Effects of vehicle traffic on space use and road crossings of caribou in the Arctic [2024 INV#WO0000000110111]
Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated…
Water Use Model Development [2024 INV#WO0000000109669]
Estimate multiple categories of water use across the U.S.
Nutrient, Salinity, sediment, temperature, and drought model development
Simulate nutrients (phosphorus and nitrate), temperature, sediment, and salinity in streams across the U.S.
CONUS EcoFlows Planning & Prototype [2024 INV#WO0000000109732]
National-scale ecological-flow response models
Using advanced computing techniques for image-based monitoring [2024 INV#WO0000000109674]
Provide tools and methods for leveraging image-based monitoring and machine learning approaches for measuring surface water properties.
Using advanced computing techniques for mobile monitoring platforms [2024 INV#WO0000000109492]
Support the navigation and swarming capabilities of autonomous vehicle platforms for water monitoring
Water Time-Series Record Automation Framework development
Leverage AI/ML to streamline USGS time-series data processing workflows
Invasive Carp Harvest Predictive Model
identify where invasive carp are congregating in large numbers in the Mississippi River for targeted harvest
Automated power line extraction using deep learning
Provide a national, consistent, powerline dataset.
Mapping wood and wood hazards in the Willamette Basin, Oregon
Large wood in rivers pose hazards to people and infrastructure, particularly post wildfire. This work uses neural network models to map large wood in rivers from aerial imagery to…
Willamette Regional IWAAs, gradient boosted ML stream temperature modeling.
Improve model predictions of stream temperature across the basin over traditional methods.
DARPAs CriticalMAAS [2024 INV#WO0000000108419; WO0000000096527]
Identify patterns in the data, isolate those that correlate with known mineral deposits, and integrate these with other geospatial layers to generate a predictive map for guiding…
National Land Cover Database (NLCD) [2024 INV#WO0000000107887]
Characterization of the physical land cover is critical for managing the lands, waters, and resources of the United States. The National Land Cover Database (NLCD) is easily one o…
Evapotranspiration mapping and monitoring
Mapping evapotranspiration (ET) with remote sensing is essential because it provides a consistent, large-scale view of how water is being used across landscapes. In agriculture, E…
Invasive Grass Mapping
USGS mapping of invasive exotic annual grasses is critical because these species, such as cheatgrass, alter ecosystems by increasing the frequency and intensity of wildfires and o…
LANDFIRE
USGS EROS has provided the expertise and staff to conduct LANDFIRE mapping for over 20 years. LANDFIRE products provide the nationally consistent, high-quality vegetation and fue…
Pathogen identification in salmon
Ichthyophonus, the most ecological and economically important pathogen of wild marine fish, is hypothesized to be a major driver of premature mortality in Yukon River Chinook salm…
Automated photographic identification of Eastern box turtles
Matching photographs from a database of photos to determine capture history of individuals which can then be used in capture-recapture models to estimate population size and demog…
Automated identification of ducks from hunter-submitted photos using deep learning models
species identification of photographs of hunter-shot ducks for use in waterfowl harvest management
PFAS model of soils in the northeast
We are predicting PFAS concentrations in soil across the northeast region
ATLAS
Literature review and data compilation is the most time-consuming phase of the mineral resource assessment workflow (https://www.usgs.gov/media/images/usgs-mineral-resource-assess…
PFAS Groundwater Model
We are building a model (likely random forest or boosted regression tree) to predict PFAS concentrations in groundwater supplies in the US.
Submersed Aquatic Vegetation Vulnerability Evaluation Application (SAVVEA)
Aid understanding of aquatic ecosystem constraints for vegetation growth
Hydrologic predictions for the Upper Mississippi River System using a hybrid deep learning approach.
Utilize historical datasets of air temperature, precipitation, discharge, and water surface elevation to train a deep learning model to predict discharge and water surface elevati…