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. @en

The Earth's landscapes are shaped by processes eroding, transporting, and depositing material over various timespans and spatial scales. To understand these surface activities and mitigate potential hazards they inflict, knowledge is needed of their occurrences and properties. Near-continuous terrestrial laser scanning (TLS) enables the acquisition of point cloud time series, constituting up to thousands of three-dimensional surface morphology representations. Exploiting the full potential of this large amount of data by extracting and characterizing different types of surface activities inside these point cloud time series is, however, challenging.

This thesis addresses this challenge by developing an automated and unsupervised method for classifying 4D objects-by-change (4D-OBCs). These 4D-OBCs represent the spatiotemporal extent of individual surface activities in a point cloud time series. They are classified using a Self-organizing Map (SOM) and hierarchical clustering, grouping them into different levels of surface activity types. The workflow is tested on its ability to characterize surface activities in two study areas, a sandy beach and a snow-covered Alpine area.

Application of an optimized SOM configuration on the sandy beach results in groups of 4D-OBCs physically interpretable as different types of surface activities. A validation dataset containing 51 manually labeled 4D-OBCs of various surface activity types (e.g., intertidal bar depositions, anthropogenic bulldozer depositions) is distributed over the SOM generally according to the labels provided. The SOM thus enables the identification of 4D-OBCs displaying a particular type of surface activity, as well as subtle differences between events of one surface activity. Hierarchical clustering allows us to find and characterize broader groups of surface activities, even if the same type occurs at different points in space or time. For example, the varying spatial redistribution of sand through the initiation of different types of surface activities after the destruction of an intertidal bar system under different environmental conditions is successfully studied.

A nearly identical workflow configuration applied on the snow cover 4D-OBC set does not result in equal performance. Several groups of surface activity in the SOM contain a combination of 4D-OBCs representing different surface activity types. These results highlight the necessity of a study area specific workflow optimization by selecting specific features and SOM configurations. However, if optimized for the specific environment, the workflow has the potential to be used in long-term automated monitoring of surface activity in systems with complex morphological interactions, increasing the applicability of TLS for studying geomorphological change.

Sea level rise causes more difficulties for coastal maintenance. Although hard structures were built in the past to prevent for flooding, nature based solutions are preferred more recently. For the application of nature based solutions, a better understanding of the coastal processes is desired. Dry sand is transported towards the dunes by aeolian processes, whose bedform development is understudied while knowledge on this is important. One of the most visually clear bedforms are organised dry sand over a moist beach, referred to as sand strips. In order to improve the knowledge on sand strips, this study focusses on sand strip properties and occurring environmental conditions during their presence at the Noordwijk beach, using data of a terrestrial laser scanning (TLS) device.

Sand strips are detected with the Fourier transform. Since surface moisture can be derived from the reflectance intensity of the TLS-data, and due to the different moisture content of the sand strips compared to the surrounding beach, the Fourier transform is applied on the reflectance intensity. Sand strips are detected based on the energy in the variance density spectrum for a wavenumber-range corresponding to sand strips. The detected sand strips were oriented alongshore to oblique-alongshore with a mean wavelength and height of 13.2 m and 4.0 cm respectively, which is in correspondence with similar sand strip-related studies.

According to sand samples of the beach the grain size varies in transverse direction of the sand strips, comparable with the grain size variation of aeolian sand ripples. The coarser grains were located at the crest and the finer grains at the lee-side. Additionally, the samples also showed a significant difference in gravimetric moisture content between the sand strips and surrounding beach, as expected due to the reflectance-based detection. At the sand strips, the maximum moisture content was 5.3%, while the minimum determined moisture content at the surrounding beach was 6.0%. The mean values were equal to 2.6% and 9.4% for the sand strips and surrounding beach respectively.

In addition, sand strips mainly occurred during (almost) alongshore wind events with a wind velocity in excess of 8 m/s. However, the threshold wind velocity for sand strip formation is determined at 10 m/s. Due to the significant height difference that can remain present during precipitation events, these events are not necessarily restrictive factors for sand strip development, although the reflectance intensity suggests different. Furthermore, sand strips mostly formed during falling tide and they were mostly destroyed during rising tide.

The one life cycle of the sand strips that is analysed showed dynamic sand strip behaviour. The migration rate of the sand strips varied over the width of the beach, causing more inland oriented sand strips. This dynamic behaviour cannot be related to weather conditions since they remained constant, however it could be related to topographic steering caused by the dune. Nevertheless, the results of the dynamic properties are only indicative and encourage further study of dynamic sand strip properties.

