Reviving legacy population maps with object-oriented image processing techniques

Vast archives of legacy maps exist for most parts of the world, containing analog information on a variety of environmental and socioeconomic parameters, and often dating back to the nineteenth century. The information contained in those data, which is potentially of great utility in environmental change or demographic studies, has traditionally only been accessible through digitizing or visual map analysis. In this paper, we show how object-oriented analysis can be used to unlock such information. We demonstrate this on a 1962 map of Kenya, which shows population distribution using differently sized dots. The procedure developed extracts those population signatures accurately, despite size and color variations, dot bleeding, and conglutination, as well as overlap with other map elements. Over 39 000 dots were automatically extracted, corresponding to 99.6 % of the published population figure, with an accuracy between 94.6% and 98.5% for the different symbol sizes. We also discuss the utility of the derived geographic-information-system-ready information, for example, to assess malaria exposure and calculate population change figures, using the 1999 census data at a detailed sublocation level. Index Terms--Definiens, demography, eCognition, image segmentation, object-oriented methods, pattern recognition.