Estimating the uncertainty of land-cover extrapolations while constructing a raster map from tabular data

This paper presents novel techniques to estimate the uncertainty in extrapolations of spatially-explicit land-change simulation models. We illustrate the concept by mapping a historic landscape based on: 1) tabular data concerning the quantity in each land cover category at a distant point in time at the stratum level, 2) empirical maps from more recent points in time at the grid cell level, and 3) a simulation model that extrapolates land-cover change at the grid cell level. This paper focuses on the method to show uncertainty explicitly in the map of the simulated landscape at the distant point in time. The method requires that validation of the land-cover change model be quantified at the grid-cell level by Kappa for location (Klocation). The validation statistic is used to estimate the certainty in the extrapolation to a point in time where an empirical map does not exist. As an example, we reconstruct the 1951 landscape of the Ipswich River Watershed in Massachusetts, USA. The technique creates a map of 1951 simulated forest with an overall estimated accuracy of 0.91, with an estimated user’s accuracy ranging from 0.95 to 0.84. We anticipate that this method will become popular, because tabular information concerning land cover at coarse stratum-level scales is abundant, while digital maps of the specific location of land cover are needed at a finer spatial resolution. The method is a key to link non-spatial models with spatially-explicit models. The National Science Foundation (NSF) supported this work through its Water and Watersheds program grant DEB-9726862 and its Research Experience for Undergraduates Summer Fellowship Program. Additional contributors include the Jesse B. Cox Charitable Trust, the Sweetwater Trust, and NSF’s Long Term Ecological Research program OCE-9726921. Stephen Aldrich compiled much of the data from MassGIS. We also thank the George Perkins Marsh Institute at Clark University and the Center for Integrated Study of the Human Dimensions of Global Change at Carnegie Mellon University, with which this work is increasingly tied intellectually and programmatically. The data for this analysis is part of the HERO project, funded by NSF grant 9978052. Hao Chen of Clark Labs programmed the Geomod model and other features required for this analysis into the GIS software Idrisi . J Geograph Syst (2003) 5:253–273 DOI: 10.1007/s10109-003-0109-9 Estimating the uncertainty of land-cover extrapolations while constructing a raster map from tabular data Robert Gilmore Pontius Jr., Aditya Agrawal, Diana Huffaker 1 Clark University, Graduate School of Geography, Department of International Development, Community and Environment, 950 Main Street, Worcester MA 01610-1477, USA (e-mail: [email protected], [email protected]) 2 NOAA Fisheries, Southwest Fisheries Science Center, Santa Cruz Laboratory, 110 Shaffer Road, Santa Cruz, CA 95060, USA (e-mail: [email protected]) Received: 15 October 2002/Accepted: 12 March 2003