Methods for visual quality assessment of a digital terrain model

A Digital Terrain Model (DTM) is a continuous representation of a ground surface landform that is commonly used to produce topographic maps. DTMs are created by integrating data obtained from a wide range of techniques including remote sensing and land surveying. Quality assessment of data is a critical parameter for DTM production and it relies heavily on statistical methods. In contrast, visual methods are generally neglected despite their potential for improving DTM quality. In this paper, several enhanced visual techniques for quality assessment are described and illustrated with areas and datasets selected from Slovenia and the planet Mars. Four classes of visual methods are defined: visualisations according to spatial analytical operations based on one or multiple datasets; visualisations according to spatial statistical analysis; non-spatial visualisations; and other visualisation techniques/other algorithms. The four classes generate different outputs: the first two produce thematic maps, while the third is used for non-spatial visualisation. The fourth class gathers other possible visualisations and algorithms. It is suggested that applying visual methods in addition to the more objective statistical methods would result in a more efficient improvement of the quality.