A Proposal for High Resolution Land Cover and Forest Mapping Products for Maine
Link to YouTube Video
Join Nate Herold from NOAA's Office for Coastal Management (OCM), Kasey Legaard from the University of Maine Center for Research on Sustainable Forests, and moderator Jamie Carter from NOAA’s Office for Coastal Management for a discussion of High Resolution Land Cover Data.
The Maine GeoLibrary has recently endorsed a proposal by NOAA's Office for Coastal Management (OCM) and the University of Maine's Intelligent GeoSolutions group to produce coordinated statewide land cover and forest type data. We will be discussing the specifics of the proposed data which will include both a 1-meter resolution land cover consistent with the national Coastal Change Analysis Program (C-CAP) standard (which is meant to replace the previously produced Maine Land Cover Dataset - MeLCD) and a 10-meter map of detailed forest types. Both are being produced with advanced classification methods and envisioned to be the basis for monitoring into the future.
Nate Herold is a Physical Scientist with NOAA's Office for Coastal Management (OCM). He is located in Charleston, South Carolina where he is responsible for leading NOAA’s national land cover monitoring activities through its Coastal Change Analysis Program, or C-CAP. His work includes improving mapping efficiency and accuracy; oversight of land cover task order awards; coordination of partnerships at the local, regional, and national levels; modeling potential wetland impacts from Sea Level Rise; and generally translating data into meaningful information that can inform decision making. He is intimately involved in NOAA's Digital Coast data and tools efforts. He has a Bachelor’s in Soil Science from The Pennsylvania State University and a Masters in Geography from George Mason University.
Kasey Legaard is a Research Assistant Professor with the University of Maine Center for Research on Sustainable Forests and School of Forest Resources, where his work revolves around satellite remote sensing of forest resources. As project leader for the U. Maine Intelligent GeoSolutions (IGS) group, he is broadly responsible for the design, implementation, and execution of machine learning methods to improve forest maps derived from satellite imagery. IGS was formed specifically to develop high-value, low-cost forest data for Maine stakeholders using methods developed at U. Maine. He has bachelor’s degrees in Mathematics and Biology from Idaho State University, a master’s degree in Oceanography from U. Maine, and a PhD in Forest Resources also from U. Maine.
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