Airborne altimetric LiDAR for topographic data collection: Issues and applications

Airborne altimetric LiDAR for topographic data collection: Issues and applications


Bharat Lohani
Phd, Department of Civil Engineering
Institute of Technology
Banaras Hindu University, Varanasi – 221 005
Tel: 0542-307-016# 47 Fax: 0542-368-174
Email: [email protected]

Airborne Altimetric LiDAR, despite its recent emergence, has become an industry-standard-tool for collecting high-resolution topographic data. This paper briefly describes the principle and technical issues related with this technology and as well its advantages. Further, the varied application areas where this technology has been successfully employed are reviewed. An assessment is also made of the other application areas where there is a great potential of using this technology. The paper also outlines the commercial and scientific potential of this technology, particularly in Indian reference and raises issues regarding the use of this technology in India.

1. Introduction
Topographic data have been the core of any Geographical Information System (GIS) project. The accuracy and functionality of many GIS projects rely to a large extent on the accuracy of topographic data and the speed with which it can be collected. Furthermore, the data collection consumes a major slice of the project resources in terms of both time and finance. Topographic data collection, therefore, assumes considerable significance and forms an integral part of a GIS project.

The conventional methods of topographic data collection include land surveying and aerial photogrammetry. More recently, attempts have been made to use satellite stereogrammetry for this purpose. However, all the above techniques have limitations in terms of their accuracy, cost-effectiveness, time-consumption, feasibility, and applicability. The recently emerged technique of airborne altimetric LiDAR has gained considerable acceptance in both scientific and commercial communities as a tool for topographic measurement. This technique has the potential to remove several bottlenecks imposed by earlier methods.

2. Principle of LiDAR
The basic concepts of airborne LiDAR mapping are simple. The airborne LiDAR instrument transmits the laser pulses while scanning a swath of terrain, usually centred on and co-linear with, the flight path of the aircraft in which the instrument is mounted. The scan direction is orthogonal to the flight path. The round trip travel times of the laser pulses from the aircraft to the ground are measured with a precise interval timer. The time intervals are converted into range measurements, i.e. the distance of LiDAR instrument from the ground point struck by the laser pulse, employing the velocity of light. The position of aircraft at the instance of firing the pulse is determined by differential Global Positioning System (GPS). Rotational positions of the laser pulse direction are combined with aircraft roll, pitch, and heading values determined with an inertial navigation system (INS), and with the range measurements, to obtain range vectors from the aircraft to the ground points. When these vectors are combined with the aircraft locations they yield accurate coordinates of points on the surface of the terrain. A typical LiDAR campaign involves the following steps:

  1. Flight planning i.e. fixing LiDAR instrument and aerial platform parameters to control the density and coverage of topographic measurements.
  2. Fixing ground control points (GCPs) to place reference receivers for differential GPS positioning.
  3. Instrument calibration– pre, during, and post-flight– to ensure accuracy of data collected.
  4. Data collection i.e. obtaining INS, GPS, laser range and scan measurements.
  5. Data processing to determine aerial platform location using GPS and INS measurements and combining it with laser range and scan measurement to yield triplets i.e. x, y, and z for each ground point struck by the laser in WGS-84 system.
  6. Quality assurance/quality check to determine and quantify the errors present in data and, if needed, elimination or minimisation of the errors.
  7. Generation of data products i.e. DSM, DEM, contour plots, 3D visualisations, and fly-throughs.

