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).