Gregory McHale

Greg McHale is a Masters student under Dan Hayes in the School of Forest Resources. His current research focuses on mapping the distribution and vegetation stress of coastal spruce forests in Maine using in-situ and remote sensing data sources. He is utilizing a scaling framework that connects ground-based, unmanned aerial vehicle (UAV), and satellite data […]

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 […]

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!

Spectroscopy of plants – What light spectra can tell us about functional, taxonomic, and phylogenetic plant biodiversity

Please join us for our next Wheatland Seminar! Anna K. Schweiger Postdoctoral Researcher University of Zurich & Université de Montréal Wednesday, November 18, 2020 1:00 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)  

Planes, UAVs, and AI to count seabirds in coastal Maine

Two recent articles on an interdisciplinary research project to develop AI tools for automated seabird surveys in coastal Maine using plane and UAV-based aerial imagery. Bangor Daily News article here UMaine News article here  

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 […]