Detection of Slope Instability using 3D LiDAR Modelling

Transcription

1 Detection of Slope Instability using 3D LiDAR Modelling Duffell CG 1, Rudrum DM 2 and Willis MR 3 1 Technical Adviser (Geotechnics), Highways Agency. City Tower, Piccadilly Plaza, Manchester, M1 4BE, United Kingdom. (Tel) +44 (0) (E) chris.duffell@highways.gsi.gov.uk 2 Associate Director, Arup. 13 Fitzroy Street, London, W1T 4BQ, United Kingdom. (Tel) +44 (0) (E) mark.rudrum@arup.com 3 Principal Engineer, Arup. 13 Fitzroy Street, London, W1T 4BQ, United Kingdom. (Tel) +44 (0) (E) matthew.willis@arup.com Abstract The Highways Agency (HA) in the United Kingdom is responsible for managing the 7,088 km motorway and trunk road network in England. As part of the development of a pro-active asset management strategy to improve the safety and reliability of the roads network, the HA are developing the use of airborne remote sensing techniques to assist in prioritising their detailed ground based inspections of earthworks 1. This paper will describe one particular area of progress, namely the use of sets of LiDAR survey data to identify change in slope profile both qualitatively and quantitatively as a measure of slope condition. Introduction The Highways Agency (HA) in the United Kingdom is an executive agency of the Department for Transport (DfT) and is responsible for managing the 7,088 km core motorway and trunk road network in England on behalf of the UK Secretary of State for Transport. Although the network only forms around 4% of the total road network in England it carries nearly a third of all traffic and up to two thirds of all freight. Allowing for junctions and earthworks such as noise bunds, it is estimated that the HA has a linear total of about 16,000km of earthworks to manage. Earthworks Asset Management Tools and Techniques Serviceability failures of earthworks on the HA network occur on a regular basis, primarily in clay soils due to long-term changes in strength and pore pressures. The most recent figures available (Patterson & Perry, 1998) indicate that at this time the Highways Agency was spending upwards of 12m per annum direct costs on reactive slope repair and that year after year costs were rising significantly. The slips themselves rarely disrupt traffic flow but in recent years the cost of repairs has increased both in terms of direct cost (for example damage to communications cables and noise barriers founded on the earthwork) and indirect cost from disruption to the traveling public caused by lane closures for repairs. Highways Agency Geotechnical Data Management System To combat the consequences of earthworks failures the HA is developing a comprehensive asset database (Highways Agency Geotechnical Data Management System - HAGDMS) with inventory and condition information on the network earthworks. In due course, HAGDMS will assist the prediction of earthworks condition and allow pro-active maintenance to earthworks to be planned, budgeted and implemented before significant failure. Earthworks Condition Data The HA network is divided into 14 Areas, each with a Managing Agent (MA) team working with the HA to manage the network in that area. One of the MA duties is to undertake detailed inspections of earthworks assets and 1 Duffell et al. Remote Sensing Techniques for Highway Earthworks Assessment ASCE Geo-Frontiers Texas

