3D Point Clouds for Representing Landscape Change

Along with increasingly rapid changes of our present landscapes, exchangeable land use patterns are evolving that lead to decreasing identification of the people with their environment. To evaluate people’s perceptions of and reactions to possible future landscape development scenarios, we aimed to develop realistic-looking landscape depictions from a pedestrian perspective, including environmental sound. With this, we faced the challenge of how to most effectively and efficiently visualize potential landscape change scenarios. In this context, LiDAR (Light Detection and Ranging) data are a promising resource to create realistic landscape depictions. We present an innovative workflow combining 3D point cloud data collection and modelling with audio recordings for visualizing scenarios of landscape change. The focus is laid on the visualization process and the integration of various geographic data sets. In the discussion of the resulting workflow we consider strengths and weaknesses of our solution regarding data collection, as well as technical and ethical issues. Overall, the presented approach looks promising, but still requires a great deal of manual labor. We recommend to further develop the visualization workflow, for example, by speeding up the data acquisition process of the point cloud data, and by further automatization of the data processing steps.