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Doing more with the core: Proceedings of the 2017 Forest Inventory and Analysis (FIA) Science Stakeholder Meeting; 2017 October 24- 26; Park City, UTAuthor(s): Sean P. Healey; Vicki M. Berrett
Source: Proc. RMRS-P-75. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 56 p.
Publication Series: Proceedings - Paper (PR-P)
Station: Rocky Mountain Research Station
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DescriptionThe Forest Service’s Forest Inventory and Analysis Program (FIA) is the primary source of information about our forests’ status and trends. A network of nationally consistent field observations forms FIA’s core, and active collaboration with clients and peer organizations ensures that the resulting inventory remains agile, comprehensive, and relevant. An FIA Science Stakeholder Meeting was held October 24-26th, 2017, to bring key FIA personnel together with important partners and peers. The theme for this meeting, “Doing More with the Core,” targeted innovation around how FIA analyzes, augments, and delivers information derived from its central data collection operations. Meeting topics included: 1) maximizing the value of the “annual” sample design adopted by the Program approximately 15 years ago; 2) developing better delivery tools that meet client needs and that take advantage of ever-expanding options for data visualization and communication; 3) assuring data continuity that supports a variety of land manager needs; 4) integrating more powerful and efficient monitoring technologies and statistical techniques into established analysis lines; and 5) supporting FIA’s expansion in areas targeted by the most recent Farm Bill. This proceedings document includes details from selected papers presented at the meeting.
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CitationHealey, Sean P.; Berrett, Vicki M., comps. 2017. Doing more with the core: Proceedings of the 2017 Forest Inventory and Analysis (FIA) Science Stakeholder Meeting; 2017 October 24- 26; Park City, UT. Proc. RMRS-P-75. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 56 p.
Keywordsstatistics, estimation, sampling, modeling, remote sensing, forest health, data integrity, environmental monitoring, cover estimation, international forest monitoring
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