Landmarks constitute an essential basis for a structural understanding of the spatial environment. Therefore, they are crucial factors in external spatial representations such as maps and verbal route descriptions, which are used to support wayfinding. However, selecting landmarks for these representations is a difficult task, for which an understanding of how people perceive and remember landmarks in the environment is needed. We investigated the ways in which people perceive and remember landmarks in nature using the thinking aloud and sketch map methods during both the summer and the winter seasons. We examined the differences between methods to identify those landmarks that should be selected for external spatial representations, such as maps or route descriptions, in varying conditions. We found differences in the use of landmarks both in terms of the methods and also between the different seasons. In particular, the participants used passage and tree-related landmarks at significantly different frequencies with the thinking aloud and sketch map methods. The results are likely to reflect the different roles of the landmark groups when using the two methods, but also the differences in counting landmarks when using both methods. Seasonal differences in the use of landmarks occurred only with the thinking aloud method. Sketch maps were drawn similarly in summertime and wintertime; the participants remembered and selected landmarks similarly independent of the differences in their perceptions of the environment due to the season. The achieved results may guide the planning of external spatial representations within the context of wayfinding as well as when planning further experimental studies.
Due to digitalization and rapid development of collection techniques for elevation data, the emphasis of users' needs for elevation contours has moved from needs of accurate elevation assessment towards needs of perception of landforms. This article introduces a design approach that considers the changed need, and a solution for accordingly generating contours for topographic maps from digital elevation models (DEMs). The solution builds upon comprehensively modifying and blending complete DEMs in order to make the generation procedure understandable for the map readers and to facilitate the readers' reliable interpretation of contours throughout the depicted terrain. The core of the solution is blending lightly and strongly smoothed DEMs according to the Topographic Position Index (TPI) that measures local deviation from surrounding variations of elevations. The solution is built to continuously consider the requirements for different levels of smoothing in areas of uniformly varying and locally deviating relief. An initial case study for typical and challenging Finnish terrains is described and success of the solution is qualitatively evaluated based on the resulting contours. Eventually, limitations of the solution as well as further evaluation and refinement needs are outlined with an intention to prepare the presented contour generation procedure for production. RÉSUMÉEn raison de la numérisation et du développement rapide des techniques de collecte de données d'élévation, la priorité des besoins utilisateurs en matière de courbes de niveaux a évolué d'un besoin en vérification de la précision de l'altitude vers le fait de pouvoir percevoir les formes du terrain. Ce papier présente une approche conceptuelle qui considère ce changement de besoin ainsi qu'une solution pour générer des courbes de niveaux pour des cartes topographiques à partir de modèles numériques de terrain (MNT). La solution est construite sur une modification complète et une fusion de MNTs afin de rendre la procédure compréhensible pour le lecteur de carte pour faciliter l'interprétation fiable des courbes de niveau par le lecteur sur tout ARTICLE HISTORY
Users prefer more realistic visualizations, even though they may be less efficient or even detrimental for a given task. In some previous studies, the evidence has shown that relief shading facilitates the landform interpretation while other studies have provided contrary results. In the present study, the effect of three different visualizations of elevation information on eye movements and performance was investigated in visual search, area selection, and route planning tasks. The results showed that the visualization of relief information affected the performance and eye movements in the visual search task. Overall, the eye movements differed between the search and area selection tasks, as well as between the search and route planning tasks. The result showed that the relief shading did not slow down the performance, either in terms of response time or eye movement measures.
Geospatial images, such as maps and aerial photographs, are important sources of spatial knowledge that people use for wayfinding. The rapid development of geodata acquisition and digital graphics has recently led to rather complete geographic coverage of both traditional and novel types of geospatial images. Divergent types of geospatial images vary in their support of human acquisition of spatial knowledge. However, evaluative studies about the acquisition of spatial knowledge from the diversity of geospatial images have been rare. In this article, we review a variety of literature about the acquisition of spatial knowledge while paying particular attention to the role of geospatial images. Based on the literature, we present a framework of image parameters that characterize the acquisition of spatial knowledge from geospatial images: vantage point, number of visible vertical features, and visual realism. With the help of the framework, we evaluate commonly used geospatial images. In concordance with the previous experiments, our evaluation shows that the different types of geospatial images have large differences in the types of spatial knowledge they support and to what extent. However, further experimentation is needed in order to better understand the human cognitive needs for geospatial images and to develop more useful geospatial images for wayfinding
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