatic systems to assess their potential as sources of metals for Carlin-type Au mineralization. Metal abundances from quartz-hosted melt inclusions (Au, Te, Ag, Sb, Tl, Mo, W, Sn, As, Pb, Co, Cu, Ni, and Zn) characterized in situ by SHRIMP-RG and LA-ICP-MS represent our best (and only) estimates for the pre-eruptive metal budget in these systems. Median metal concentrations are generally within one order of magnitude of average upper crust and average continental rhyolite values. But there are two notable exceptions, with median Au contents extending >1 order of magnitude higher than average upper crust and median Cu contents ranging >1 order of magnitude lower than upper crust. Despite this, melts contain lower Au/Cu (<0.1), Au/Ag (<5), and Au/Tl (<0.3) than most ore-grade Carlin-type rock samples and quartz-hosted fluid inclusions, regardless of their age and timing relative to nearby Carlin-type Au mineralization. The metal fingerprints of these magmatic systems, de-fined both by traditional and multivariate compositional data analysis techniques, are distinct from one another. Yet none are particularly specialized, e.g., high Au/Cu, in terms of being ideal ingredients as postulated by magmatic models for Carlin-type Au mineralization. Magmatic Au contents do not appear to be correlated with rhyolite “flavors” in the way that Cu, Sn, and Nb contents are. Fluid/melt partitioning modeling and magma volume estimates support the idea that a diverse array of non-specialized silicic magmas could feasibly contribute some or potentially all of the Au, Ag, and Cu in Carlin-type systems. The compositional diversity among contemporaneous magmatic systems could possibly contribute to some of the diversity observed across Carlin-type Au districts in Nevada.

Nevada↗

USGS2026

Site response models based on geometric parameters for southern California sedimentary basins

Site response in sedimentary basins is influenced by complex three-dimensional (3D) features, including trapping of seismic waves, focusing of seismic energy and basin resonance. Current ground motion models (GMMs) incorporate basin effects using one-dimensional parameters like V S30 and shear wave velocity isosurface depths, which are limited in capturing lateral and 3D effects. To address these limitations, we develop seismic site response models based on novel parameters that represent multi-dimensional properties of the Los Angeles Basin (LAB) geometry and shear wave velocity. We define a basin shape for the LAB using depth to subsurface geologic interfaces associated with the oldest sedimentary deposits (depth to a particular shear wave velocity horizon, i.e., 1.5 km/s - z 1.5 ) and the depth to the crystalline basement ( z cb ) which are determined using geologic cross sections and community seismic velocity model profiles. We explore a suite of geometric descriptors computed for the LAB and southern California, from which three parameters with the greatest predictive potential are selected and evaluated using empirical ground motion residual analyses in combination with the Boore et al. GMM. The results demonstrate that the zonal heterogeneity index ( ), standard deviation of the absolute difference between z 1.5 and z cb ( ) and standard deviation of z cb ( ) each provide a reduction in site-to-site variability ( ϕ S2S ) of empirical GMMs. The reduction in ϕ S2S is period-dependent, with average decreases of 3%, 26% and 6% for , , and , respectively. Although these reductions are modest from an engineering application perspective, they are statistically significant, underscoring the inherent difficulty in fully characterising complex basin effects. Collectively, these findings indicate that the inclusion of basin-specific geometric parameters yields measurable, albeit incremental, improvements in site response prediction and establishes a framework for the progressive refinement of seismic hazard characterisation within sedimentary basins.

