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…
Telemetry Analysis Learning Algorithm (TALA)
Applies machine learning to analyze operational data from agency-managed systems to support maintenance and reliability objectives.
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…
Machine learning in remote sensing-based wildfire and natural resource risk assessments
Predict the risks of wildfire, drought, and invasive species spread on assets of value to the American public
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
Automating the Detection and Classification of Wildlife in Aerial Imagery [2024 INV#WO0000000109409]
The tools and workflows developed by this project will be used by the Bureau of Ocean Energy Management (BOEM) to assess wildlife populations as part of planning and monitoring fo…
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.
Flor-AI: Developing a Remotely Sensed Image Classification Method for Inventory and Monitoring of Flora in Digital UAS Imagery
This project supports the management of oak-pine barrens on the Necedah National Wildlife Refuge, Wisconsin. Necedah NWR staff conduct habitat management actions (prescribed burni…
U.S. Wind Turbine Database
Capture of geographic location of wind turbines from high resolution satellite imagery with object detection pipelines vs manual methods
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…
Integrate High-resolution Satellite Remote Sensing Data with Automated Machine Learning Techniques to Enhance Water Quality Assessment
understanding water quality in the Mississippi River using available data
Estimates of Habitat Suitability of Reed Canarygrass (Phalaris arundinacea) in Upper Mississippi River Floodplain Forest Understories
A better understanding of where in the Upper Mississippi River floodplain and invasive grass may occur.
Detecting and tracking reed canarygrass (Phalaris arundinacea) invasion in the Upper Mississippi River floodplain using remote sensing and artifial intelegence.
We have a limited understanding of how the distribution of an invasive grass has changed over time. We seek to use satellite imagery to identify and track annual changes in the di…
Developing land cover maps for barrier islands using satellite imagery
The objective of this ML/AL use case was to map land cover on barrier islands using satellite imagery.
Reducing elevation error in coastal wetland digital elevation models
The objective of this use case was to train/deploy a random forest regression model to reduce elevation error in a coastal wetland digital elevation model.