LIght Detection And Ranging(LiDAR) Systems

LIght Detection And Ranging(LiDAR) Systems
This white paper on LiDAR mapping provides the reader with an introduction to a maturing tech­nology used to acquire land based Digital Eleva­tion Models (DEM), and an existing mature tech­nology used to acquire marine (undersea) DEMs. Common to both the land-based and marine-based systems is the use of lasers, integrated into what are known as LIghtDetectionAndRanging systems, or LiDAR.
The paper begins with an introduction to LiDAR, and follows-through with how the systems are used, a description of land and marine variants, and statements as to what accuracy is attain­able. Data products driven by applications are outlined, and the ability of these products to be integrated into a GIS is addressed. In turn and integral to the theme of the paper, evidence is presented to support applications developments that will ultimately benefit the public at large.
Where valid, comparisons of LiDAR to other map­ping technologies are presented to give the reader an understanding of current traditional practices. In many cases the combination of Li­DAR with other technology creates a result that is unachievable with a single methodology.
Finally, conclusions are presented for discussion purposes that draw on the experiences of LiDAR practitioners and clients, as well as those of Ter­rapoint.

LiDAR, an acronym for Light Detection and Ranging, is a term that has been around,
discussed, and researched since the early 1950’s. It was not until the development of
accurate positioning systems that LiDAR became to be considered as a viable imaging /
mapping technology.
Looking generally at how LiDAR works, there is typically a LiDAR laser sensor, which
is precision mounted to the underside of an aircraft, and which transmits or pulses a
narrow laser beam towards the earth as the aircraft flies. A receiver additionally affixed
to the aircraft receives the reflection of these pulses as they bounce off the earth below
back to the aircraft. Most LiDAR systems use a scanning mirror to generate a swath of
light pulses. Swath width depends on the mirror's angle of oscillation, and ground-point
density depends on factors such as aircraft speed and mirror oscillation rate. Ranges are
determined by computing the amount of time it takes light to leave an airplane, travel to
the ground and return to the sensor. A sensing unit's precise position and attitude,
instantaneous mirror angle and the collected ranges are used to calculate 3-D positions of
terrain points. As many as 100,000 positions or "mass points" can be captured every
second. The LiDAR sensor essentially records the difference in time between the signal
being emitted and received from a given point, very much like a conventional survey
instrument. The LiDAR data is coupled with additional precise positioning information
gathered by on board Global Positioning Instruments (GPS) and other Inertial Navigation
Systems (INS). Once the total information volume is stored and processed, the resulting
product is an extremely accurate "x.y.z." for every position scanned on the ground.

LIDAR uses ultraviolet, visible, or near infrared light to image objects and can be used with a wide range of targets, including non-metallic objects, rocks, rain, chemical compounds, aerosols, clouds and even single molecules. A narrow laser beam can be used to map physical features with very high resolution.
LIDAR has been used extensively for atmospheric research and meteorology. Downward-looking LIDAR instruments fitted to aircraft and satellites are used for surveying and mapping. A recent example being the NASA Experimental Advanced Research Lidar.

Wavelengths in a range from about 10 micrometers to the UV (ca. 250 nm) are used to suit the target. Typically light is reflected via backscattering. Different types of scattering are used for different LIDAR applications, most common are Rayleigh scattering, Mie scattering and Raman scattering as well as fluorescence. Based on different kinds of backscattering, the LIDAR can be accordingly called Rayleigh LiDAR, Mie LiDAR, Raman LiDAR and Na/Fe/K Fluorescence LIDAR and so on. Suitable combinations of wavelengths can allow for remote mapping of atmospheric contents by looking for wavelength-dependent changes in the intensity of the returned signal.


