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.
Patterns in the Landscape – Analyses of Cause and Effect
ML satellite image classification is being used to better map flooding and fire events/characteristics for more effect hazard management.
Diploid Detector/Triploid Tracker for Grass Carp
There are expected benefits from the ability to determine whether Grass Carp can reproduce (diploid, with two sets of chromosomes) and thus take over and damage an ecosystem, or w…
Frog vocalization recognition from digital recordings
Automated audio recorders make it easy to gather large amounts of digital audio recordings where frogs may be vocalizing. These recordings are too numerous to make it cost effecti…
Using deep learning to classify potential piping plover habitat along the Upper Missouri River
The U.S. Army Corps of Engineers is required to assess piping plover habitat on the Missouri River annually, per a Biological Opinion. We have been using classification tools to m…
Global food-and-water security-support analysis data (GFSAD) project [2024 INV#WO0000000107073]
1. Landsat-derived rainfed and irrigated area-product of Conterminous United States (LRIP30) 2. Landsat-derived global cropland extent product @ 30 m (LGCEP30) 3. Landsat-derived…
Fire Effects at Whiskeytown National Recreation Area and Lava Beds National Monument
We used random forests to predict the mortality class (live/dead) of lidar derived tree approximate objects and vegetation conditions.
Forest metrics at Redwood National and State Parks
We are developing a convolutional neural network in TensorFlow to predict the presence of treefall gaps based on Sentinel-2 imagery.
Lake Champlain Cyanobacteria Bloom modeling
Developing prediction for harmful algal bloom occurrence
Predicting post-fire tree mortality
We used random forests to select predictor variables for models of individual tree mortality following fire.