In recent years, our knowledge of coastal environments has been enriched by remotely sensed data. In this research, we co-analyse two sensor systems: Terrestrial Laser Scanning (TLS) and satellite-based Synthetic Aperture Radar (SAR). To successfully extract information from a combination of different sensors systems, it should be understood how these interact with the common environment. TLS provides high-spatiotemporal-resolution information, but it has high economic costs and limited field of view. SAR systems, despite their lower resolution, provide complete, repeated, and frequent coverage. Moreover, Sentinel-1 SAR images are freely available. In the present work, Permanent terrestrial Laser Scanning (PLS) data, collected in Noordwijk (The Netherlands), are compared with simultaneous Sentinel-1 SAR images to investigate their combined use on coastal environments: knowing the relationship between SAR and PLS data, the SAR dataset could be correlated to beach characteristics. Meteorological and surface roughness have also been taken into consideration in the evaluation of the correlation between PLS and SAR data. A generally positive linear correlation factor up to 0.5 exists between PLS and SAR data. This correlation occurs for low- or moderate-wind-speed conditions, whilst no particular correlation has been highlighted for high wind intensity. Furthermore, a dependence of the linear correlation on the wind direction has been detected. @en

Global climate change affects mountain regions such as the European Alps. Consequently, glacier extents decrease, and proglacial areas, the areas that recently lost their ice cover, increase in size. These proglacial areas are subject to a high frequency and magnitude of geomorphological activity and act as a sediment source for downstream fluvial systems, extending the influence of their activity beyond proglacial margins. Therefore, a good understanding of the geomorphological activity in these regions is important and subject to numerous studies. Challenges to access Alpine proglacial areas complicate collection of data with high spatial and temporal coverage. A permanently installed terrestrial laser scanner (TLS) overlooking the Hintereisferner glacier in the Ötztaler Alps (Austria) provides daily ranging observations of a proglacial area. The aim of this study is to assess the potential of this permanent laser scanning system for identifying geomorphological processes in proglacial areas. Point clouds of this TLS system were rasterised into range images. An automated registration method is developed to ensure alignment of large quantities of range images in the event of scanner movement. Scans of the 2020 and 2022 summer were combined into two 4D spatiotemporal datasets, allowing analysis of range change time series for each raster cell. A principal component analysis (PCA) of the 4D spatiotemporal datasets is used to explore spatial and temporal patterns of change in the observed proglacial area. The range image registration procedure performed slightly worse than conventional registration methods, but allowed for automated registration of large quantities of scans. Based on the patterns found in the PCA, as well as in the range time series and precipitation data, different geomorphological processes are identified in the observed proglacial area at daily time scales, with magnitudes of several meters. Among these processes are debris flows in gullies, and slumps on lateral moraines. These results demonstrate that characteristic patterns of topographical change can be distinguished using PCA, and PCA is a promising method to be used in other studies exploiting 4D spatiotemporal datasets. The identification of different geomorphological processes indicates that the permanent TLS system could be of use for further research on geomorphological activity in proglacial areas, such as reworking of lateral moraines, while the developed methodology could be used in other studies exploring 4D spatiotemporal datasets as well.

The European beach-dune systems are under increasing pressure due to urbanization, beach tourism and the effects of climate change like rising sea level and increased storm intensity. Building with nature solutions (Stive et al., 2013) are advocated as an effective and adaptable approach to protect sandy coasts in the future. This approach however interacts with the increased human use of the beaches- which can have an adverse impact on the efficiency of the building with nature approach. Especially permanent structures influence the natural sand transport dynamics from the beach to the dunes and can have long lasting effects on dune development. To obtain more insight into the influence of buildings on longer term dune development a 3-months ‘Scanex 2020’ field campaign was conducted (Poppema et al., 2021) on Noordwijk beach (52.24 °N, 4.42 °E) to monitor the natural sand development around two sea containers (see Figure 1). In addition on a larger scale the dune development around a permanent beach pavilion was monitored for two years (from August 2019 till August 2021) within the CoastScan project (Vos et al., 2017) with a permanent laser scanner. @en

The European beach-dune systems are under increasing pressure due to urbanization, beach tourism and the effects of climate change like rising sea level and increased storm intensity. Building with nature solutions (Stive et al., 2013) are advocated as an effective and adaptable approach to protect sandy coasts in the future. This approach however interacts with the increased human use of the beaches- which can have an adverse impact on the efficiency of the building with nature approach. Especially permanent structures influence the natural sand transport dynamics from the beach to the dunes and can have long lasting effects on dune development. To obtain more insight into the influence of buildings on longer term dune development a 3-months ‘Scanex 2020’ field campaign was conducted (Poppema et al., 2021) on Noordwijk beach (52.24 °N, 4.42 °E) to monitor the natural sand development around two sea containers (see Figure 1). In addition on a larger scale the dune development around a permanent beach pavilion was monitored for two years (from August 2019 till August 2021) within the CoastScan project (Vos et al., 2017) with a permanent laser scanner. @en

