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Multiscale mapping is a hot topic in modern cartographic community, and is widely applied in geographic research. It helps us to understand the structural patterns of phenomena that appear in different scales of observations. Sometimes these patterns are established by human, and may have strictly defined borders, such as hierarchy of administrative units. Most of the natural phenomena do not have such well-defined partonomy and can be decomposed into structural levels using spatial statistics and generalization techniques. Our observational research summarizes modern achievements in development of specialized visualization techniques and supporting data analytics for multiscale mapping. We show that appropriate selection of graphical variables, such as color and size of symbols and areas, is essential for understanding the differences between value distributions and spatial distributions at different scales. Changes appearing across scales can be closely related to modifiable unit problem in case of administrative units, and should be reflected in visual representations. We introduce a set of rules for thematic and general mapping that allow for consistent changes of symbology in map zooming process. One of the novelties of our study is establishment of the close relationship between visualization technique and underlying generalization operations.