Abstract
The Forest Service, U.S. Department of Agriculture's (USDA's) Northern Research Station Forest Inventory and Analysis program (NRS-FIA) examines inventory locations on digital aerial imagery to determine if the land use at each plot location meets the FIA definition of forest and thereby becomes a field visit site. This manual image-interpretation effort requires a significant amount of staff time yet accrues substantial financial savings. Using the same imagery currently used by NRS-FIA, the Service Center Agencies of the USDA have initiated work on a digital data set detailing agricultural areas, including a land class designation. These data are known as Common Land Units (CLUs). In this study, CLU data for the State of Minnesota were acquired from USDA?s Farm Service Agency. NRS-FIA manual image-interpretation information for inventory locations was compared with the land class information in the CLU data set. Thirty-five percent of Minnesota FIA plots were identified as nonforest using the CLU data set. A little less than 1 percent of plots fell within nonforest CLU polygons yet were observed during field visits to be forested. Thus, the CLU method for identifying nonforest plots may introduce a small underestimation bias into the inventory. Because NRS-FIA plots previously observed as forested will be revisited regardless of an updated land use status, however, this bias would not occur. Thus, the CLU data set shows the potential to eliminate manual, prefield image interpretation of plots occurring within agricultural areas delineated by CLU boundaries.
Parent Publication
Citation
Liknes, Greg C.; Nelson, Mark D. 2009. Improving Forest Inventory and Analysis efficiency with common land unit information. In: McRoberts, Ronald E.; Reams, Gregory A.; Van Deusen, Paul C.; McWilliams, William H., eds. Proceedings of the eighth annual forest inventory and analysis symposium; 2006 October 16-19; Monterey, CA. Gen. Tech. Report WO-79. Washington, DC: U.S. Department of Agriculture, Forest Service. 363-366.