The Earth's landscapes are shaped by processes eroding, transporting and depositing material over various timespans and spatial scales. To understand these surface activities and mitigate potential hazards they inflict (e.g., the landward movement of a shoreline), knowledge is needed on the occurrences and impact of these activities. Near-continuous terrestrial laser scanning enables the acquisition of large datasets of surface morphology, represented as three-dimensional point cloud time series. Exploiting the full potential of this large amount of data, by extracting and characterizing different types of surface activities, is challenging. In this research we use a time series of 2,942 point clouds obtained over a sandy beach in The Netherlands. We investigate automated methods to extract individual surface activities present in this dataset and cluster them into groups to characterize different types of surface activities. We show that, first extracting 2,021 spatiotemporal segments of surface activity using an object detection algorithm, and second, clustering these segments with a Self-organizing Map (SOM) in combination with hierarchical clustering, allows for the unsupervised identification and characterization of different types of surface activities present on a sandy beach. The SOM enables us to find events displaying certain type of surface activity, while it also enables the identification of subtle differences between different events belonging to one specific surface activity. Hierarchical clustering then allows us to find and characterize broader groups of surface activity, even if the same type of activity occurs at different points in space or time.

@en

Coastal areas world wide are highly dynamic areas, subject to continuous deformation processes. Both natural and anthropogenic processes constantly cause changes at various spatial scales. Sandy beaches in the Netherlands fall under a regulation, according to which moving sand is permitted, if the volume change remains below a certain threshold. The threshold holds for volume changes within a cross section of 1 m width of the beach. The enforcement of this rule is currently labor intensive, because monitoring generally happens only on a yearly basis, or incidental and non-quantitative. Improved observation capabilities with remote sensing are advancing the supporting technology for this kind of regulations. Permanent laser scanning is a potential tool for monitoring and quantifying volume changes of a section of the beach. We develop and implement methodology to extract time series of volume change with respect to a reference date of 01-01-2020 covering January 2020 until the end of April 2020. The method is applied on point cloud data from a permanent laser scanner on the coast of Noordwijk, The Netherlands. We analyse the time series for incidents, where the threshold in volume change is passed, and find all shortest intervals during which the threshold is passed. Then we analyse potential underlying cause in order to support not only enforcement, but also evaluation of the current regulation. This will ultimately help to work towards a better understanding of the influence of small scale human activities on coastal development.

@en

Sandy shores worldwide suffer from coastal erosion due to a lack of sediment input and sea-level rise. In response, coastal sand nourishments are executed using ‘Building with Nature’ techniques (BwN), in which the sand balance is amplified and natural dynamics are instrumental in the redistribution of sand, cross- and alongshore. These nourishments contribute to the growth of beaches and dunes, serving various design objectives (such as flood safety, nature, and recreation). Nevertheless, human interference (such as buildings and traffic) along urbanized sandy shores may have significant, yet poorly understood, effects on beach and dune development. Better insight is required into the interplay of morphological, ecological and urban processes to support Aeolian BwN processes for dune formation and contribute to the sustainable design of urbanized coastal zones. This paper aims to bridge the gap between coastal engineering and urban design by formulating design principles for BwN along urbanized sandy shores, combining nourishments, natural dune formation and urban development on a local scale to strengthen the coastal buffer. The first part of the paper analyses sedimentation processes in the (built) sea-land interface and identifies spatial mechanisms that relate coastal occupation to dune formation. Hence a preliminary set of design principles is derived by manipulating wind-driven sediment transport for BwN dune formation after nourishment. In the second part of the paper, these principles are applied and contextualized in two case-studies to compare their capability for BwN in different coastal profiles: the vast, rural, geomorphologically high dynamic profile of a mega-nourishment (Sand Motor); versus the compact, highly urbanized, profile(s) of a coastal resort (Noordwijk). Conclusions reflect on the applicability of BwN design principles within different coastal settings (dynamics, urbanity) and spatial arrangements facilitating BwN dune formation.@en