A LiDAR system combines a single narrow-beam laser with a receiver system. The laser produces an optical pulse that is transmitted, reflected off an object, and returned to the receiver. The re­ceiver accurately measures the travel time of the pulse from its start to its return. With the pulse trav­elling at the speed of light, the receiver senses the return pulse before the next pulse is sent out. Since the speed of light is known, the travel time can be converted to a range measurement. Combining the laser range, laser scan angle, la­ser position from GPS, and laser orientation from INS, accurate x, y, z ground coordinates can be calculated for each laser pulse. Laser emission rates can be anywhere from a few pulses per second to tens of thousands of pulses per sec­ond. Thus, large volumes of points are collected. For example, a laser emitting pulses at 10,000 times per second will record 600,000 points every minute. Typical raw laser point spacing on the ground ranges from 2 to 4 meters

Some LiDAR systems can record “multiple re­turns” from the same pulse. In such systems the beam may hit leaves at the top of tree canopy, while part of the beam travels further and may hit more leaves or branches. Some of the beam is then likely to hit the ground and be reflected back, ending up with a set of recorded “multiplereturns” each having an x, y, z position. This fea­ture can be advantageous when the application calls for elevations for not only the ground, but for tree or building heights

As surface types and characteristics vary and change the laser beam’s reflectivity, then theability of the LiDAR to record the return signals changes. For example, a laser used fortopo­graphic applications will not penetrate water, and in fact records very little data even for the surface of the body of water. Where the appli­cation calls for a laser to penetrate water to determine x, y, z positions of undersea features, then a slightly different variation of LiDAR technology is used.


In general there are two kinds of lidar detection schema: "incoherent" or direct energy detection (which is principally an amplitude measurement) and Coherent detection (which is best for doppler, or phase sensitive measurements). Coherent systems generally use Optical heterodyne detection which being more sensitive than direct detection allows them to operate a much lower power but at the expense of more complex transceiver requirements .

In both coherent and incoherent LIDAR, there are two types of pulse models: micropulselidar systems and high energy systems. Micropulse systems have developed as a result of the ever increasing amount of computer power available combined with advances in laser technology. They use considerably less energy in the laser, typically on the order of one microjoule, and are often "eye-safe," meaning they can be used without safety precautions. High-power systems are common in atmospheric research, where they are widely used for measuring many atmospheric parameters: the height, layering and densities of clouds, cloud particle properties (extinction coefficient, backscatter coefficient, depolarization), temperature, pressure, wind, humidity, trace gas concentration (ozone, methane, nitrous oxide, etc.).

There are several major components to a LIDAR system:
1. Laser — 600–1000 nm lasers are most common for non-scientific applications. They are inexpensive but since they can be focused and easily absorbed by the eye the maximum power is limited by the need to make them eye-safe. Eye-safety is often a requirement for most applications. A common alternative 1550 nm lasers are eye-safe at much higher power levels since this wavelength is not focused by the eye, but the detector technology is less advanced and so these wavelengths are generally used at longer ranges and lower accuracies. They are also used for military applications as 1550 nm is not visible in night vision goggles unlike the shorter 1000 nm infrared laser. Airborne topographic mapping lidars generally use 1064 nm diode pumped YAG lasers, while bathymetric systems generally use 532 nm frequency doubled diode pumped YAG lasers because 532 nm penetrates water with much less attenuation than does 1064 nm. Laser settings include the laser repetition rate (which controls the data collection speed). Pulse length is generally an attribute of the laser cavity length, the number of passes required through the gain material (YAG, YLF, etc.), and Q-switch speed. Better target resolution is achieved with shorter pulses, provided the LIDAR receiver detectors and electronics have sufficient bandwidth[1].
2. Scanner and optics — How fast images can be developed is also affected by the speed at which it can be scanned into the system. There are several options to scan the azimuth and elevation, including dual oscillating plane mirrors, a combination with a polygon mirror, a dual axis scanner. Optic choices affect the angular resolution and range that can be detected. A hole mirror or a beam splitter are options to collect a return signal.
3. Photodetector and receiver electronics — Two main photodetector technologies are used in lidars: solid state photodetectors, such as silicon avalanche photodiodes, or photomultipliers. The sensitivity of the receiver is another parameter that has to be balanced in a LIDAR design.
4. Position and navigation systems — LIDAR sensors that are mounted on mobile platforms such as airplanes or satellites require instrumentation to determine the absolute position and orientation of the sensor. Such devices generally include a Global Positioning System receiver and an Inertial Measurement Unit (IMU).

