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Monitoring Coastal Instability using Airborne and Terrestrial LiDAR

By 08/02/2016

Monitoring coastlines is a challenging task, especially due to the typically inaccessible nature of the coastal terrain. With rapid erosion rates becoming commonplace, this is increasingly becoming an area of concern. To determine the associated hazards and potential impacts upon local infrastructure, it is important to measure the erosion rates which result in unstable slopes in coastal areas.

Study area map 72

Fig 1: Study Area Map

3D Laser Mapping and Durham University are demonstrating the benefits of integrating data collected from different sensors, on different time scales, to intensively monitor rock faces on the North-Yorkshire coast in the UK near the historic town of Whitby. The coastal cliffs in this area are formed from middle Lias rocks that consist of the interbedded mudstones, shales, siltstones, ironstones and sandstones that form the Staithes Sandstone and underlying Redcar Mudstone formations. Coastal instability in this area is significant, with regular rock fall and landslide events leading to elevated rates of coastal recession and associated hazards. It is a challenging and dynamic environment comprising both bare earth and heavily vegetated terrain.

The aim of the project is to understand the process through which wave erosion at the base of the cliffs causes undercutting of the cliff slope, resulting in an unstable cliff and failure of material into the sea. Using a combination of airborne laser scanning, photography, terrestrial laser scanning, weather sensors and monitoring software, this large scale monitoring project has allowed a much greater insight into the process of coastal erosion and rock fall.

Terrestrial scanning provides high resolution data (in time and space) that enables small changes in the slope to be identified very quickly that may be possible precursors to larger scale failures. The airborne survey gives a different dataset that is over a larger scale, lower resolution but at a much longer time interval, enabling larger scale changes to be assessed less frequently. This dataset is useful for looking at longer term, larger scale trends in the behaviour of the coast.

When combined, these data sets can be used to fully understand the movements and mechanisms of a studied rock face. As a result, the seaside town of Whitby now has one of – if not the most – intensively monitored coastal rock faces in the world.

The project is part of a KTP (Knowledge Transfer Partnership), a scheme funded by InnovateUK, which has a track record, improving businesses competitiveness, productivity and performance by accessing the knowledge and expertise available within UK Universities and Colleges.

Airborne Surveys for Large Scale Change 

Helipcoter used for aerial survey mounted with StreetMapper pod 72

Fig 2: Helicopter used for aerial survey mounted with StreetMapper pod

Two repeat surveys were captured at an interval of approximately ten months (August 2014 and June 2015) using a StreetMapper IV Mobile Mapping System (MMS) installed on a helicopter.

The MMS comprised a Riegl VQ-450 laser scanner coupled with an IGI AeroControl navigation system. The AeroControl system consists of an Inertial Measurement Unit (IMU-IIe) based on fibre-optic gyros and a Sensor Management Unit with integrated high-end GPS receiver. The VQ-450 laser scanner has a measurement rate of up to 500 kHz, a measurement range of up to 800 m and offers online-waveform processing enabling multiple targets to be detected for each individual laser pulse.

The laser scanner system was housed in a protective pod giving a 180 degree downward and sideways-looking field-of-view. The field-of-view enabled both the terrain surface (downward looking) and cliff faces (sideways looking) to be scanned. In addition to the laser scanning system, a downward-looking 36.3 megapixel Nikon D-800 camera with a 20 mm lens was also installed in the protective housing to capture optical imagery during the surveys. The average flying height for the surveys was ~100 m AGL giving laser measurement point spacing on the ground of ~15 cm and a GSD of ~1 cm for the optical imagery

(A) 3D coloured point cloud of study area. (B) Results of terrain surface classification - 72

Fig 3: (A) 3D coloured point cloud of study area (B) Results of terrain surface classification

Surface displacement velocity was derived by first using an automatic classifier on the online-waveform laser data to determine bare earth and vegetated terrain. This step was important as seasonal variation and growth of vegetation can limit the ability to consistently track corresponding terrain features in time-series image sets. The terrain classification approach used the online-waveform data from the laser scanner to identify areas of the terrain exhibiting more than one return per laser pulse. Pulses with multiple returns were assumed to be representative of vegetated terrain where backscatter is observed from more than one object (e.g. the ground surface and vegetation above the ground surface) and classified accordingly. Pulses with only a single return were classified as bare-earth.

