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Land-use/cover change (LUCC) projections can be generated by a variety of land-cover change models (LCMs) and applied to a range of ecological and environmental studies. Most existing spatially explicit LCMs represent land use or cover using either pixel or polygon/patch spatial units. However, the effects of the choice to use pixel versus polygonal land units on the outputs from any given model have not yet been systematically assessed. We evaluated the impacts of alternative land units on the performance of a LCM. A stochastic LCM based on a geostatistical algorithm was developed and applied using both pixel and polygons, which were derived from parcel maps. Nine possible parcel-change scenarios were generated to evaluate the effects of geometric change in management boundaries. The approach was tested through the simulation of multiple land-cover transitions in Medina County, Ohio, between 1992 and 2011. Performance of the simulations was assessed using a metric for the accuracy of spatial allocations (figure of merit (FoM)) and several landscape pattern metrics describing the shapes and sizes of resulting land-cover patches. Results support the notion that there is a clear trade-off between pixel and polygon land units: using polygon boundaries is helpful in obtaining more realistic spatial patterns, but at the cost of location accuracy. Significant differences were found among different parcel-change scenarios on both location accuracy and spatial patterns, with the primary effects being dependent on the type of land-cover transition and the resolution at which validation was assessed.

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This page is a summary of: Sensitivity of a stochastic land-cover change model to pixel versus polygonal land units, International Journal of Geographical Information Science, September 2016, Taylor & Francis,
DOI: 10.1080/13658816.2016.1231316.
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