Of Light and Time

July 1, 2007
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One of the biggest challenges in modern remote sensing is to devise an assured means to achieve a high degree of accuracy in ground sampling, without undertaking a physical survey. Because airborne LiDAR (Light Detection and Ranging, or Laser Imaging Detection and Ranging) technology determines the distance to an object or surface using laser pulses, it is becoming more and more important in terrain applications and in acquiring remotely sensed topographical data.

This article provides a window for understanding a few of the many capabilities for LiDAR in resource management.



Because airborne LiDAR technology determines the distance to an object or surface using laser pulses, it is becoming more and more important in terrain applications and in acquiring remotely sensed topographical data.

Technology at a Glance

The LiDAR system basically consists of the integration of three technologies: Inertial Navigation System (INS), laser and GPS. A pulsed laser ranging system is mounted in an aircraft equipped with a precise kinematic GPS receiver and an INS. Solid-state lasers are now available that can produce thousands of pulses per second, each pulse having a duration of a few nanoseconds (the time it takes light to travel a few feet). The laser consists of an emitting diode that produces a light source at a specific frequency. The signal reflects off a feature of the Earth and back to the aircraft where a receiver captures the return pulse. With accurate timing, the distance to the feature can be measured. Using a rotating mirror inside the laser transmitter, the laser pulses have the ability to sweep through an angle, tracing out a line on the ground. By reversing the direction of rotation at a selected angular interval, the laser pulses can scan back and forth along a line. When such a laser ranging system is mounted in an aircraft with the scan line perpendicular to the direction of flight, it produces a saw tooth pattern along the flight path.



A pulsed laser ranging system is mounted in an aircraft equipped with a precise kinematic GPS receiver and an Inertial Navigation System.

LiDAR Employment

There are multiple uses for LiDAR technology. Presently, a worldwide network of observatories uses LiDAR to measure the distance of the Earth to the moon with millimeter precision and to facilitate tests of general relativity. The Mars Orbiting Laser Altimeter (MOLA) is an instrument that used LiDAR technology in a Mars-orbiting satellite to produce a stunningly accurate topographic survey of the red planet. In atmospherics, LiDAR is used as a remote detection instrument to measure densities of certain constituents of the middle and upper atmosphere, such as potassium, sodium, or molecular nitrogen and oxygen.

One situation where LiDAR has notable non-scientific application is for vehicle speed measurement. The technology for this application is small enough to be mounted in a handheld camera “gun” and permits a particular vehicle’s speed to be determined from a stream of traffic. LiDAR can be used for many military applications and considerable research continues in this segment. Here the name LADAR (laser detection and ranging) is more common. At the JET nuclear fusion research facility in Oxfordshire, London, the LiDAR Thomson Scattering method is used to determine electron density and temperature profiles of the plasma.



A LiDAR-generated DTM associated with orthophotos is a worthwhile tool for the localization and class-ification of urban areas, manmade infrastructure and the generation of land use classes.

LiDAR in Large-scale Mapping

LiDAR is extensively used for large-scale mapping projects. With the application of LiDAR for map development, new generation map development is reduced; that is, more precise, user-friendly maps are made available in a very short development and design period. The absolute accuracy of the elevation data achieved is approximately 15 cm; however, a relative accuracy of less than 5 cm or below can be achieved, depending on operating parameters such as flight altitude, etc. The elevation data is generated at thousands of points per second. With these high measurement rates, it is possible to rapidly complete a large topographic survey and generate DTMs (digital terrain models) with a grid spacing of 1 m or less. With LiDAR from fixed-wing aircraft flying at higher altitudes (which is essential to meet accuracies for large-scale contour mapping), the data filtered (i.e., when measurements made to buildings, foliage, etc. are removed) to a bare-Earth DTM can be used for aerial triangulation. The orthophoto is useful for 3D modeling of bridges, highway ramps, etc. Because LiDAR points are collected randomly and at an angle, points may appear atop and below bridges. This causes a feature such as a bridge to appear distorted on a digital orthophoto. With proper breakline placement, obstructions are rectified and appear geographically correct as well as aesthetically pleasing.

