In choropleth mapping, most classification schemes that have been proposed are based on the properties of the data's statistical distribution without regard for the data's spatial distribution. However, one of the more important tasks associated with choropleth map reading is the task of regionalization and identifying spatial patterns. For this reason some authors have proposed class interval selection procedures that also consider spatial contiguity. This book evaluates different classification schemes based on given data sets statistical as well as its spatial distribution. This book also involved with the choosing of suitable choropleth technique for given data set considering their accuracy level.