California↗

USGS2025

Simulation of groundwater flow in Wake County, North Carolina, 2000 through 2070

In 2019, the U.S. Geological Survey and Wake County Environmental Services began a collaborative study to evaluate groundwater resources and long-term groundwater availability in the county’s fractured-rock groundwater system. Wake County, in central North Carolina, is experiencing rapid population growth, associated land development, and changing water use. Hydrogeologic data including groundwater levels, aquifer testing, borehole fracture flow measurements, water-quality samples, and groundwater age-dating tracers were collected, along with findings from previous investigations, to help inform a conceptual model of the flow system used to develop a modular three-dimensional finite-difference groundwater-flow model (MODFLOW) for simulating historical and future groundwater conditions from 2000 to 2070. Hydraulic conductivity and transmissivity ranges were estimated from 17 slug tests and 21 borehole-flow measurements. Groundwater-quality analytical results from 19 sampling sites indicate that oxidation-reduction (redox) conditions varied within the regolith and bedrock and that minimal evaporation occurred before recharge entered the groundwater system. Age dating revealed mixtures of older and younger water, ranging from the 1940s to the 1990s—indicating variable flow pathways of recharge within permeable bedrock fracture zones. To simplify the complex fractured-rock groundwater system, two layers representing the regolith and the fractured bedrock were used in the MODFLOW model. Model calibration included parameter estimation and provided a reasonable fit to observed groundwater levels and estimated stream base flows. The model forecast scenarios incorporated future climate-model data for two emissions scenarios with land cover change projections to simulate potential impacts to future groundwater levels, recharge, and base flows. Recharge and base flow projections were largely within historical ranges, with no apparent long-term trends, but did indicate a slight downward shift in median values—likely, in part, because of differences in spatial resolution of input climate datasets. Seasonal patterns were consistent with historical data, with projections of possible increases in future winter recharge. Model limitations are discussed, and additional monitoring and model refinement needs are highlighted to support decision making for local groundwater management.

North Carolina↗

USGS2024

Models no not provide proof: An example of model ambiguity and application of isotopic data in a mine pit lake

Geochemical and hydrologic models of pit lakes are commonly used in environmental regulatory decisions to predict future water quality and hydrologic conditions and to understand existing pit lakes. Models may be used to quantify sulfide oxidation, predict thermal/chemical stratification and mixing, and better understand connections between pit lakes and aquifers. One concern related to the hydrologic character of pit lakes is if they are terminal (a groundwater sink with no outflow) or flowthrough (both receiving groundwater inflow and discharging to groundwater). This question was pertinent to the Liberty pit lake, a small acidic pit lake formed in a former Cu deposit in south-central Nevada where potentiometric and geochemical data potentially indicate pit-lake outflow. Potential discharge to groundwater from the pit lake was evaluated using a water-balance model, but uncertainty in hydraulic parameters led to ambiguity in the hydrologic character. Stable isotopes of water were then sampled from the pit lake and adjacent groundwater wells, which unambiguously indicated the lack of an evaporative signature in downgradient groundwater because the groundwater did not plot on a hypothetical mixing line between evaporated pit lake water and observed meteoric recharge. This methodology provided a more effective and more data-driven approach for understanding pit-lake hydrology. Although predictive models are required to quantify reasonable bounds on future conditions, many models contain substantial uncertainty and are not well suited in some environments. Datasets that provide more clear lines of evidence could be collected from existing pit lakes whenever possible to inform water-rock interaction, limnological behavior, and connectivity to adjacent groundwater.

Nevada↗

USGS2025

Colored shaded-relief bathymetry and acoustic backscatter of Lake Sammamish, Washington

Evidence of strong earthquakes (such as underwater landslides and associated deposits) may be recorded within the lacustrine sediments of Pacific Northwest lakes. The floor of Lake Sammamish, Wash., an approximately 11 kilometer (6.8 mile) long, 2 kilometer (1.2 mile) wide, and 35 meter (114.8 feet) deep lake located in a populated region just east of Seattle, was mapped by the U.S. Geological Survey in November of 2021 to search for evidence of past earthquakes. Mapping was conducted using a SWATHplus-M 234-kHz interferometric side-scan sonar system was pole-mounted on the U.S. Geological Survey research vessel Parke Snavely, and the system collected full-coverage bathymetric and acoustic backscatter data, which were processed to 2-meter spatial resolution. Two maps were created, a colored shaded-relief bathymetric map showing lake floor morphology (sheet 1), and an acoustic-backscatter map showing backscatter intensities (sheet 2). The results may then be utilized together to investigate past earthquake activity.