3. Advantages of LiDAR

  1. Accuracy: An accuracy of order of 10 – 15 cm in the vertical and 50 – 100 cm in the horizontal is claimed by manufactures and has been demonstrated by many field studies.
  2. Time of data acquisition and processing: The data capture and processing time is significantly less for LiDAR compared to other techniques. LiDAR can allow surveying rates of up to 90 km2 per hour (Environment Agency, 1997) with post-processing times of two to three hours for every hour of recorded flight data (Martin and Gutelius, 1997).
  3. Minimum user interference: User interference is minimum, as most of the data capture and processing steps are automatic except the maintenance of the ground GPS station.
  4. Weather independence: LiDAR is an active sensor and can collect data at night and can be operated in slightly bad weather and low sun angle conditions, which prohibit the aerial photography.
  5. Additional data: Besides relief information, laser reflectance may be used to generate intensity images to help in classifying the terrain features (Schreier et al., 1985). Further, the systems can have fluorosensors allowing pollutant identification and chlorophyll mapping (Environment Agency, 1997; Measures, 1984).
  6. Canopy penetration: Unlike photogrammetry, LiDAR can see below canopy in forested areas and provide topographic measurements of the surface underneath. Additionally, LiDAR generates multiple returns from single pulse travel, thus providing information about understory.
  7. Data density: LiDAR has the ability of measuring subtle changes in terrain as it generates a very high data density ( due to firing of 2000 – 80000 pulses per second).
  8. Ground control point independence: Each LiDAR pulse is individually georeferenced using the onboard GPS, INS, and laser measurements. Only one or two GPS ground stations are required for improving the GPS accuracy by the differential method. Independence from GCPs makes it an ideal method for inaccessible or featureless areas like wastelands, ice sheets, deserts, forests, and tidal flats.
  9. Digital compatibility: Data produced from LiDAR flights are in digital format with Easting, Northing, and Altitude values of each laser target. This makes importing of data to GIS and other image processing packages straightforward.
  10. Cost: One of the major hindrances in the use of LiDAR had been the cost of the equipment. However, in recent years the purchase price of these instruments has been reduced so that cost is no longer a barrier to companies capable of investing in standard aerial photogrammetry equipment (Martin and Gutelius, 1997). Furthermore, with more and more users opting for LiDAR the cost of the system and operation is likely to go further down. Mason et al. (1999), on the basis of overall performance evaluation of available topographic techniques for coastal terrain, found that LiDAR could achieve good performance at a lower cost.

4. Review of LiDAR applications

4.1 Floods
High-resolution and accurate LiDAR data are suitable for improving the performance of flood models by providing a more reliable initial boundary condition (Bates, 1999). LiDAR data having multiple returns help in generating and understanding the 3D structure of obstructions (i.e. surface roughness, vegetation, buildings, and other structures). This information can yield the friction coefficient over the various parts of a floodplain (Cobby, 1999). LiDAR data are also being employed for flood hazard zoning (Hill et al., 2000). FEMA (Federal Emergency Management Agency, US) is using LiDAR on a mandatory basis to create Digital Flood Insurance Rating Maps.

4.2 Coastal applications
LiDAR has generated considerable interest among coastal researchers as a topographic tool. Highly accurate, dense, and rapidly obtained data sets are most suitable for coastal applications like sediment transport, coastal erosion, and coastal flood models (Brock et al., 1997; Gutierrez et al., 1998).

4.3 Bathymetry
LiDAR in its bathymetric form can map the bed topography up to a depth of 70 m (Wehr and Lohr, 1999). This information is useful for determining the siltation on navigation canals and ports and planning the construction details.

4.4 Hydrology
LiDAR data can be used to quantify gully and stream channel cross sections and roughness, gully and stream bank erosion and channel degradation, to estimate soil loss from gully or channel banks and to measure channel and flood plain roughness and cross sections for estimating flow rates (Ritchie, 1996). Further, coastal channels which are difficult to map otherwise can be automatically quantified using LiDAR data (Lohani, 1999).

4.5 Glacier and avalanche
LiDAR has been found ideally suited for mapping glacial topography (Krabill et al., 1995; Kennett and Eiken, 1997) and ice velocities (Abdalati and Krabill, 1999). The above studies have amply shown that LiDAR can be used to monitor snow glacier movement, snow accumulation, and predict the onset of avalanche. The data set can further be employed to estimate the risk from a particular avalanche (Wehr and Lohr, 1999).

4.6 Landslides
LiDAR has made it possible to monitor and predict slope failure by rapidly obtaining highly accurate and dense elevation data. In post-slide conditions rapid damage assessment and mapping can be realised using LiDAR.

4.7 Forest mapping
The unique feature of LiDAR of producing multiple returns from the canopy top, understory, and the ground has attracted many to use it for estimating forest biomass, timber volume, and other parameters (Nelson et al., 1984).

4.8 Volcano monitoring
Ridgway et al. (1997) have shown that subtle systematic changes (uplift of up to 4 cm per year) in volcano dome height can be monitored from time to time using LiDAR.