The Impact of Map Generalization with Multiple Spatial Data Levels on GIS Analyses

When representing spatial data and their attributes on different types of maps, the scale which is the numerical relationship between the ground extent and the mapped extent, plays a key role. In order to create a clear and legible map at different scale levels, map generalization techniques are used. Though current commercial mapping software packages are integrated with sophisticated tools and operations to prepare maps and to manage spatial data, users violate some basic theorems and concepts in cartography. They retrieve a data set and do the analysis part without considering very important characteristics such as the scale of the source data set, the purpose of what the original map is prepared and the degree of generalization of the data sets. Further, the GIS users use and combine different scaled data sets with different degrees of generalization. In this study, it attempts to find the impacts of map generalization on GIS analyses. Current study used two types of features with different spatial data levels for a simple GIS analysis. These digital data sets were prepared by the Survey Department of Sri Lanka with the scales of 1:10000, 1:50000 and 1: 250000. 09 combinations of data sets were used for the analysis through a model prepared using the model builder tool in the GIS package. This simple overlay operation was done to find the best location for a wild life park using three basic requirements. The study clearly shows that different results can be obtained for different combinations. It can be noticed different potential zones with the variations of the number, extent, X and Y coordinates of the Centroid and their perimeters. Therefore, study thoroughly recommends to GIS users to use different data layers with same scale and same degree of generalization in the analyses.