We quantified the map accuracy for the Sacramento River Monitoring and Assessment Project to help land and water manager’s better plan for restoration efforts. While map errors are quantifiable and even predictable, linking the causes of error to complex environmental and geographic variables would improve decision making. We evaluated patterns of GIS-induced map error on over 32,000 acres based on environmental and GIS variables like floodplain age and edge complexity. We conducted extensive field validation and used spatial statistics to compare environmental variables with vegetation map inaccuracies. We then constructed a multivariate model to predict errors in certain vegetation types. We field validated 15% of map polygons (n=8,067) which were 85% correct (K=0.83). Using validated polygons, we found errors occurred most frequently on older floodplains but rates varied by vegetation type. By incorporating error in attribution and spatial assignment, restoration planners have a more realistic assessment of current conditions.
Viers, JH, AK Fremier, and RA Hutchinson. 2010. Predicting map error by modeling the Sacramento River floodplain. Proceedings from the 2010 ESRI International User Conference, San Diego, California. 21 ppd.