In geomorphology, PhotoScan is a software that is used to produce Digital Surface Models (DSMs). It constructs 3D environments from 2D imagery (often taken by Unmanned Aerial Vehicles (UAV)) based on Structure-from-Motion (SfM) and Multi-View Stereo (MVS) principles. However, unpublished computer-vision algorithms used, contain random elements which can affect the accuracy of the outputs. For this letter, ten model runs with identical inputs were performed on UAV imagery of a rock glacier to analyse the magnitude of the variation between the different model outputs. This variation was quantified calculating the standard deviation of each cell value in the respective DSMs and derivatives (curvature). Places with steep slope gradients have considerably more DSM variation (up to 10 cm) but stay within the range of the model's accuracy (10 vertical cm) for 88-96% of the area. The edges of the model also show a larger variability (0.10-3 m), related to a lower number of overlapping images. These results should be accounted for when performing a geomorphological research at centimetre scale using PhotoScan, especially in areas with a complex relief. Using medium-quality runs, additional oblique viewpoints and respecting a minimum of five overlapping images can minimize the software's variations.
To be able to design indoor wayfinding systems that adhere better to the needs of the users, user perception on complexity needs to be examined and linked to user characteristics and decision point characteristics. To identify how these characteristics influence perception, an online survey is executed in which participants had to indicate how complex they found a decision point, while interpreting a route instruction. The results show that complexity ratings depend both on user characteristics and on the function of the decision point. Decision points to change levels, start or end a route and to take turns each received significantly different complexity ratings. Isovist and visibility graph analysis characteristics of these decision points show that the first two actions were perceived as more complex when they took place in a narrow hallway, while the third action was perceived as more complex in a convex space. The results of this study can be used in the design of an adaptive wayfinding system that adapts the route instructions to the perceived decision point complexity. This adaptation will adhere better to the needs of the users compared to an adaptation based on solely theoretical complexity.
More and more digital 3D city models might evolve into spatiotemporal instruments with time as the 4th dimension. For digitizing the current situation, 3D scanning and photography are suitable tools. The spatial future could be integrated using 3D drawings by public space designers and architects. The digital spatial reconstruction of lost historical environments is more complex, expensive and rarely done. Three-dimensional co-creative digital drawing with citizens’ collaboration could be a solution. In 2016, the City of Ghent (Belgium) launched the “3D city game Ghent” project with time as one of the topics, focusing on the reconstruction of disappeared environments. Ghent inhabitants modelled in open-source 3D software and added animated 3D gamification and Transmedia Storytelling, resulting in a 4D web environment and VR/AR/XR applications. This study analyses this low-cost interdisciplinary 3D co-creative process and offers a framework to enable other cities and municipalities to realise a parallel virtual universe (an animated digital twin bringing the past to life). The result of this co-creation is the start of an “Animated Spatial Time Machine” (AniSTMa), a term that was, to the best of our knowledge, never used before. This research ultimately introduces a conceptual 4D space–time diagram with a relation between the current physical situation and a growing number of 3D animated models over time.
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