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Remote Sensing Inventory and Monitoring of Maine’s Forest Resources
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.

Authors: Anthony Guay, Daniel Hayes, Sylvia Noralez, David Sandilands, and Stephanie Willsey, Wheatland Geospatial Lab.

Jan 25, 2022 12:00 PM in Eastern Time (US and Canada)

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