Washington↗

USGS2026

A practical decision tool for marine bird mortality assessments

Given the rise in anthropogenic, environmental, and disease events contributing to marine bird mortality, there is a critical need to improve the rigor of mortality assessments. Deficits in data collection and mortality estimation can hinder a manager’s ability to document the scale of events and assess population level impacts. Therefore, to inform decisions required during activities, such as conservation status assessments or harvest management, organizations may choose to incorporate mortality assessments into response plans. Resources, capacity, and assets to assess mortality vary across jurisdictions (federal, state, Indigenous, local, etc.), and clear guidance to support mortality assessments is often unavailable or not clearly addressed. Here, we present a decision support tool to help managers identify and evaluate survey options to assess bird mortality in a diverse array of scenarios. The objective of the decision tool is to improve data collection and availability, which will increase the ability to estimate mortality robustly, given situation-specific attributes and constraints. This decision tool is designed to guide the response when a mortality event is initially encountered and offers suggestions for assessment and reporting procedures in the absence of other guidance or to complement existing protocols. The decision tool is also meant to inform decision making for response determination and resource allocation. The tool facilitates examination of options for further assessment and monitoring, which users determine by examining questions pertaining to species prioritization, determination of mortality minimum spatial extent, and the potential magnitude of impacts on affected species. Finally, identification of appropriate survey methods that address imperfect detection when a complete census is not possible are determined by exploring location, spatial and temporal extent, and the type of species affected. Ultimately, this decision tool aims to facilitate and improve the standardization of mortality assessments, equipping managers with a practical resource to navigate the decision-making process for marine bird mortality estimation.

Ornithological Applications↗

USGS2024

The U.S. Geological Survey National Water Quality Network—Groundwater—2023

conterminous United States↗

USGS2025

Landsliding follows signatures of wildfire history and vegetative regrowth in a steep coastal shrubland

Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km 2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.

California↗

USGS2025

The U.S. Geological Survey National Water Quality Network—Groundwater, 2024

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, 8 of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,089 wells in the network. All wells are sampled for physical properties, nutrients, major ions, trace elements, per- and polyfluoroalkyl substances (PFAS), and a subset of wells are sampled for pesticides, volatile organic compounds, radionuclides, and microbiological contaminants.

Contiguous United States↗

USGS2024

Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams

Headwater stream temperature often exhibits spatial variation at the kilometer-scale, but the relative importance of the underlying hydrogeological processes and riverine perturbations remains poorly understood. In this study, we investigated the relative importance of groundwater (GW) and other processes on downstream annual stream temperature signal characteristics using deterministic heat budget model (HFLUX) scenarios within an idealized stream reach representative of mountainous forested conditions. We summarized annual stream thermal regimes from the relationship of paired sinusoidal air and water temperature signals (amplitude ratio, phase lag, and mean ratio). Results showed that downstream changes in annual temperature depended on the thermal gradient between water and the hypothetical equilibrium temperature (where all heat fluxes sum to zero). GW inflow, riparian shading, and the boundary input signal were the most significant factors affecting downstream annual water temperature signals, while flow volume and channel dimensions impacted how quickly annual temperature signals changed. Effects of GW were dominated by advective rather than conductive heat exchange processes, but conduction played a larger role when GW input was more spatially diffuse. Our results indicated several mechanisms by which local processes may affect stream thermal resilience to disturbances and can help guide management of wildfire and climate change.

