Video available on YouTube
Authors: Anthony Guay, Daniel Hayes, Sylvia Noralez, David Sandilands, and Stephanie Willsey, Wheatland Geospatial Lab.
Abstract: Forests provide critical ecosystem services, the sustainable management of which requires high quality and reliable information on the quantity and condition of forest resources. Traditional approaches to forest inventory are limited as information demands increase in the face of a changing and uncertain future. Remote sensing has the potential to revolutionize how we measure and monitor our forests, but the effective application of such emerging technologies requires new research across a range of scales and among different use cases. This is especially true in Maine, which is heavily reliant on its natural resources but where the mixed-species, intensively-managed forests are particularly complex and dynamic. The Wheatland Geospatial Lab (WGL) in the School of Forest Resources at the University of Maine is conducting research at the forefront of Enhanced Forest Inventory (EFI) applications using cutting-edge remote sensing technologies and methodologies. Here, we will present our current findings and future opportunities in co-producing and stakeholder-sharing machine-learning models of EFI attributes using multispectral and LiDAR data sets acquired from drones, airplanes, and satellites and calibrated with high quality ground information collected with\ strategic sample plot designs. We will discuss how we are expanding the scope of this research with larger, NASA-funded projects for biomass mapping with spaceborne LiDAR and multi-data fusion for monitoring, reporting, and verification of forest carbon resources. Finally, we will overview the suite of remote sensing tools, research applications, and stakeholder engagement activities provided by the WGL in service of the geospatial community in Maine and beyond.
Remote sensing of tree composition and structure in an area on the Penobscot Experimental Forest, Bradley, Maine. This image depicts the 3-D “point cloud” of canopy heights, generated from an aerial LiDAR acquisition in August 2021 with NASA Goddard’s LiDAR-Hyperspectral-Thermal (G-LiHT) system, and colored using an aerial infrared image taken with WGL’s camera system on board the University of Maine’s Cessna aircraft.
Bio: (Link to all author bios) Daniel Hayes is an associate professor in the School of Forest Resources at the University of Maine and director of the Wheatland Geospatial Laboratory. Dan teaches and conducts research using remote sensing and modeling tools in the science and applications of forestry and ecology. He is involved in various collaborative scientific efforts including the interagency North American Carbon Program, NASA’s Arctic-Boreal Vulnerability Experiment, DOE’s Next Generation Ecosystem Experiment and the NSF Permafrost Carbon Network. Dan earned a B.S. from SUNY-ESF, an M.S. from UMaine, and a PhD from Oregon State University.
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