Geological structure measurement by LiDAR technology is a remote sensing method applied in structural geology. It enables monitoring and characterisation of rock bodies. This method's typical use is to acquire high resolution structural and deformational data for identifying geological hazards risk, such as assessing rockfall risks or studying pre-earthquake deformation signs.
Geological structures are the results of tectonic deformations, which control landform distribution patterns. These structures include folds, fault planes, size, persistence, spatial variations, and numbers of the rock discontinuities in a particular region. These discontinuity features significantly impact slope stability, causing slope failures or separating a rock mass into intact rock blocks (rockfall). Some displaced blocks along faults are signs of earthquakes.
Conventionally, geotechnical engineers carried out rock discontinuity studies manually. In post geological hazards studies, such as rockfall, the rockfall source areas are dangerous and are difficult to access, severely hindering the ability to carry out detailed structural measurements and volumetric calculations necessary for hazard assessment. By using LiDAR, geological structures can be evaluated remotely, enabling a 3D investigation of slopes with virtual outcrops.
LiDAR technology (Light Detection and Ranging) is a remote sensing technique that obtains precise 3D information and distance. The laser receptor calculates the distance by the travelling time between emitting and receiving laser pulses. LiDAR produces topographic maps, and it is useful for assessing the natural environment.
Useful Links LiDAR Strike and Dip Related DisciplinesGeologyRemote Sensing PortalEarth Sciences Portal __TOC__
Importance of measuring geological structures by LiDAR
Geological structures are responsible for providing distinct physical properties to rock masses. Discontinuous properties and plate tectonic forces may alter rock masses and their geometries. These structures contain joints, fractures, bedding planes, shear zones, mechanical breaks, or any other features ranging from microscopic (<1 cm, foliation development by metamorphism) to macroscopic scale (>100m, mid-oceanic ridges).
Geological structures are typically elongated, their orientations are often described as "strike". If a rock body is extensively tilted, taking its slope resistivity into account, it may have a high potential to cause rockfalls. The use of LiDAR in the structural analysis allows measuring landform features from a single outcrop scale to a terrestrial scale. Some geological structures measurement and their importance are listed below:
Rock plane orientation measurement and rockfall risk assessment Rock plane orientations are the natural inclinations that occurred on a rock plane. Some examples of rock planes are bedding planes, fault planes. The planes' orientations are measured by dip and dip direction with a clinometer and compass, where dip represents the maximum inclination of a plane to the horizontal, dip direction is the direction of the intersection line between horizontal and the inclined plane. A stereonet can visualise the distribution of dip and dip directions to analyse the kinematics of a slope.
Kinematics represents the motion of a rock body without external forces that cause them to move. Kinematics analysis concentrates on the possibility of translational failures due to planes sliding although other types of failure modes, such as wedge and toppling failures, can also be recognized.
Faults behaviours measurement and earthquakes predictions Faults behaviours can be used to measure the rate of sediment transportation and predict earthquakes. An earthquake can contribute to the formation of faults scraps. One side of a block will be relatively upthrown, causing vertical displacements. Therefore, given the parameters of fault scraps, structural geologists are able to trance the age of it and deduce the time involved to form such features.
Earthquakes are initiated by slow slips. Slips are the displaced blocks along two sides of a fault. However, these slips are undetectable by seismometers (maximum 5mm/day). When the slipping blocks reach a critical rupture velocity, the faults would gradually evolve into a final quake size by linear acceleration along fault planes. The critical displacement of faults is proportional to the initial rupture velocities.
After collecting LiDAR data from pre-earthquake and post-earthquake landforms, by constructing 3D digital terrain models, the displacement and deformations can be derived. Thus, scientists can predict the final earthquake scale in the future by determining faults and slips' characteristics and areas' size, and short-term earthquake predictions are possible.
Surface processes and geological mapping When carrying out geological mapping, interpretations through aerial photographs and satellite imagery are often used, but forest vegetation remained the major challenge for mapping. For example, characterising physical landform features at ridges and valleys are somehow complicated, many of these features are forest-covered. The topographic maps are then constructed by obtaining data manually.
LiDAR provides the full-waveform system, it enables the laser pulse to penetrate canopies and vegetations. This system allows obtaining bare-ground geological data points. Webster et al. have discovered new craters in Northern Canada by harnessing LiDAR data and digital terrain models. A digital terrain model has to be constructed to measure structural parameters (tilt angles, river incision depths). With the precise bedrock and surficial lithology mapping by LiDAR, structural geologists can reconstruct surficial processes involved.
Traditional structural measurement Traditional structural orientations can only be assessed on reachable exposed rock mass manually. Conventionally, engineering geologists investigated rock discontinuities studies with only a limited number at a time. The discontinuities may not represent the whole outcrop. Thus, the traditional rock plane orientation measurement may contain bias.