(A) Match features (Using masked SIFT keypoints) between reference and comparision survey (B) Calculated 72

Fig 4: (A) Match features (Using masked SIFT keypoints) between reference and comparison survey. (B) Calculated displacement vectors.

To automatically detect and track the movement of key surface features between the two successive time-series image sets, the SIFT (Scale Invariant Feature Transform) feature tracking algorithm was implemented to determine the 2-D motion of features. The algorithm automatically identifies and tracks common features in successive time-series images to determine the 2-D displacement of each tracked feature. To limit the negative impact of vegetation on the surface displacement results, the terrain classification derived from the laser data was used to exclude any tracked features falling within areas classified as vegetation from the analysis. Three-dimensional displacement vectors for the final set of (non-excluded) tracked features were then derived by projecting the feature tracks onto the point cloud-derived reference surface.

3D surface distance comparison map 72

Fig 5: 3D Surface distance comparison map

Through combining surface elevation changes derived from laser data and displacement velocities calculated from images, it was possible to quantify both the magnitude of displacement, and the rate and direction over which the displacement occurred. The results demonstrate that laser scanning and automated feature tracking using images can be effectively combined to provide measurements of slope instability.

High Resolution Monitoring using SiteMonitor4D

The airborne survey provided displacement information over 23km of coastline and provided information on larger scale trends occurring over the whole area. However, in order to understand the detailed mechanisms of failure it is necessary to “zoom in” to a small area and undertake high resolution terrestrial laser scanning. SiteMonitor software from 3D Laser Mapping was used to automatically schedule the capture and analysis of high resolution 3D laser scans.

Continual and frequent measurement of the cliff face occurred using SiteMonitor over a 12 month period allowing changes resulting from rock fall to be recorded and analysed. Environmental data was captured alongside the laser scanned data, to try to understand the processes of coastal erosion by looking at projected increases in sea level and stormy weather. Whilst this process may at first glance appear straightforward, research by Durham University over the last decade has shown that this understanding is largely anecdotal. The linkage between waves and erosion evolves gradually through time, and is one that responds to a wide range of factors, and not just the action of waves alone.

Terrestrial laser scan data coloured by laser reflectivity, slope & aspect, to identify rock bands & vari 72

Fig 6: Terrestrial laser scan data coloured by laser reflectivity, slope and aspect to identify rock bands and variation in jointing pattern across the rock face (100m width)

The system was designed to scan the cliff face 24 hours a day at 30 minute intervals. Within each scan measurements of the cliff face are taken at approximately 10 cm intervals, generating over 2 million points per scan. Whilst this data capture is itself uniquely innovative, the analysis of such a large volume of information presents significant challenges. To overcome this, the system streams data live from Whitby to Durham, where the analysis is undertaken.

One of the outcomes of the KTP project between 3D Laser Mapping and Durham University, as the development of new algorithms to extract additional information from time-series 3D scan data in order to understand the slope failure mechanisms.

Moisture content on the rock face (due to seepage of water from the rock mass behind) is a significant factor in the prediction of slope failure. Each laser scan can show the moisture content and the time-series data can be used to show areas where there is increasing moisture therefore increasing risk of a failure. Data from the weather sensors was used to develop a correlation between rainfall and evidence of seepage into the rock face.

Terrestrial laser scan map of moisture content and seepage on the cliff face 72

Fig 7: Terrestrial laser scan map of moisture content and seepage on the cliff face

Combining Survey Methods for Greater Insight

Combining Terrestrial Laser Scanning (TLS) and Airborne Laser Scanning (ALS) projects gives both a detailed survey and a larger scale survey, both of which are important for developing better models of how coastal erosion happens. This improved insight will ultimately lead to better prediction and management of slope failure.
As has been demonstrated in this project, both SiteMonitor and StreetMapper can be used to provide a total monitoring solution, versatile enough for even the most challenging of environments.

The implications of the research is to move beyond Whitby and the coastlines of the UK. The more usual location of 3D Laser Mapping’s SiteMonitor system is in some of the world’s largest open pit mines, where rockfall and slope failure presents a significant challenge for sustaining mine productivity. The insight into the fundamental mechanics of how rockfall evolves, gained from the research at the cliffs in Whitby, is designed to be transferrable to these settings and enhance the reliability of slope failure early warning systems.

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