Journal of Hydrology↗

USGS2024

Post-wildfire debris flows

Post-wildfire debris flows pose severe hazards to communities and infrastructure near and within recently burned mountainous terrain. Intense heat of wildfires changes the runoff characteristics of a watershed by combusting the vegetative canopy, litter, and duff, introducing ash into the soil and creating water repellant soils. Following wildfire, rainfall on bare ground is less able to infiltrate into the fire-altered soils and overland flow is less impeded by vegetation. Rainfall runoff in recently burned areas can erode hillslopes owing to the removal of soil binding organic matter near the soil surface by fire. In channels, loose, dry-ravel deposits composed of sand and gravel are readily entrained by concentrated runoff in channels. Entrainment of soil on hillslopes and in channels bulks up the sediment concentration of the rainfall runoff to generate debris flows capable of transporting boulders and large woody debris. Post-wildfire debris flows can be triggered by rainfall conditions that would typically produce little runoff during unburned conditions. The primary rainfall trigger for post-wildfire debris flows is high intensity rainfall during short duration convective rainstorms or periods of high rainfall intensity embedded within a long-duration frontal storm. Numerous observations of debris flows triggered by storms lasting less than an hour following periods of little to no rainfall indicate that antecedent rainfall is not a requirement for initiation of post-wildfire debris flows. Post-wildfire debris-flow hazard assessment entails estimating probability and magnitude of debris flows in the burned area, estimating debris-flow runout and intensity, and defining rainfall intensity-duration thresholds for debris-flow initiation. In the United States, probability and magnitude is estimated using empirically derived models largely based on data collected in southern California. The models provide maps to identify watersheds and drainage paths where post-wildfire hazards are most pronounced. Rainfall intensity-duration thresholds can be incorporated into flood hazard forecasting tools. Currently, work is underway to identify how to best implement debris-flow runout models in burned areas with efficiency and accuracy. Post-wildfire debris flows have been a long-recognized process in the Transverse Ranges of southern California; however, climate change is driving more frequent wildfires to burn more mountainous terrain throughout the western United States and worldwide. As a result, post-wildfire debris flows are becoming a more common threat in areas where they were once infrequent. As the threat of post-wildfire debris flow expands into new areas, evaluating the hazard becomes challenging because the degree to which wildfire increases debris-flow susceptibility varies from region to region. This chapter summarizes the knowledge to date for evaluating post-wildfire debris-flow susceptibility and hazard assessment. We summarize the characteristics of wildfire burn severity, topography, underlying soil and geology, and rainfall conditions that contribute to making a watershed most likely to produce post-wildfire debris flows. Methods for hazard assessment in the United States and other countries are summarized. We highlight knowledge gaps for how post-wildfire debris-flow susceptibility varies throughout the western United States and worldwide and identify research needs to improve hazard assessment methods in different geographies.

Book chapter↗

USGS2025

An unexplained tsunami: Was there megathrust slip during the 2020 Mw7.6 Sand Point, Alaska, earthquake?

On October 19, 2020, the M w 7.6 Sand Point earthquake struck south of the Shumagin Islands in Alaska. Moment tensors indicate the earthquake was primarily strike-slip, yet the event produced an enigmatic tsunami that was larger and more widespread than expected for an earthquake of that magnitude and mechanism. Using a suite of hydrodynamic, seismic, and geodetic modeling techniques, we explore plausible causes of the tsunami. We find that strike-slip models consistent with the moment tensor orientation cannot produce the observed tsunami. Hydrodynamic inversion of sea surface deformation from deep ocean and tide gauge data suggest seafloor deformation more closely matches a megathrust, rather than a strike-slip, source. Static slip inversions, using sea level and Global Navigation Satellite System data, allow for a portion of co-seismic megathrust slip that can explain tsunamigenesis. Combining all available geophysical datasets to model the kinematic rupture, we show that considerable, relatively slow, megathrust slip is allowable in the Shumagin segment, concurrent with strike-slip faulting. We hypothesize that the slow megathrust rupture does not contribute much seismic radiation allowing it to previously go unnoticed with traditional seismic monitoring.

Alaska↗

USGS2025

40Ar/39Ar geochronology supporting mineral resources research at USGS Denver

The 40 Ar/ 39 Ar geochronology method is used to date potassium-bearing rocks and minerals, based on the decay of 40 K to 40 Ar, which provides important temporal constraints for geological events. The USGS Denver Argon Geochronology Laboratory dates samples from a variety of projects, mainly in the USGS Mineral Resource Program and the National Cooperative Geologic Mapping Program, facilitating in-depth research into the timing of geological events and processes. Recent applications of this method include geochronological studies in the Yellow Pine district, revealing mineralization ages that range from 51 to 70 Ma, and investigations into the Bear Lodge alkaline complex, providing insights into the timing of REE carbonatite formation. Additionally, studies at Alunite Ridge highlight the method's potential for understanding concealed mineral deposits. Ongoing projects continue to leverage 40 Ar/ 39 Ar data to enhance understanding of geologic frameworks and mineral resources, underpinning its importance in modern geochronology and mineral resource assessment.