Forest Management

LiDAR remote sensing is a breakthrough technology for forestry applications. New LiDAR data sets provide precise measurements of various forest parameters like canopy height, sub-canopy topography, and the vertical distribution of intercepted surfaces between the canopy top and the ground. Other forest structural characteristics, such as above-ground biomass, are modeled or inferred from these direct measurements. Ecologists and wildlife managers are using the data to assist in applying information to better characterize, model and manage habitats and associated natural resources.
 
Telecommunications

The application of LiDAR in the telecommunications sector is predicted to boom in the near future. Telecommunications companies rely on accurate and detailed data sets and need a spatial accuracy of at least 1 m (x,y,z) to ensure proper planning. Because of its flexibility, accuracy and timeliness, this industry has started acquiring LiDAR-generated building contour renderings for the accurate geo-referenced dataset. These data are being used to evaluate radio frequency, wave interference and traffic capability.

Seismic Management

Airborne LiDAR is gaining widespread use in seismic acquisition for the following applications:

a. Slope determination. Pre-planning of source locations, source type identification, locating staging areas, positioning crews to work in downhill directions and illustrating regulation compliance.

b. Survey efficiency. Using LiDAR derived elevation (Z) value for seismic points instead of acquiring Z with GPS units can increase the efficiency of survey crews, especially in conditions of heavy vegetative canopy.

c. Identification of hazards. Hazards include steep terrain, thick vegetation and oilfield infrastructure such as pipelines, well pads and roads.

d. Map creation. LiDAR DEMs (digital elevation models) serve as a backdrop and provide the capability to create various themes.

e. Radio communication. Radio transmission and reception models help locate ideal signal repeater locations.

f. Logistical and safety planning. Fly-through simulations on DTMs provide a visualization of ground conditions and hazards that occur on any travel route.

Urban Planning

A LiDAR-generated DTM associated with orthophotos is a worthwhile tool for the localization and classification of urban areas, manmade infrastructure and the generation of land use classes. It is possible to produce volumetric data for quarry and landfill sites, a cyclic census of forested expanses, location of wildcat buildings and land use classification.

The availability of a DTM of a floodplain and a river basin is paramount for the control and monitoring of riverbanks and coastlines. The deployment of airborne LiDAR enables the timely survey of large areas of the floodplain efficiently and accurately during or immediately after a flooding event by analysis and comparison of altitude data and orthophotos.

It is also possible to obtain accurate and up-to-date estimates of sediment/erosion volumes along a river course and pinpoint potential areas prone to landslides.

The use of a DTM greatly enhances the planning capability of the basin and helps in managing emergency scenarios. This also helps in studying, evaluating, modeling and analyzing the hydrological parameters within a river basin. An accurate DTM can be used to measure the distance, steepness and river cross-sections.


LiDAR in GIS

LiDAR is well-suited for GIS applications due to the fact that the data is processed rapidly, is geo-referenced and can be readily imported into a GIS environment. Imported data is in vector format consisting of spatially distributed points. From this topology, many GIS functions may be performed including aggregation, neighborhood/proximity analysis, spatial statistics and contour modeling. Most LiDAR information is used for the study and building of DEMs. In the case of atmospheric applications, multi-spectral LiDAR allows for quick monitoring of aerosols, where varying light pulses of different wavelengths result in thematic layers being created for individual types of airborne particles.

GIS image analysis software is increasingly used to differentiate between light points of differing time returns and/or differing spectral color. The data captured with LiDAR can be readily integrated with other thematic content if all of the information is geo-referenced. Issues related to scale and resolution require consideration since LiDAR information tends to be quite accurate with submeter resolutions, while other data sets may be of a coarser resolution. Future applications are likely to be linked with artificial intelligence and real-time coupling to other instrumentation. One of the primary benefits of LiDAR is the quick construction of 3D and 4D models.

