Inventorying landforms with convolutional neural networks [2024 INV#WO0000000108738; WO0000000109117]
efficiently identify and inventory these features landform features from LiDAR derived topographic data images
Zero shot segmentation to expedite Quaternary geologic mapping [2024 INV#WO0000000108739; 2024 INV#WO0000000109150]
The construction of detailed geologic maps requires a lot of manual GIS data input to outline the extent of interpreted geologic features.
Machine Learning Image Classification of Wetlands and Soil moisture [2024 INV#WO0000000108779]
inform land managers, planners, and researchers about historical and current changes to human and natural environments, focused on floods, droughts, and fires
Predicting PFAS occurrence in groundwater using machine learning [2024 INV#WO0000000108780]
predict PFAS occurrence in groundwater at the depths of drinking water supplies across the conterminous U.S.
Machine learning-based landscape feature classification using satellite and airborne imagery [2024 INV#WO0000000108791; 2024 INV#WO0000000108794]
need to increase the accuracy of habitat and land cover classifications
Improving accuracy and precision of sonar-based estimates of fish abundance [2024 INV#WO0000000108800]
Sonar-based estimates of fish abundance are prone to inaccuracies that can limit their utility
Predicting PFAS in shallow soils in northern New England [2024 INV#WO0000000108973]
predict PFAS in soils across Maine, New Hampshire, and Vermont
Whole-lake indexing of round goby abundances with photographic catch data [2024 INV#WO0000000109010]
quantify abundances of one of the most abundant prey fishes in the Great Lakes, an invasive species called Round Goby
Classifying GPS data to understand flight behavior of birds [2024 INV#WO0000000109015]
understand under what circumstances eagles are more likely to collide with wind turbines
Extracting robust, searchable data from narrative geologic descriptions [2024 INV#WO0000000109022]
Extracting robust, searchable data from narrative geologic descriptions
Environmental streamflows in the United States: historical patterns and predictions [2024 INV#WO0000000109075]
It is important that environmental streamflow assessments by water managers consider changes in climate, land use, and water management; this cannot be done effectively without un…
Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery [2024 INV#WO0000000109078]
delineate sub-surface agricultural drainage
Predicting inundation dynamics of small forested wetlands [2024 INV#WO0000000109089]
better understand the wetting/drying dynamics of small wetlands relevant to amphibians
Climate Futures for Lizards and Snakes in Western North America [2024 INV#WO0000000109092]
Identifying new management challenges to reptiles based on shifting environmental conditions
InSAR and other geodetic studies at Volcanoes [2024 INV#WO0000000109093]
recognize transient signals in combined InSAR and GPS data that may be indications of impending hazardous volcanic activity
Advancing image-based surveys to support sea duck conservation along the Pacific Flyway [2024 INV#WO0000000109096]
Safety, expense, observer bias and lack of methodological consistency are rising concerns associated with observer-based surveys, making it imperative to transition to more sustai…
Lava lake thermal pattern classification using self organizing maps and relationships to eruption processes at Kilauea Volcano, Hawaii [2024 INV#WO0000000109098]
classify lava lake thermal patterns
Mapping wildfire fuels in previously burned landscapes [2024 INV#WO0000000109121]
understand how land management treatments affect the probability of reburning
SAMPLE Toolbox [2024 INV#WO0000000109123]
monitoring vegetation
Pacific Northwest Stream Flow Permanence [2024 INV#WO0000000109137]
streamflow classification of perennial versus non-perennial which is the charge of many land steward agencies
Oil Spill Response for Ice-Covered Rivers [2024 INV#WO0000000109142]
The goal of this DOI Inland Oil Spill Preparedness Program (IOSPP) funded work is to provide rapid, near real-time information to oil spill response crews concerning about the saf…
Deep Learning application for automated mapping of surficial landforms, surficial geological deposits, and abandoned mine sites from lidar-derived topography [2024 INV#WO0000000109153]
mapping of surficial landforms, surficial geological deposits, and abandoned mine sites
Using machine learning to detect invasive bullfrogs [2024 INV#WO0000000109159]
Detecting bullfrogs along their invasion front in order to inform removal efforts
Predicting Sparse (Geothermal) Resources Availability by using Machine Learning [2024 INV#WO0000000109195]
developing new ML metrics for evaluating model performance that work with sparse natural resources, addressing the extreme mathematical sparsity of these resources at the regional…