Positional accuracy, positional uncertainty, and feature change detection in historical maps: Results of an experiment

The measurement and management of positional accuracy and positional uncertainty is especially problematic in historical cartography and Historical GIS applications, for at least two reasons: first, historical sources, and especially historical maps, generally carry a higher degree of positional inaccuracy and uncertainty compared to contemporary geographic databases; second, it is always difficult and often impossible to reliably measure the positional accuracy and positional uncertainty of the spatial attribute of historical data. As an added complication, the terms “inaccuracy” and “uncertainty” are often used as synonyms in the literature, with relatively little attention given to issues of uncertainty.In this article we propose a methodology for detecting the positional inaccuracy and positional uncertainty of measurements of urban change using historical maps at a very high spatial resolution (the building). A widely accepted and routinely employed method for detecting urban change, and spatial change in general, consists in overlaying two or more maps created at different dates, but the technique can lead to the formation of spurious changes—typically, sliver polygons—that are the product of misclassification error or map misalignment rather than actual modifications in land cover. In this paper we develop an algorithm to detect such spurious changes. More in general, we extend the discussion to examine the effects of positional uncertainty and positional inaccuracy in feature change detection analysis. The case-study is the city of Milan, Italy.

► We overlay a historical map with a current map (2005) of Milan, Italy.
► We examine urban changes that have occurred between the two periods.
► We develop an algorithm for the detection of spurious changes due to the overlay process.
► Spurious changes are indicator of positional inaccuracy and positional uncertainty.
► Inaccuracy and uncertainty are ontologically different, but disentangling the two when measuring urban change is problematic.