2 to populate the HAGDMS database in their area. These principal inspections are to be undertaken at least every 5 years by qualified geotechnical engineers and are supplemented with lower level annual defect inspections by nongeotechnical staff. Both types of inspection are generally carried out from the ground with various combinations of slow moving vehicle on the carriageway and walkovers. Aerial Laser Scanning (LiDAR) Since 2000 the HA has been researching the use of remote sensed data sets to assist in the management of the highways network (Duffell et al 2005). This work concluded that airborne laser scanning (LiDAR) techniques in combination with vertical photography, appeared to offer the most promising opportunity for rapidly obtaining detailed earthworks inspection data. In the LiDAR system, laser pulses are emitted from a source mounted under an aircraft (either fixed wing or helicopter) and are directed downwards in a scanning pattern creating a swath of laser pulses. The laser pulses are reflected back to a receiver by the ground surface and other objects on the ground in the laser swath. The time taken for the laser pulses to return to the aircraft is recorded and provides a distance measurement from the aircraft. The aircraft is fitted with a global positioning system (GPS) and onboard Inertial Measurement Units (IMU) which are used to relate the aircraft position and hence the laser points to the world geoidal reference system WGS84. This is then transformed to a national grid system such as UK OSGB. Ground reference GPS stations are also used at 5-10km intervals to provide local survey reference to the national survey network. The resultant output is a 3-D point cloud of data points with each point georeferenced. This point cloud of data is then processed to products such as CAD drawings or types of digital ground surface model to suit the application. The key advantages of all LiDAR systems are that they provide a means of rapidly obtaining spatial data on assets with minimal initial ground support and that the data can then be economically processed into a number of different specific products without requiring additional ground work. Application of Remote Sensed Data Three key areas for the use of remote sensed data for earthworks asset management can be identified, namely; use in preparing an initial earthworks asset inventory; use in rapidly providing an indication of earthworks condition over a large length of earthworks to assist in prioritising inspections; and detailed evaluation at specific sites. Earthworks Asset Inventory Patterson (2002) has estimated that approximately 50% of the cost and time of earthworks inspections is associated with obtaining the initial earthwork geometry in terms of location, height and slope angle. In addition to cost and time savings, having inventory data before the inspection has important safety benefits in that it reduces the exposure of staff to the risks of working near live carriageways and allows a more complete understanding of the earthworks asset to be achieved earlier than conventional means. HA research by Arup et al (2004) identified that digital ground models from remote sensed data sources such as aerial photography and LiDAR had sufficient resolution to allow an initial or first pass population of earthwork inventory for the entire network to be produced without ground inspection or bespoke survey. HAGDMS is due to be populated using this method during Earthworks Asset Condition The key aim of initial HA remote sensing research was to identify a means of rapidly identifying the location of earthworks defects. The research considered various remote sensing techniques and concluded that the use of LiDAR data, processed to give a 3D contour representation of earthworks, was a simple and effective means of identifying the location of possible slope instability (Arup 2001, 2003, 2004). HAGDMS has standard GIS browser capability with the ability to overlay geo-referenced data sets, and to zoom / pan along the network. Accordingly, the 3D contour data sets from LiDAR data, together with accompanying orthorectified aerial photography, are being loaded directly into HAGDMS to assist geotechnical engineers in prioritising locations for more detailed inspection. An example of the contour data and its presentation in HAGDMS is shown in Figure 1. The HA research identified that the absolute positional accuracy of LiDAR data raised the possibility that repeat LiDAR surveys of the same area, say several months or years apart, could be compared digitally and changes in ground elevation due to say, slope instability, be identified automatically. This would potentially allow changes 2

3 to be automatically highlighted to the asset manager and inspections to be effectively focused on these areas of change. Figure 1a Figure 1b 3D Ground Contours generated from LiDAR data showing slip locations As part of the HA research trials (Arup 2004), two repeat LiDAR surveys, one year apart, of a trial area on the M25 London Orbital Motorway were undertaken using a helicopter based system. For each survey a digital terrain surface model was created after filtering to remove trees, structures, buildings and similar features. By adopting a suitable threshold difference to take account of the accuracy of the LiDAR system, differences in elevation between the 2002 survey and the previous 2001 survey were derived. The results are shown in Figure 2, with zones of settlement shown in green and zones of rise shown in red. This area is in fact a location of an ongoing slope repair where between 2001 and 2002 the slope has been re-profiled and blue tarpaulins laid to protect the slope from water ingress. The cross-section clearly shows the differences in elevation associated with further excavation at the face and filling at the toe of the slope. Figure 2a aerial imagery of change detection trial area showing slope repairs Figure 2b Corresponding differences in elevation identified by automated change detection routine At the time of writing the HA is undertaking further research into automated change detection. In particular the research is seeking to clarify the achievable resolution (what is the smallest change that can be measured?) and the precision (how reproducible and repeatable is the measurement?) of LiDAR change detection. 3

