Summer School on Topological and Scaling Analyses of Transport and Social Media
Data (June 13–17, 2016, Gävle, Sweden)
Current geospatial analysis is highly constrained by Euclidean geometry and Gaussian statistics in the sense of geographic locations and distances, as well as a well-defined mean
and small variance. These two ways of thinking (Euclidean geometry and Gaussian statistics) suffer from some major disadvantages that prevent us from gaining new insights into the underlying complexity of geographic phenomena. On the other hand, topology, fractal geometry, and power law statistics represent new perspectives for geospatial analysis, particularly in the era of big data.