These limitations are: (1) spatial data will show some degree of spatial dependence; (2) spatial data often are subject to a modifiable areal unit problem (MAUP); and (3) the assumption of variable data stationarity often is violated across the study area and fueled the development of exploratory spatial data analysis (ESDA) methods (Unwin and Unwin 1998).
Exploratory spatial data analysis is broadly defined as the collection of techniques to describe and visualize spatial distribution, identify atypical locations, discover patterns of spatial association, and suggest different spatial regimes and other forms of spatial instability.
Dall'erba (2010) Spatial Disparities across the Regions of Turkey: An Exploratory Spatial Data Analysis.
Ertur (2003) Exploratory Spatial Data Analysis of the Distribution of Regional Per Capita GDP in Europe, 1980-1995.
The spatial patterning of county homicide rates: an application of exploratory spatial data analysis
Although this article focuses on exploratory spatial data analysis
and spatial regression procedures, procedures have been developed to conduct spatial Poisson, spatial time series cross-sectional, and spatial hierarchical models (see Banerjee, Carlin, & Gelfand, 2003; Gruenewald, Millar, Ponicki, & Brinkley, 2000).