4 Site Specific Assessment Where LiDAR data is acquired on a site specific basis, data collection can be tailored to suit particular requirements. For a heavily wooded hillside site adjacent to main trunk road, topographic survey data was required to identify the extent of a historic landslip. The site is shown in Figure 3. Figure 3a Landslip site note helicopter with LiDAR Figure 3b Typical vegetation density at site One of the key advantages of LiDAR is that with sufficient density of laser scan points, LiDAR returns from beneath a vegetation canopy will be recorded. This allows the ground profile beneath wooded slopes to be identified. For this particular application a low-level helicopter LiDAR system was employed, flying over the site to achieve a point density in excess of 150 points / m². The resulting ground surface model is shown as Figure 4, clearly delineating the extent of the landslip and providing topographic survey data for use in the remedial works design. Figure 4a Cross-section from LiDAR data showing tree profiles and ground surface Figure 4b 3-D Ground surface model from LiDAR data showing extent of landslip 4

5 Wider use of Geospatial Data The HA research into the use of remote sensing techniques earthworks inspection (Arup 2004) concluded that as well as potentially improving safety and reducing road works requirements, the geospatial data itself had a wider application in the HA than simply earthworks management. In particular it was identified that recent remote sensing techniques had potential advantages in terms of rapid data collection, a reduced requirement for ground based asset survey activity and the potential for archiving asset data to allow interrogation by multiple users. This has directly led to the use of LiDAR to collect asset information and topographic survey data for a number of significant design, build, finance and operate highway projects, including enhancement of the M25 London Orbital Motorway (Colgan et al 2006). Conclusions The Highways Agency research has identified that LiDAR data can be used by geotechnical engineers to assist in their management of earthworks. Key benefits are seen as being the use of such digital terrain data to provide an initial asset inventory and indication of a condition prior to visiting site. The research has led to the wider use of geospatial data in the HA and the collection of data such as LiDAR for multiple uses ranging from geotechnics to topographic survey and noise assessment. Acknowledgements This paper is published with the permission of the Highways Agency. The authors express their thanks to the various parties who contributed and supported the work detailed herein, and in particular: Messrs John Sherwood and David Gingell, Highways Agency Major Projects Directorate, Birmingham; Mrs Sue Housley, Highways Agency, Major Projects Directorate, Leeds; Mr George Crawshaw, Highways Agency, Procurement North, Leeds; Mr Nick Butler, Mouchel Parkman Manchester. References Arup (2001) Development of remote rapid assessment techniques for the Geotechnical Asset. Research Project 3/303 Report on Phase 1 Research, Arup unpublished project report for Highways Agency, December 2001, London Arup (2003) Development of remote rapid assessment techniques for the Geotechnical Asset. Research Project 3/303 Report on Phase 2A Research, Arup unpublished project report for Highways Agency, April 2003, London Arup, Mott MacDonald, Infoterra and KeyNetix (2004) Rapid Remote Assessment Project - Development of Procedures for adding Earthwork Geometry to the Geotechnical Data Management System (HAGDMS), Arup unpublished project report for Highways Agency, February 2004, London. Arup (2004) Development of remote rapid assessment techniques for the Geotechnical Asset. Research Project 3/303 Report on Phase 2B Research, Rev 1-04, Arup unpublished project report for Highways Agency, April 2004, London Colgan, E, Duffell, C.G., Rudrum M (2006) Highways Asset Data from Airborne Laser Scanning, Paper submitted to Transportation Research Board for Jan 2006 Conference in Washington DC. Duffell, C.G.; Rudrum, D.M. and Willis, M.R.(2005) Remote Sensing Techniques for Highway Earthworks Assessment ASCE Geo-Frontiers 2005 Austin, Texas Jan 24-26, 2005 Patterson, D and Perry, J (1998) Geotechnical data and asset management systems for highways, In : Proc. of the maintenance engineers conference. Nottingham, September 1998, Surveyor and Municipal Journal, London Patterson, D (2002) Review of costs associated with implementation of new Maintenance Standard for Management of the Geotechnical Asset (HD 41/03). Internal Note Highways Agency TAG (Geotechnics) 7 October