An integrated sensor network and data driven approach to satellite remote sensing of Dissolved Organic Matter
AI leverages the very large water quality dataset from extensive existing in situ data at continuous monitoring stations to develop a remote sensing model with improved accuracy f…
Machine Learning for automatic fracture mapping and rock identification [2024 INV#WO0000000109499]
Machine learning algorithms are being used to improve detection and characterization of fault surface geometries using the spatial patterns of earthquake locations. We have improv…
PRObability of Streamflow PERmanence (PROSPER models) [2024 INV#WO0000000109074]
predictions of reliable surface flow in streams at regional scales to inform land and water resource decisions related to water availability.
Remote sensing of particulate and filter passing mercury species: models and proxies
AI provides the framework for understanding the relationship between optical water quality parameters and non-optical contaminants to develop highly accurate remote sensing models…
HOTLink: identifying elevated thermal anomalies at volcanoes [2024 INV#WO0000000109217]
Moves beyond threshold-based hotspot detection algorithms using computer vision and CNN for improved detection of weka thermal signals that may be the first indiciation of volcani…
Tephra classification with machine learning [2024 INV#WO0000000109095]
Layers of volcanic ash can be classified using a their geochemical components to link a the ash to the volcano it erupted from.
use of random forest for species distribution modeling
We use random forest models in R as part of an ensemble species distribution modelling workflow. Random forests have been applied to model the distribution of Joshua trees, as wel…
Determining the resource potential of critical minerals in seafloor massive sulfide deposits [2024 INV#WO0000000109311]
The system predicts the location of seafloor massive sulfide deposits for use as critical mineral indicators. Produces associated mapping products for public use.
Mapping ecohydrological headwater refugia
This application of machine learning is being used to aggregate complex spatial data to develop a statistical model used to create detailed maps of headwater stream resources and…
Tsunami Hazard Analysis [2024 INV#WO0000000108470]
Improve onshore probabilistic inundation forecasts
Machine Learning based shoreline detection and sea ice dynamics using coastal cameras [2024 INV#WO0000000108008]
Determine shoreline location and change as well as sea ice dynamics from coastal cameras in remote communities
Machine learning for streamflow forecasting [2024 INV#WO0000000109317]
Improve streamflow forecasting predictions in the Willamette River basin.
Machine Learning for Bat Acoustics
Improving the accuracy and timeliness of species status assessments and science to support deregulation efforts.
CHS Q Business AI Assistant (theKraken)
The AI Assistant is designed to address the challenge of quickly finding and using information spread across multiple platforms like GitLab and Confluence. Instead of employees sp…
Rangeland Condition Monitoring Assessment and Projection (RCMAP) [2024 INV#WO0000000107126]
To address the need for long-term tracking of vegetation change, scientists from the USGS and Bureau of Land Management (BLM) developed the Rangeland Condition Monitoring Assessme…
Foundation Models to Advance Earth Science [2024 INV#WO0000000107153]
Advance the understanding of Earth's conditions and processes by developing and deploying generalist AI models (Foundation Models) trained on Earth Observations from field, suborb…
Seabird and Marine Mammal Surveys Near Potential Renewable Energy Sites Offshore Central and Southern California [2024 INV#WO0000000107535]
Using rapidly developing machine- learning (ML) techniques, the USGS WERC team is developing new methods to automate the detection and counts of seabirds and marine mammals from d…
Data-driven approaches to filling missing time-series data within the San Francisco Bay-Delta [2024 INV#WO0000000107683; INV#WO0000000107488]
Environmental time-series data may suffer from gaps at a variety of time scales, significantly reducing the number of observations to understand phenomena, identify change, calibr…
Deep Learning based image segmentation [2024 INV#WO0000000107975]
Machine Learning based shoreline detection and mapping, automated data suitability analyses from satellite imagery
Using Machine Learning in USGS StreamStats to make suspended sediment and bedload predictions [2024 INV#WO0000000107977]
Getting estimates of suspended sediment and bedload in Minnesota rivers without sampling data.
National Oceanographic Partnership Program (NOPP) [2024 INV#WO0000000108018]
Machine Learning based coastal sediments assessment and prediction
Machine learning based shoreline time-series imputation, classification and forecasting (time-series analyses) [2024 INV#WO0000000108117]
data generation and QC/QA procedures, for large scale and short-term forecasting of shoreline trends
Sediment Transport in Coastal Environments [2024 INV#WO0000000108118]
time-series imputation of oceanographic time-series
National Wildlife Disease Database (NWDD) [2024 INV#WO0000000108149; 2024 INV#WO0000000109192]
bring together various wildlife health data streams across informational domains (i.e., laboratory results, environmental observations, news media, etc.)