2023 AGU Meeting

At the 2023 American Geophysical Union meeting in San Francisco, Xinyuan Wei and Daniel Hayes made a significant impact with their presentations on innovative forest research. They introduced a pioneering project for Maine’s working forests, titled “Building a carbon MRV prototype using a stakeholder-driven, landscape model-data framework.” This initiative aims to enhance sustainable forest management […]

Stephanie Willsey

Stephanie Willsey is a 2nd year Masters student under Dan Hayes in the School of Forest Resources at the University of Maine. Her current research focuses on how calibration plot data affects enhanced forest inventories in Maine. Before becoming a member of the Barbara Wheatland Geospatial Lab, she was a Master of Forestry student at […]

Xinyuan Wei

Xinyuan Wei joined the School of Forest Resources in July 2023 as an Assistant Research Professor. Previously, he worked at Oak Ridge National Laboratory. His research primarily focuses on accounting for carbon storage in forest ecosystems, examining the impacts of climate change and disturbances on forest biomass, applying forest ecosystem simulation models, and studying the […]

UMaine & NASA to map carbon in forests!

Check out this article in Mainebiz about our new project with NASA and the Center for Research on Sustainable Forests to map forest carbon with spaceborne LiDAR!

Leveraging High Resolution Forest Inventory and Satellites to Predict Fire Damage Severity at the Micro-Stand Level

Please join us for our next Wheatland Seminar! Cassidy Rankine Director of Remote Sensing High Resolution Inventory Solutions (HRIS) Wednesday, November 4, 2020 3:00 pm ET via Zoom (https://maine.zoom. us/j/95874189170)

Moving Beyond Enhanced Forest Inventory (EFI): Accelerating the Digitalization of the Forest Value-Chain

Please join us for next week’s Wheatland Seminar! Adam Dick Forest Research Project Leader Canadian Wood Fibre Centre / Canadian Forest Service Wednesday, October 14, 2020 3:00 pm ET via Zoom (https://maine.zoom. us/j/95874189170)  

Forest Disturbance Detection and Aboveground Biomass Modeling Using Moderate-Resolution, Time-Series Satellite Imagery

Human-induced and natural disturbances are an important feature of forest ecosystems. Disturbances influence forest structure and composition and can impact crucial ecosystem services. However, deriving spatially explicit estimates of past forest disturbance across a large region can prove challenging. Researchers have recognized that remote sensing is an important tool for monitoring forest ecosystems and mapping […]

Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Forest Inventories of New England

For two decades Light Detection and Ranging (LiDAR) data has been used to develop spatially-explicit forest inventories. Data derived from LiDAR depict three-dimensional forest canopy structure and are useful for predicting forest attributes such as biomass, stem density, and species. Such enhanced forest inventories (EFIs) are useful for carbon accounting, forest management, and wildlife habitat […]

Airborne Hyperspectral Data Application in Health Stress Detection of Blueberry Fields and Ash Trees

Advanced detection of health stress in agricultural fields and forests can prompt management responses to mitigate detrimental conditions such as nutrient deficiencies, disease, and mortality. New applications in hyperspectral data and imaging spectroscopy on agriculture and forests have shown the potential for early stress detection. We build on previous work by assessing two different systems; […]

The Effects of Climate Change on Forest Ecosystem Phenology and its Impacts on Tourism in Maine

Over the past 25 years, the average annual temperature in Maine increased by nearly 2 °C and is predicted to continue rising if global carbon emissions are not reduced. Climate warming is affecting the social and ecological systems of the northeastern U.S., including changes in the seasonal timing and duration of biophysical processes. Phenology is […]