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…
Gulf Coast Geologic Energy Machine Learning [2024 INV#WO0000000109198]
predict expected ultimate recovery of shale oil wells
Seedling Identification and Percent Growth Analysis [2024 INV#WO0000000109200]
extraction of alphanumeric labels and analyze seedling growth in petri dish images
Earthquake Catalog Development [2024 INV#WO0000000109208]
develop more complete and robust earthquake catalogs
Seismology of Magmatic Injection [2024 INV#WO0000000109214]
understand the nature and dynamics of seismic sources associated with magmatic injection and magmatic transport
Quantifying Watershed Controls on Fine Sediment Flux to Lake Tahoe, California/Nevada [2024 INV#WO0000000109215]
estimate watershed parameters of importance that drive sediment flux
Development of a Strategic Framework for Use and Implementation of Machine Learning in Energy Resource Program Workflows [2024 INV#WO0000000109216]
development of a strategic framework for integrating Energy Resources Program science with traditional information technology related platforms
Ecological niche models for bat species [2024 INV#WO0000000109233]
We are trying to understand what environmental factors determine the presence and absence of bat species across their range.
Machine Learning to evaluate water quality [2024 INV#WO0000000109241]
Examining the effect of physicochemical and meteorological variables on water quality indicators of harmful algal blooms in a shallow hypereutrophic lake
Wildlife species recognition and distance from camera estimation [2024 INV#WO0000000109245]
need reliable population estimates of animal density
Computationally efficient emulation of spheroidal elastic deformation sources using machine learning [2024 INV#WO0000000109302]
analytical models are fast but can be inaccurate as they do not correctly satisfy boundary conditions for many geometries, while numerical models are slow and may require speciali…
Quantifying the effects of land-use change and bioenergy crop production on pollinators, wildlife, and ecosystem services in the Northern Great Plains [2024 INV#WO0000000109305]
Quantifying the effects of land-use change and bioenergy crop production on pollinators, wildlife, and ecosystem services in the Northern Great Plains
Oceanographic, coastal, and geomorphic change analysis: data generation, QC/QA, and data management [2024 INV#WO0000000109310]
Machine learning to quantify coastal/marine change across broad scales. QC/QA processes in place to assess data robustness.