Capturing Raster Data From Scanned Thematic Maps Using Desktop Graphics Software
Stephen M. Wise
Abstract
Stephen M. Wise
Abstract
Data capture from paper maps remain a slow and costly part of many Geographic Information System projects. In this paper a simple method is described which makes use of the facilities of desktop graphics software to capture raster data from scanned thematic maps. The first stage is to use the flood fill tool to identify the regions of the map that represent the data values and set them to a separate colour for each thematic category. This edited image is then imported into a GIS, where a specially written majority filter is used to classify any remaining pixels to produce a raster GIS layer. The technique is tested on samples from three maps, giving accuracy levels of over 90% in all cases when compared with digitising the same maps by hand. The technique could be useful for situations where a rapid and simple means of data capture is needed and could be developed further by drawing on techniques for contextual classification rather than relying on a general purpose flood fill algorithm.
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Data capture from paper maps remain a slow and costly part of many Geographic Information System projects. In this paper a simple method is described which makes use of the facilities of desktop graphics software to capture raster data from scanned thematic maps. The first stage is to use the flood fill tool to identify the regions of the map that represent the data values and set them to a separate colour for each thematic category. This edited image is then imported into a GIS, where a specially written majority filter is used to classify any remaining pixels to produce a raster GIS layer. The technique is tested on samples from three maps, giving accuracy levels of over 90% in all cases when compared with digitising the same maps by hand. The technique could be useful for situations where a rapid and simple means of data capture is needed and could be developed further by drawing on techniques for contextual classification rather than relying on a general purpose flood fill algorithm.
Key concepts: Raster graphics, Thematic map, Raster data, Computer science, Software, Graphics, Set (abstract data type), Filter (signal processing)