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 […]
A synthesis study of the terrestrial ecosystem carbon cycle at various temporal and spatial scales

This research includes analyzing the impacts of wildfires on the global terrestrial biosphere carbon cycle, assessing the patterns of biome carbon fluxes in response to droughts at different time scales, and estimating carbon fluxes with Terrestrial Ecosystem Model. This includes modeling the lateral dissolved organic carbon (DOC) flux into an earth system model. The lateral […]
An Assessment of Aerial Survey Acquisition Methods for Generating Forest Inventory Models

Structure from motion (SfM) derived three dimensional (3D) point clouds have performed well in comparison to airborne laser scanning (ALS) in generating timber inventory models, yet little has been done to assess the viability of a wide range of aerial image acquisition methods for developing these models. Remote sensing factors such as sensor reflectance characteristics, […]
Investigating the patterns of vegetation-permafrost dynamics as determined by landscape-scale disturbance

The University of Maine conducts research in collaboration with Brookhaven National Laboratory and Oak Ridge National Laboratory toward a subset of science objectives outlined in the Phase 3 proposal of the Next-generation Ecosystem Experiments (NGEE) in the Arctic. The NGEE-Arctic project is using observations, experiments and modeling to improve our predictive understanding of Arctic ecosystem […]