Spatial Autocorrelation and Random Effects in Digitizing Error
Daniel A. Griffith
Ashbel Smith Professor of Geospatial Information Sciences
University of Texas at Dallas, USA
Abstract. The volume of georeferenced data that have involved manual digitizing suggests that error associated with this process merits a more thorough analysis, especially given recent advances in conventional and spatial statistical methodology. Spatial filtering and mixed modeling techniques are used to analyze manual digitizing outcomes of an experiment involving Hill’s famous drumlins data of Northern
Ireland. Findings include: (a) spatial autocorrelation plays an important role, and (b) a random effects term accounts for a nontrivial amount of variability.
Keywords: digitizing error, drumlins, random effects, spatial autocorrelation
In: Wan, Y. et al. (eds) Proceeding of the 8th international symposium on spatial accuracy assessment in natural resources and environmental sciences, World Academic Union (Press).