Landform perception accuracy in shaded relief maps : a replication study confirms that nnw lighting is better than nw against the relief inversion effect

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Authors

Coltekin, A.
Rautenbach, Victoria
Coetzee, Serena Martha
Mokwena, T.

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Copernicus Publications

Abstract

Relief inversion effect is a perceptual phenomenon that leads to an inverted perception of convex and concave shapes. This perceptual inversion occurs in scenes where the shading/shadows act as the main depth cue. In visuospatial displays, such as shaded relief maps, the positioning of the shadows in the northern slopes, thus when light source placed broadly in south, mislead the cognitive system based on the ‘light from above prior’ assumption (Mamassian and Goutcher 2001). Thus, assuming the light must come from above, our mind creates an illusion, and we perceive the landforms incorrectly. To judge the 3D spatial relationships in terrain representations correctly, the relief inversion effect must be avoided. Cartographic convention against this effect is to place the light source at northwest (NW), whereas a recent study demonstrated that north-north-west (NNW), or even north yields more precise results (Biland and Çöltekin, 2016). Since this finding goes against decades of convention, to establish its validity further, we attempted replicating the results with a different sample in South Africa. In this paper, we present our findings, which broadly confirm that the NNW (or also N) is better than NW against the relief inversion effect.

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Keywords

Relief inversion effect, Terrain reversal effect, Shaded relief maps, Landform perception, Light direction, Facsimile, Terrain representations, Spatial relationships, Replication study, Inversion effects, Concave shape, Light source, Cognitive systems

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Citation

Cöltekin, A., Rautenbach, V., Coetzee, S. et al. 2018, 'Landform perception accuracy in shaded relief maps : a replication study confirms that nnw lighting is better than nw against the relief inversion effect', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, no. 4, pp. 169-175.