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Estimating fine-scale land use change dynamics using an expedient photointerpretation-based method Tonya Lister1, Andrew Lister1, and Eunice Alexander1 Abstract: Population growth and urban expansion have resulted in the loss of forest land. With growing concerns about this loss and its implications for global processes and carbon budgets, there is a great need for detailed and reliable land use change data. Currently, the Northern Research Station uses an Annual Inventory design whereby all plots are revisited every 5 years and land use change matrices are estimated using a mapped plot design. These methods have great potential for providing the needed land use change data; however, for many states in the Northern region, these data will not be available until 2013 or later and the ability of these methods to capture finer scale changes, especially those due to urbanization, has not yet been tested. This paper presents an efficient photointerpretation-based change detection method that automates the work of gathering and loading images. A grid of photo plots is optimally created and overlain on the sample area, and land use change is recorded for two points in time by comparing digital imagery from 1998 and 2007. Results of a pilot test in Maryland show a net loss of forest land with losses due primarily to urban development and most gains in forest land coming from agricultural land uses. Forest losses are largely concentrated around Baltimore and Washington, DC. This pilot study indicates that about 75,000 photo plots would be needed to estimate land use change in Maryland at the county level. This would require approximately 125 hours, about 1.12 minutes per thousand acres, or roughly $1,500. The photointerpretation method presented here could be applied to other states and is well suited for land use change monitoring as the same points could be resampled when new imagery becomes available