Airborne LiDAR Hydrography (ALH) has been un­der development since the mid 1960s. There are currently half a dozen ALH systems in operation, and one of the most advanced and reliable is the Scanning HydrographicOperationalAirborne LiDAR Survey, or SHOALS system. It has been de­scribed as one of the most versatile hydrographic LiDAR systems in use in the world today. To the author’s knowledge there is only one SHOALS sys­tem in operation, and it is owned by the United States Army Corps of Engineers.
There are several fundamental differences be­tween a SHOALS system and a topographic Li­DAR system. The principle difference is that the SHOALS system uses two varying laser beams whereas most topographic systems use a single beam. In addition, the wavelengths of the laser in each are different. Most topographic LiDAR uses near infrared beams that reflect off most ob­jects. The SHOALS system uses a red wavelength (infrared) beam that is reflected by the water sur­face and detected by the receiver, as well as a blue-green wavelength beam which penetrates the water surface and is reflected from the bot­tom. As shown in the graphic on the left, a hydro­graphic LiDAR fires co-aligned laser pulses of the two different wavelengths at the water. The time difference between the two signals determines the water depth. Another major difference be­tween a topographic and SHOALS system is the frequency of the emitted laser beam. Whereas a topographic LiDAR emits beams at up to 30,000 Hz, the SHOALS system operates at relatively low frequency, emitting pulses at 400 Hz.
A final interesting difference between the SHOALS LiDAR and a typical topographic LiDAR is the dis­parate energy requirements of each. Whereas a topographic system can be used in a relatively small aircraft or helicopter, the SHOALS system requires much more power to operate. This is due to the power required to energize a laser beam such that it can penetrate the water to the depths necessary to map the ocean floor.
Typically, marine LiDAR can measure the depth of water down to about 50 meters depending on the turbidity, or clarity of the water. This is one of the major limiting factors when considering a SHOALS system for underwater applications.

Earlier laser based instruments consisted of single laser pulses. Current LIDAR technology involves the rapid scanning of 10-15,000 pulses per second in a pattern perpendicular to airplane flight path. These pulses are emitted from the aircraft toward the earth’s surface and reflect from the earth’s surface and other objects on the surface back to the aircraft. Similar to GPS the travel time of the pulses multiplied by the speed of light (299,792,458 m/s) determines distance
or – range. The rate of pulse emission, speed of the aircraft and altitude all play an important.
role in LIDAR mapping. Their roles can be thought of similar to conventional aerial photography where scale can be determined based upon aircraft altitude and camera focal length. However, in the case of LIDAR, emission angle must be determined since the scanner emits laser pulses and acquires them from multiple angles from a nadir (point perpendicular to the emitter toward the earths surface). LIDAR has been used in the study of atmospherics, flood plains, forest canopy density, agriculture and geology. By far, most LIDAR applications are for construction of (DEM). When building a DEM a series of ‘raw’ data points are generated for a landscape.

The LIDAR instrument is calibrated prior to beginning operation through the application and alignment with pre-determined ground control points. INS is also calibrated at this time. These calibrations and the initial raw data are compared and accuracy’s of 50 cm. or less are common. It should be remembered that all landscape objects are visible at this stage. These objects can be ‘filtered’ from the initial images thereby allowing for the construction of a DEM (Fig.2). Further interpolation of the DEM dependent upon either captured LIDAR data points or ground collected elevation points may be included in the data set

The filtered data containing ‘objects’ is kept and may be analyzed. For example, when investigating forest cover types, constructing 3-D visualizations or delineating routes, line-work or other physical attributes. Currently a significant number of researchers internationally are studying natural environments and landscapes with a view to developing algorithms derived from LIDAR data that recognize common landscape attributes.

The portability and rapid turn around of LIDAR information has led to the study of ice sheets in Canada, aerosols in the City of Leipzig, Germany and earthquake prone areas in the Seattle, Washington area. In emergency or natural disasters where conditions and change rapidly, LIDAR can be used effectively for the purposes of monitoring change. Since the data can be acquired locally and processed locally quicker management decisions can be made and observation of changing conditions more closely investigated. In the case of natural disasters LIDAR has other benefits due to being an aerial application, therefore reducing need and possible injury to ground based monitoring. Similarly, environments where aerosols or other dangerous airborne pollutants are present can be monitored from a distance.

