Project Summary
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Spatially explicit information about forest stand-level attributes across all land ownerships provide a valuable resource for informing forest assessments, management planning, and policy decisions. Patterns of forest structure and mosaics of stand ages across landscapes are largely driven by canopy disturbances caused by both natural events (e.g. wildfire, windstorms, flooding, insects, and disease) and human actions (e.g. harvest, thinning, and planting). These disturbance events impact stand boundaries, age, structure, and growth. The cause of change (e.g. harvest, fire, or insects) can also influence goods and services such as economic value, productivity, recreation opportunities, water quality, biodiversity, and forest resilience. We aim to leverage the long-running Landsat archive, advances in cloud computing resources, and additional ancillary data sets to map annual forest canopy cover and identify disturbance patterns by their agents of change across the Great Lakes Basins. These canopy cover and disturbance products will be incorporated into efforts that take a watershed perspective across all land ownerships, such as National Forest planning and the Great Lakes Restoration Initiative. This project will support improved forest stewardship and facilitate assessments of the impacts of changes in land use and land cover on watershed health and brook trout habitat.
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Research Objectives
Objective 1Compile a Landsat time series dataset (1984-2019) across the Great Lakes basins to aid in land cover mapping, forest attribute modeling, and forest change detection to support management and landscape planning across all ownerships.
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Objective 2Produce annual forest masks and maps of percent canopy cover across the Great Lakes basins (1984-2019) for assessing changes in forest extents and additional evaluations related to impacts on watershed health.
Objective 3Identify abrupt forest change patches by year and magnitude of change, further classifying the agent of change (e.g. harvest, fire), for all patches across the study region to quantify land use changes and disturbance impacts on watershed health and fish habitat quality.
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Project Outputs
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Publications
Fekety, P.A., Vogeler, J.C., Filippelli, S.K., & Nelson, M.D. (2025). Forest disturbance attribution and sensitivity to harvest detection with Landsat in the Greak Lakes region, USA. Forest Ecology and Management, 595, p.123039. https://authors.elsevier.com/c/1lVkJ_8cEVTqL3
Filippelli, S., Vogeler, J., Schleeweis, K., Fekety, P., & Nelson, M. (2024). Temporal transferability of remote sensing models for large area monitoring. Science of Remote Sensing. p.100119. https://doi.org/10.1016/j.srs.2024.100119 Severud, W.J., Landisch, P., Nelson, M.D., Elliott, L.H., Vogeler, J.C., Host, T.K., & Knight, J.F. (2020). Combining FIA and Land Cover Data for Assessing Watershed Conditions for Coldwater Fish within Great Lakes Basins. Pp. 42-44. In Brandeis, T.J., comp. Celebrating progress, possibilities, and partnerships: Proceedings of the 2019 Forest Inventory and Analysis (FIA) Science Stakeholder Meeting. November 19-21, 2019; Knoxville, TN. e-Gen. Tech. Rep. SRS-256. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 267 p. |
Spatial Data Products
Fekety, Patrick A., Vogeler, Jody C., Filippelli, Steven K., Nelson, Mark, D. (2025). Forest disturbances in the Great Lakes region, 1986-2019. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2025-0020
Filippelli, S.K.; Schleeweis, K.G.; Nelson, M.D.; Fekety, P.A.; Vogeler, J.C. (2023). Tree canopy cover in the Great Lakes region, 1985-2019. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2023-0043 |
Project Team & Funding
CollaboratorsDr. Mark Nelson - USDA Forest Service
Dr. Karen Schleeweis - USDA Forest Service |
Funding Agency:
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