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Comparison of forest area data in the Chesapeake Bay WatershedAuthor(s): Tonya W. Lister; Andrew J. Lister
Source: In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 29-36.
Publication Series: Paper (invited, offered, keynote)
Station: Northern Research Station
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DescriptionThe Chesapeake Bay, the largest estuary in the United States, has been designated by executive order as a national treasure. There is much interest in monitoring the status and trends in forest area within the bay, especially since maintaining forest cover is key to bay restoration efforts. The Chesapeake Bay Land Cover Data Series (CBLCD), a Landsat-based, multi-temporal change detection raster geographic information system (GIS) product was developed by the U.S. Geological Service (USGS) to monitor land cover change in the bay. The objective of this study was to assess relationships between the CBLCD dataset and Forest Inventory and Analysis (FIA) estimates of land use in order to provide a better understanding of the nature of the CBLCD and its potential for use in assessing forest cover dynamics. Data were summarized at different geographic scales, and differences between datasets were highlighted with the goal of providing information that will help users of the CBLCD interpret findings. Our analyses suggest there is a strong, positive relationship between the CBLCD forest information and that from the FIA data. Misclassifications can be explained by analyses created by integrating the CBLCD data with the FIA data and standard FIA reporting tools.
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CitationLister, Tonya W.; Lister, Andrew J. 2012. Comparison of forest area data in the Chesapeake Bay Watershed. In: Morin, Randall S.; Liknes, Greg C., comps. Moving from status to trends: Forest Inventory and Analysis (FIA) symposium 2012; 2012 December 4-6; Baltimore, MD. Gen. Tech. Rep. NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. [CD-ROM]: 29-36.
Keywordsstatistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring
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