LIDAR errors can and do occur for a number of reasons. The field of (FOV) of a LIDAR beam can be varied. Generally a FOV from ranging from 15° to 50° is used. The wider the FOV the less accurate will be the results due to lesser numbers of light pulses reflecting upon the earths surface. Higher numbers of pulses per unit area may be achieved by a number of methods including:
Slower aircraft speed
Lower flying altitude
Reduced field of view (FOV)
Increased pulse emission

A change in altitude, for example by flying higher will result in a decrease of resolution as propagation times tend to merge and subsequently ‘average’ together. Flying closer to ground level will result in stronger signal returns and more of them over a smaller area. This will result in improved resolution due to increasing numbers of points being sampled per unit area. Further, those objects closer to the LIDAR instrument return pulsed light sooner than those farther in distance due less atmospheric scattering.
Assume a forest canopy, and for the moment consider the forest canopy has two height classes. One height class has trees that are at 20 meters high and the other where trees are at 35 meters in height. Light pulses will strike the upper crowns of the forest canopy (if generated from above) prior to striking those of the lower height class. Further, the light pulses will strike the ground itself lastly. Those pulses striking the upper will be returned to the instrument first and those striking the ground will return to the instrument last. This is a very simple example, however it does raise some interesting questions, particularly if one is interested in investigating crown size – which might be useful for determining carbon storage and turn over rates within a forest.
Most tree canopies, if not all, are not symmetric they tend to be irregular and vary with height and density. How would you determine from an irregular collection of objects (trees), their heights, from a widely spaced collection of returned pulsed points? Similarly, a series of buildings closely spaced but of irregular shape and height will return a series of points to the instrument. How can we in such a case determine which pulses belong to which buildings thereby delineating the building – accurately in both shape and height?

To determine the shapes of objects and their corresponding heights the points returned to the emitter are collected and filtered. This can be done a number of ways including:
Density of points with similar range – return times
Density of points using neighbourhood / proximity analysis
Correlation to other information including aerial photographs
Spectral analysis in the case of multi-spectral emitters
Object analysis – linking physiology / biology
Structural analysis – building design / surfaces

Vertical LIDAR refers to the placement of a LIDAR instrument perpendicular to the earth surface (side-view). Similar to aerial LIDAR, vertical applications of LIDAR are designed to acquire a representation of the sides of buildings, trees, bridges and other landscape objects.
Perhaps a model is needed for an oil refinery or historical building, in which case vertical LIDAR can be applied to quickly build a model suitable for integration into a GIS or other visualization software.
In the study of biological environments, vertical LIDAR holds great promise for the determination of ecological bio-diversity when applied from the side since patterns and structure of biological entities can and do vary beneath canopies trees. One investigation using conventional light laser studied side-views of forest canopies using laser, GPS and image analysis (Fig. 4). In this image the viewpoint is from the top-down. Those objects closer to the laser are at the top and the point distances have been analysed from the side using GIS neighbourhood analysis.

LIDAR point side-view data tables can be collected for other objects besides forests. (Fig. 4) is classified into 12 classes, however, it is almost impossible to determine actual tree shapes. Other researchers are working on this problem and developing techniques for the analysis of both raster and vector models of the point distributions. It should come as no surprise that with greater numbers of emitted light pulsed points returned, resolution improves. Finally, after analysis of the point distributions, thematic layers suitable for GIS analysis can be developed.

Airborne LIDAR sensors emit between 5,000 and 50,000 laser pulses per second in a scanning array. The most common scanning arrays, as shown below, go back and forth sideways relative to the points measured on the ground. The scan angle and flying height determine the average point spacing in the cross-flight direction, whereas the flying height and the airspeed determine the average point spacing in the in-flight direction. Each laser pulse has a pulse width (typically between 0.5 and 1 meter in diameter) and a pulse length (equivalent to the short time lapse between the time the laser pulse was turned on and off). Therefore, each laser pulse is actually like a cylinder of light with diameter and length.