Future Development of LiDAR

As the GIS community advances toward 3D technology and virtual reality environments for modeling and analysis, the demand for highly detailed and accurate DTMs will increase significantly. Digital orthophotography will demand DTM models for “true orthophoto” production, which rectifies buildings and other tall structures. DTMs can be used to simulate fly-throughs of areas to view tall buildings, freeway ramps and other obstructions. True 3D orthophotography provides engineers and planners with a powerful tool to design and visualize cities and utility infrastructures.

Moreover, points currently filtered out of data sets to create a bare-Earth DTM will be classified through feature-recognition techniques to differentiate buildings, trees, cars, etc., alleviating the monotony of collecting the features manually. Using this methodology, a land base project executed over a city the size of New Delhi (43 km2) could automatically classify 1 million buildings. LiDAR can be used to efficiently locate areas of change, which provides invaluable information for subsequent mapping updates. Original LiDAR DTMs taken during the first mapping phase are compared to later data sets, and areas of change can be located by superposition.

LiDAR is an appropriate complement to existing photogrammetric technologies, and it offers substantial benefits in terms of increased data collection efficiencies and accuracy levels. As LiDAR becomes more sophisticated and refined, uses for the technology will expand.

Multi-purpose Technology

The increased resolution and accuracy of elevation data from modern LiDAR systems are proving useful in a variety of earth resource applications. From a military perspective, traditional sources of elevation models such as 30-m DEMs are often inadequate for assured mobility in tactical settings. This problem must be solved in order to meet the requirement for mobile units to defeat micro-terrain gaps by crossing or avoiding them. Advance knowledge of the type, location and characteristics of gaps available in a GIS can be a useful tool for cross-country planning purposes. Fine-grained terrain information will be even more critical for the smaller wheelbases of future unmanned ground vehicles.

Using slope breaklines as useful indicators of the spatial limits of gap features, the refinement of numerical algorithms for finding breaklines from high-resolution terrain models will increase the speed and accuracy of gap identification. Slope breakline information may then be processed and organized into individual linear gap features as geo-located objects in a GIS, whose extent would be constrained by the input of geometric parameters. In spite of the difficulty of discovering breaklines using a discrete sampling scheme, current and future LiDAR sensors may provide adequate resolution for characterizing micro-terrain anomalies from an elevation model.

Future work may include development and testing of effective breakline-finding algorithms, including the determination of algorithm constraints and thresholds under field conditions. Experiments with bare-earth LiDAR elevation models to reduce the creation of erroneous breaklines resulting from neighboring pulse returns from tree canopies and adjacent terrain will also be completed.

Additional work is possible in the investigation of elevation models derived from Interferometric Synthetic Aperture Radar (IFSAR) over the same site for comparative analysis with the LiDAR data in modeling micro-terrain discontinuities. In addition to modeling mobility barriers, such efforts would complement studies of various features such as the geomorphic distribution of fault scarps. To date, the results from such a preliminary study indicate that high-resolution elevation models show strong potential for the extraction of specialized slope/terrain products, with the promise of more efficient capture of these features by semi-automated and automated means. Complex solutions for the interoperable issues have been tested as well as artificial intelligence GIS data mining engines with LiDAR data. These results will allow for future solutions to be generated at a higher degree of accuracy. Users of LiDAR should not lose sight of the fact that the technology is one of the sources of highly accurate data and not the solution itself.

This article is a collection of works done in the field of LiDAR by various individuals and institutes. The author takes no claim in either designing LiDAR or its methodologies. Only the integration of isolated works in the field of LiDAR has been done in this article, keeping in view resource management for instituting awareness towards developing LiDAR concepts. Various proceedings of IEEE and e-zines on remote sensing and GIS, data from various conferences, websites, journals and references from open sources have contributed in the development of this article.

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