Assessing Geomorphologic Processes with Permanent Laser Scanning

Abstract

Coastal areas are sensitive ecosystems, which are important as natural habitat, recreational areas and for protection of the hinterland. Coastal monitoring is essential in the analysis and prediction of coastal development. Coastal monitoring has become more urgent due to climate change and its effects on sea level and frequency of storm events. Permanent laser scanning (PLS) provides a tool to acquire 3-dimensional point clouds of an area nearly continuously over extended periods of time. PLS bridges the gap between incidental, in-situ measurement campaigns with high spatial detail, and frequent monitoring via satellite data at lower spatial resolution. Methods to process the complex high-resolution permanent laser scanning data are needed to find and analyse the effects of geomorphological processes over extended periods of time and with high spatial detail. This dissertation deals with the development of methods for spatio-temporal data mining of large 4D data sets from permanent laser scanning for the application of coastal monitoring on sandy beaches.

Two data sets of hourly 3-dimensional point clouds, acquired over periods of six months and three years at two different locations on the Dutch coast were analysed, to identify and assess geomorphological dynamics at the sediment surface. Each data set contains up to 20 000 epochs capturing the dynamics of the sandy beaches in Kijkduin and Noordwijk.

In this thesis two methods are developed: the application of multiple hypothesis testing for the estimation of minimal detectable bias and the generation of a so-called inventory of trends, and the application of clustering algorithms for grouping elevation time series. The first method using multiple hypothesis testing provides a means to define the minimal detectable bias for an expected model behaviour of time series from permanent laser scanning. This method provides a new way to detect small but persistent and statistically significant changes in longer time series derived from 3-dimensional point clouds. Using multiple hypothesis testing allows to identify linear changes with slopes of 0.032 m/day and sudden changes in elevation of 0.031 m with a given discriminatory power of 80% and significance level of 5% in 24-hour time series.

In an additional step, multiple hypothesis testing is used to reduce the complex permanent laser scanning data set to an inventory of trends, which consists of linear pieces of time series, matching the predefined statistical models and corresponding parameters. This method is applied to find and analyse times and areas where specific processes such as storms, aeolian sand transport or bulldozer works occur. The inventory of trends is particularly effective for the detection of aeolian sand transport, which has been difficult to identify using other coastal observations because it causes small, gradual deformations at the sediment surface.

The second method uses clustering algorithms to identify areas which are subject to similar change patterns. These change patterns are then easily associated with underlying physical and anthropogenic processes, mostly tidal induced changes and bulldozer works.

In summary, the developed methods allow to effectively detect deformations on sandy beaches and establish their origins, such as storms, tides, anthropogenic activities or aeolian sand transport, with a resolution and detail that has not been achieved until now. These results allow further analysis and interpretation of geomorphological coastal processes. For instance, the analysis of bulldozer works in our study area leads to the conclusion, that not only buildings themselves, but also the associated human interventions on the sandy beach around each building have a significant impact on coastal morphology and possibly lead to increased erosion.