Given the considerable range of applications within the European Union Copernicus system, sustained satellite altimetry missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to provide precision sea level, sea surface height, significant wave height, inland water heights and other products tailored to operational services in the ocean, climate, atmospheric and land Copernicus Services. Sentinel-6 provides enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon mission and follow-on Jason-1, Jason-2 and Jason-3 satellite missions. The mission is implemented through a unique international partnership with contributions from NASA, NOAA, ESA, EUMETSAT, and the European Union (EU). It includes two satellites that will fly sequentially (separated in time by 5 years). The first satellite, named Sentinel-6 Michael Freilich, launched from Vandenburg Air Force Base, USA on 21st November 2020. The satellite and payload elements are explained including required performance and their operation. The main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter that uses an innovative interleaved mode. This enables radar data processing on two parallel chains the first provides synthetic aperture radar (SAR) processing in Ku-band to improve the received altimeter echoes through better along-track sampling and reduced measurement noise; the second provides a Low Resolution Mode that is fully backward-compatible with the historical reference altimetry measurements, allowing a complete inter-calibration between the state-of-the-art data and the historical record. A three-channel Advanced Microwave Radiometer for Climate (AMR–C) provides measurements of atmospheric water vapour to mitigate degradation of the radar altimeter measurements. The main data products are explained and preliminary in-orbit Poseidon-4 altimeter data performance data are presented that demonstrate the altimeter to be performing within expectations.

@en

The advancement of permanently measuring laser scanners has opened up a wide range of new applications, but also led to the need for more advanced approaches on error quantification and correction. Time-dependent and systematic error influences may only become visible in data of quasi-permanent measurements. During a scan experiment in February/March 2020 point clouds were acquired every thirty minutes with a Riegl VZ-2000 laser scanner, and various other sensors (inclination sensors, weather station and GNSS sensors) were used to survey the environment of the laser scanner and the study site. Using this measurement configuration, our aim is to identify apparent displacements in multioral scans due to systematic error influences and to investigate data quality for assessment of geomorphic changes in coastal regions. We analyse scan data collected around two storm events around 09/02/2020 (Ciara) and around 22/02/2020 (Yulia) and derive the impact of heavy storms on the point cloud data through comparison with the collected auxiliary data. To investigate the systematic residuals on data acquired by permanent laser scanning, we extracted several stable flat surfaces from the point cloud data. From a plane fitted through the respective surfaces of each scan, we estimated the mean displacement of each plane with the respective root mean square errors. Inclination sensors, internal and external, recorded pitch and roll values during each scan. We derived a mean inclination per scan (in pitch and roll) and the standard deviation from the mean as a measure of the stability of the laser scanner during each scan. Evaluation of the data recorded by a weather station together with knowledge of the movement behaviour, allows to derive possible causes of displacements and/or noise and correction models. The results are compared to independent measurements from GNSS sensors for validation. For wind speeds of 10m/s and higher, movements of the scanner considerably increase the noise level in the point cloud data.

@en

Landslides endanger settlements and infrastructure in mountain areas across the world. Monitoring of landslides is therefore essential in order to understand and possibly predict their behavior and potential danger. Terrestrial laser scanning has proven to be a successful tool in the assessment of changes on landslide surfaces due to its high resolution and accuracy. However, it is necessary to classify the 3D point clouds into vegetation and bare-earth points using filtering algorithms so that changes caused by landslide activity can be quantified. For this study, three classification algorithms are compared on an exemplary landslide study site in the Oetz valley in Tyrol, Austria. An optimal set of parameters is derived for each algorithm and their performances are evaluated using different metrics. The volume changes on the study site between the years 2017 and 2019 are compared after the application of each algorithm. The results show that (i) the tested filter techniques perform differently, (ii) their performance depends on their parameterization and (iii) the best-performing parameterization found over the vegetated test area will yield misclassifications on non-vegetated rough terrain. In particular, if only small changes have occurred the choice of the filtering technique and its parameterization play an important role in estimating volume changes.

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Sandy beaches are highly dynamic areas affected by different natural and anthropogenic effects. Large changes, caused by a storm for example, are in general well-understood and easy to measure. Most times, only small changes, at the centimeter scale, are occurring, but these changes accumulate significantly over periods from weeks to months. Laser scanning is a suitable technique to measure such small signals, as it is able to obtain dense 3D terrain data at centimeter level in a time span of minutes. In this work we consider two repeated laser scan data sets of two different beaches in The Netherlands. The first data set is from around the year 2000 and consists of six consecutive yearly airborne laser scan data sets of a beach on Texel. The second data set is from 2017 and consists of 30 consecutive daily terrestrial scans of a beach near The Hague. So far, little work has been done on time series analysis of repeated scan data. To obtain a first grouping of morphologic processes, we propose to use a simple un-supervised clustering approach, k-means clustering, on de-leveled, cumulative point-wise time series. The results for both regions of interest, obtained using k=5 and k=10 clusters, indicate that such clustering gives a meaningful decomposition of the morphological laser scan data into clusters that exhibit similar change patterns. At the same time, we realize that the chosen approach is just a first step in a wide open topic of clustering spatially correlated long time series of morphological laser scan data as are now obtained by permanent laser scanning.@en