Visual insight into the temporal changes of sand patterns along the Dutch coast, A contribution to detailed point cloud visualization for policymaking and research in coastal management

Abstract

Coastal management in the Netherlands is an important issue to avoid flooding. The coast is a dynamic system which changes through time. Changes in morphology do not only occur on the long term but also on the short term. Through monitoring, data is obtained for research, in this way information can be captured in coastal dynamics. With the use of LiDAR (Light detection and ranging) the elevation along the Dutch coast is measured. In this research is examined to which extend the application and visualization of the original measurements, consisting of point clouds, are useful for policy makers and researchers in providing visual insight into short- and long-term changes of sand patterns along the Dutch coast. Point cloud based visualizations of long term changes along the Dutch coast are visualized in the Hondsbossche Dunes and short term changes are visualized in Noordwijk. Point cloud measurements are possible to be visualized in 3D whereby detailed morphology can be displayed in a very high resolution on a large scale. Furthermore, these point cloud images are really close to reality because there is no information lost or added due to interpolation techniques. In addition, several visualization techniques, like shadow effects and the use of colour scales, are available to increase the quality of the visualization even more. There are however some disadvantages of using point clouds, such as the large volume of the datasets which can make it difficult to work with. There are techniques like point thinning or using continuous levels of detail to overcome this problem. Using point clouds does have an added value when visualizing detailed morphology on a large scale. Especially, on the short term, where changes in morphology are often small and thus need a high resolution to be visualized and where in a short period of time a high volume of data becomes available. Massive 3D point clouds can be updated, integrated, and accessed with much less effort than is required for the normal 3D models.