Conference Paper↗

USGS2025

Mapping eelgrass (Zostera marina) cover and biomass at Izembek Lagoon, Alaska, using in-situ field data and Sentinel-2 satellite imagery

The U.S. Geological Survey and the U.S. Fish and Wildlife Service have developed a three-tiered strategy for monitoring eelgrass ( Zostera marina ) beds at Izembek Lagoon, Alaska, that targets different spatial and temporal scales. The broadest-scale monitoring (tier-1) uses satellite imagery about every 5 years to delineate the spatial extent of eelgrass beds throughout the lagoon. This report describes the most recent (mid-2020s) tier-1 eelgrass monitoring at Izembek Lagoon. The monitoring effort began by canvasing all satellite imagery collected during summer, under clear daytime skies and at low-tide, since the last tier-1 effort in 2006. Two eelgrass maps of Izembek Lagoon were generated by first creating maps of spectrally unique classes from two Sentinel-2 satellite images collected on July 1, 2016, and August 14, 2020, then attributing those spectral classes with information about eelgrass conditions based on field data. Specifically, maps depicting various eelgrass metrics, such as percentage of cover and modeled biomass, were generated using summaries of the ground data that spatially intersected each spectral class. Comparisons of the 2016 and 2020 Sentinel-2 maps showing eelgrass distributional extent, as well as a 2006 Landsat map, indicated that areas where eelgrass presence may have declined during 2006–20 were most prevalent in the central part of Izembek Lagoon. More recently, during 2016-20, areas of possible biomass decline were more prevalent in the southern part of the lagoon. Monitoring eelgrass conditions at Izembek Lagoon with satellite imagery and concurrent ground data allows conditions to be compared over time, but the influences of tide levels, growing season phenology, and spatiotemporal co-registration accuracy should be considered when designing and interpreting change detection analyses.

Alaska↗

USGS1999

Effects of snowmobile use on snowpack chemistry in Yellowstone National Park, 1998

Snowmobile use in Yellowstone National Park has increased substantially in the past three decades. In areas of greatest snowmobile use, elevated levels of by-products of gasoline combustion such as ammonium and benzene have been detected in snowpack samples. Annual snowpacks and snow-covered roadways trap deposition from local and regional atmospheric emissions. Snowpack samples representing most of the winter precipitation were collected at about the time of maximum annual snow accumulation at a variety of locations in the park to observe effects of a range of snowmobile traffic levels. Concentrations of organic and inorganic compounds in snow samples from pairs of sites located directly in and off snow-packed roadways used by snowmobiles were compared to concentrations in samples collected at nearby off-road sites. Concentrations of ammonium were 2 to 5 times higher for the in-road snow compared to off-road snow for each pair of sites. Thus, concentrations decreased rapidly with distance from roadways. In addition, concentrations of ammonium, nitrate, sulfate, benzene, and toluene in snow were positively correlated with snowmobile use.

Wyoming↗

USGS2026

3D semantic mapping of surface geological features

Semantic mapping in 3D is fundamental to a wide range of geoscientific studies and applications, including geomorphology, hazard assessment, and environmental monitoring. However, automatically segmenting geological features from large-scale photogrammetric datasets remains a significant challenge. We present a methodology to address this gap. Using overlapping images collected over environments of interest, Structure-from-Motion (SfM) produces georeferenced point clouds and estimates camera poses. Existing large vision models, such as Segment Anything Model, segment objects in the images, generating pixel-segmentation associations. To produce pixel-point associations, we project the points back onto the camera image planes. As objects are independently segmented across multiple images with different perspectives, we develop a segmentation mosaicking algorithm to build probabilistic point-segmentation associations that combines the pixel-segmentation associations and pixel-point associations. Our methodology is validated using both synthetic data generated by Kubric and real-world UAV-SfM data. The implementation is designed to be compatible with existing SfM software, including Agisoft and OpenDroneMap, for photogrammetry mapping in geoscience studies. As a case study, we apply our method to the semantic mapping of precariously balanced rocks (PBRs), which provide upper-bound constraints on historical ground motion shaking intensity. To support object-level identification of PBRs, we additionally integrated Grounding DINO, enabling text-prompted segmentation of features of interest within UAV imagery. This case study demonstrates the effectiveness of our method in generating a 3D semantic map of PBRs, enabling spatial distribution of PBR fragility for earthquake hazard analysis.

Computers & Geosciences↗