Raster Tools
Integrating geospatial analysis with AI in parallel.
TreeMap and FuelMap (all versions)
Produce tree-level model of the forests of the US, and corresponding model of fuel loading.
Landscape Change Monitoring System (LCMS)
LCMS produces annual vegetation cover change, land cover, land use, and tree canopy cover data on National Forest System lands and more broadly across the conterminous United Stat…
Forest Health Detection Monitoring
This project monitors forest health by detecting tree damage through changes in light patterns collected by satellites.
DISTRIB-II: Habitat Suitability of Eastern United States Tree
The goal of this use case is to provide information about current and future habitat suitability of east United States tree species. Machine learning is used to develop models tha…
XyloTron/XyloPhone Wood Identification System
The purpose of these tools is to identify different types of wood based on their cross-section. These tools will help industries follow laws and support law enforcement in meeting…
Forest disease detection and screening
To improve tree disease diagnosis and screening.
Use of LLMs for data extraction
The purpose of this model is to quickly gather information from scientific papers to track the spread of plant diseases.
Fire Resilient Landscapes
Assists in planning treatments to reduce wildfire risk and calculate treatment costs
Spread and Balance Sample Design
The purpose of this tool is to produce samples that are well spread and balanced, reducing sampling cost and error.
Regression, Classification, Clustering with Hilbert Curves
Implementation of many machine learning techniques into applied research
The Big Data, Mapping, and Analytics Platform (BIGMAP) Project
To produce maps of various characteristics of US forests at all locations, based on field plots measured by the US Forest Service Forest Inventory and Analysis (FIA) program only…
Wildlife Deterrent System
The purpose of the AI device is to keep coyotes out of a fenced area by blocking their entry through a gap in the fence, while still allowing other wildlife to pass through.
Markov random fields for mixed forests
A level of uncertainty can exist in model predictions and sometimes that level of uncertainty is incorrectly assessed, leading to less effective decision-making when based on the…
IOL Focus Group and Survey Sensemaking
Processing and interpretation of questionnaires and transcripts can be slow and tedious. Using Google NotebookLM can improve the process.
Esri ArcGIS Pro Deep Learning Modules
Object detection from aerial images
Forest based and boosted classification and regression methods
Determining which features of a forest best indicate species presence and amount
MaxEnt/ENMeval models of habitat suitability
Predict species habitat under current and future conditions
Species Distribution Data analysis
Machine learning models built for predicting and understanding species distributions and ranges for thousands of different species.
A wetland-based habitat suitability model for Spotted Turtles in West Virginia
Classifying environmental suitability of wetlands for a species of turtle.
Projected contemporary habitat distribution and quality for wood turtles in the midwestern United States
Estimating environmental suitability of stream cells for a turtle species.
Amphibians reveal unexpectedly large differences in potential environmental change responses among ecologically similar habitat specialists
Estimating environmental suitability for amphibians
Projected future changes in the geographic distributions of the threatened Plethodon nettingi and a potential competitor
Estimation of environmental suitability for two salamander species.
Random Forest with Aquatic Effectiveness Monitoring
Protecting aquatic ecosystems and restoring watershed processes can be improved by understanding predictors of sediment in streams after wildfire.