Geotechnical studies also investigate other geomechanical parameters, such as persistence, block size and rock joint spacing.
LiDAR technology LiDAR (Light Detection and Ranging) is a rapid surveying process that emits and receives laser pluses to acquire 3D information. By illuminating lights with different wavelengths to the object of interest, LiDAR can be used to create precise topographic maps, with applications in: geology, geomorphology, surveying and other applications. Topographic maps are possible because of the Inertial Measuring Unit and Global Positioning System. Furthermore, it is a technology that can carry out studies on a steep slope and rock-cliffs.
Accurately measured data is necessary for the LiDAR data to be geo-referenced such as locating the data in a local or global coordinates system. Therefore, the produced LiDAR can be overlaid onto the aerial photographs collected previously to observe the topography changes over time.
Principle of LiDAR LiDAR system emits pulsed and continuous-wave lasers to acquire 3D information. The laser scanner is the main component of LiDAR. Lasers with a wavelength of 550-600 nm are used on a ground-based system (handheld laser scanning and terrestrial laser scanning), whereas airborne systems use lasers with 1000-1600 nm wavelength.
Laser calculates the reachable range by the following formula:
R represents Range in meters c represents speed of light in m/s t is the travelling time of a laser pulser in seconds
LiDAR receives information by discrete and full-waveform return. Full-waveform (multi-return) is often used for forest analysis by Airborne LiDAR, while discrete return (single return) is used by a ground-based laser scanning method. A laser is reflected whenever it reaches any surfaces. The full-waveform return is able to penetrate down into canopies and return vegetation information at different heights. Discrete return can only return the superficial materials. Thus, airborne LiDAR is often used for forestry studies.
Data representation and data format LiDAR data is mainly stored in a point cloud format(.las). The captured point cloud data store X, Y Z geometric data. Each data point is obtained from a single laser scan and represents a local geo-referenced spatial datum. It can represent realistic and three-dimensional rock faces in a remote and inaccessible natural terrain.
The LiDAR data have the following parameters:
Each data point contains Co-ordinates (X, Y, Z co-ordinates in a local reference system) Each point has its associated color information(R, G, B format) The reflected intensity of the surface Possible automatic superposition of photographs onto point clouds (captured during scanning process) Any other hyperspectral data
These data help rock body features analysis, they include recorded geometrical or radiometric information of natural, excavated, or blasted rock slopes.
Previously, the LiDAR data are in the form of the American Standard Code for Information Interchange format(ASCII), which has several problems :
1) Low reading and interpreting speed of ASCII files
2) Useful data loss during data processing
3) ASCII is unstandardised
After 2003, the American Society for Photogrammetry and Remote Sensing (ASPRS) has standardized the LiDAR data in sequential binary laser(.las file) containing LiDAR or other point cloud data records.
Geo-referencing Geo-referencing means the co-ordinates on an aerial photograph/digital terrain model can be referenced on a global/regional geographic system. Thus, the users are able to determine and locate every point of collected data on the Earth's surface. The typical global positioning system uses the World Geodetic System of 1984(WGS84) datum, and stores the geo-referenced data in GeoTIFF/GeoPDF format. In addition, the users may require orthometric elevation (elevation above sea-level or geoid model) in different scenarios. For example, analysing sea-level change by hydrological data.
Geo-referencing can be done by adding control points at the base of the slope. By shifting the point cloud data onto the known correct co-ordinates with at least 3 points, the point cloud data can be repositioned into an accurate co-ordinate system. This information is useful for calculating distances, volume and areas.
Types of LiDAR LiDAR data can be collected on ground-based, airborne and mobile platforms. For example, Airborne LiDAR Scanning (ALS), Unmanned Aerial Vehicles (UAV), Terrestrial Laser Scanning (TLS) and Handheld Laser Scanning (HLS). The tables below will compare the mentioned data collection platforms:
1) The data collection methods
2) Geo-referencing technique (how to acquire the exact coordinate of a point)
3) Advantages and disadvantages +Sample images of different data acquisition methodsAirborne LiDAR Scanning (ALS)Unmanned Aerial Vehicle (UAV)Terrestrial Laser ScanningHandheld Laser Scanning An airborne LiDAR scanning system would scan the objects along its flight path with a zigzag pattern An Unmanned Aerial Vehicle can be controlled by a small scale remote control A terrestrial laser scanning method that stands on a flat and stable terrain A handheld laser scanning device with a small size, it is highly portable +A comparison of different laser scanning methodsLiDAR scanning methodsData collection methodsGeo-referencing techniqueAdvantagesDisadvantagesAirborne LiDAR Scanning (ALS) An airborne LiDAR system that emits lasers with a wavelength of 1000-1600 nm Data returned from a single pulse with multiple returns for classifying different objects according to canopy structure With a maximum 167 MHz laser repetition rate The distance can be calculated by LiDAR 2 way return time Point density can be more than 8 points/m2