Abstract

International audience; We detail an empirical animation study to assess how display design and user spatial ability and training might influence visuospatial decision-making with animated displays showing aircraft movements. We present empirical results of a visuospatial detection task with moving objects, based on response accuracy and response time, including a descriptive eye-movement analysis. We found significant differences in a visuospatial detection task of moving objects across animation design types and domain expertise levels based on viewers' visuospatial skill differences. With this empirical approach, we hope to better understand how users explore and extract information from animated displays. Based on these results, we aim to further develop empirically validated animation display design guidelines to increase their efficiency and effectiveness for decision-making with and about moving objects.; Nous présentons en détail une expérimentation évaluant des tâches utilisateurs dans un contexte de visualisation dynamique représentant des mouvements d'avions sur une interface de contrôle aérien. Nous cherchons à évaluer l'influence des principes d'affichage et du niveau d'expertise sur les aptitudes spatiales des participants à prendre des décisions. L'évaluation est basée sur l'exactitude des réponses données, le temps de réponse, et analyse descriptive des mouvements oculaires (eye tracking). Nous constatons des différences significatives dans la détection visuelle et spatiale d'objets en mouvement, selon le type d'animation et le niveau d'expertise des utilisateurs. À l'aide de cette expérimentation, nous espérons mieux comprendre comment les utilisateurs examinent, interprètent et extraient des connaissances à partir d'affichages dynamiques. À partir de ces résultats, nous souhaitons dégager des principes directeurs qui nous permettrons d'améliorer la conception d'animation, nous cherchons ainsi à accroître l'efficacité dans les prises de décisions des utilisateurs considérant la visualisation d'objets en mouvement.

Abstract

Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset (“ground truth dataset”). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions. Document type: Article

Abstract

The land use structure is a key component to understand the complexity of urban systems because it provides a snapshot of urban dynamics and how people use space. This paper integrates socially sensed activity data with a remotely sensed land cover product in order to infer urban land use and its changes over time. We conducted a case study in the Washington D.C.&ndash Baltimore metropolitan area to identify the pattern of land use change from undeveloped to developed land, including residential and non-residential uses for a period covering 1986&ndash 2008. The proposed approach modeled physical and behavioral features of land parcels from a satellite-based impervious surface cover change product and georeferenced Tweets, respectively. A model assessment with random forests classifiers showed that the proposed classification workflow could classify residential and non-residential land uses at an accuracy of 81%, 4% better than modeling the same land uses from physical features alone. Using the timestamps of the impervious surface cover change product, the study also reconstructed the timeline of the identified land uses. The results indicated that the proposed approach was capable of mapping detailed land use and change in an urban region, and represents a new and viable way forward for urban land use surveying that could be especially useful for surveying and tracking changes in cities where traditional approaches and mapping products (i.e., from remote sensing products) may have a limited capacity to capture change. Document type: Article