Several technologies operate for LIDAR to survey high-accuracy data points on the ground:

  • Airborne Global Positioning System (GPS) is needed todetermine the x, y, and z coordinates of the moving LIDAR sensor in the air, surveyed relative to one or more GPS base stations.
  • The Inertial Measuring Unit (IMU) directly measures the roll, pitch, and heading of the aircraft, establishing the angular orientation of the LIDAR sensor about the x, y, and z axes in flight.
  • The LIDAR sensor measures the scan angle of the laser pulses. Combined with the IMU data, this establishes the angular orientation of each laser pulse.
  • The LIDAR sensor measures the time needed for eachemitted pulse to reflect off the ground (or features thereon) and return to the sensor. 

LIDAR sensors are capable of receiving multiple returns, some up to five returns per pulse. This means that a 30-KHz sensor (30,000 pulses per second) must be capable of recording up to 150,000 returns per second. The "first return" recorded by a LIDAR sensor is the first thing hit by a laser pulse. This could be a treetop, roof, ground point, or a bird in flight. When a laser pulse hits a soft target (e.g., a forest canopy), the first return represents the top of that feature. However, a portion of the laser light beam might continue downward below the soft target and hit a tree branch. This would provide a second return. Theoretically, the last return represents the bare earth terrain, but this is sometimes not the case. Some vegetation is so thick that no portion of the laser pulse penetrates to the ground. This is usually the case with sawgrass, mangrove, and dense forests where a person on the ground cannot see the sky through the canopy. LIDAR for the North Carolina Floodplain Mapping Program was flown during "leaf off" conditions to favor the acquisition of bare earth data.

Most topographic LiDAR systems are used in small to medium fixed-wing aircraft. A typical platform would range from a Cessna 206/210 or equivalent, to a Piper Navajo or equivalent. These aircraft may require some additional fitting for mounts and power supplies, but it is usual that an aircraft equipped to conduct aerial photog­raphy can be used to fly current commercially available LiDAR systems.
There are a number of topographic LiDAR systems that can be fitted to operate in helicopters, and several have been designed to be exclusive to this type of platform. Systems are currently oper­ated on helicopters ranging from Robinson R44s, to Enstrom F28s, Bell 206 Jet Rangers and Aero­spatial AS350 aircraft.
The SHOALS system requires a much larger plat­form for production flying, something that might range from a DeHavilland Twin Otter aircraft to a Bell 212 helicopter.
It stands to reason that the bigger the aircraft the more expensive it is to operate. For example, to­day’s commercial rates for a Bell 212 helicopter might be in the range of $3,000 per hour, while a Bell 206 Jet Ranger might be hired at a cost of $900 per hour. This order of magnitude dif­ference would be similar if comparing the cost of a twin otter against that of a Piper Navajo or Cessna 210.
Although beyond the scope of this paper, LiDAR systems are also operated by NASA on space-borne platforms including the Space Shuttle.

One of the inherent features of LiDAR data is that it is acquired, processed, and delivered in a digi­tal format. This makes it very easy to work with LiDAR, and to create data products that meet a wide range of needs. The simplest form of data acquired from LiDAR is an ASCII format file con­taining x, y, z coordinate data. This coordinate data corresponds to the geographic 3-D position of an actual LiDAR return. The return and associ­ated coordinate could be the position of a return off the ground, a building, a tree, or any other object that the laser beam has hit and been re­flected from.
The ASCII x, y, z files can be imported into various software packages, and especially GIS. Data manipulation can create a wealth of products, and augmenting or fusing other types of data with LiDAR can produce valuable results. For in­stance, it is possible to import the x, y, z points into a GIS, create a raster gridded DEM, and use the DEM to create shaded surface models that are highly realistic. With the same DEM, it is possible to create orthomaps (often referred to as Digital OrthoImages) by fusing the data with images acquired by conventional aerial photography or digital imaging cameras. For a less accurate overview of the subject area being surveyed, the SHOALS system and many topographic LiDAR systems record VHS or SVHS video imagery. The video can be viewed stand-alone or it can be fused with the DEM to produce a less accurate but still valuable map product.
LiDAR also lends itself to the development of non-traditional 3-D products that provide appealing visualizations to meet a number of needs. Using off-the-shelf software, it is possible to input a series of orthomaps and DEMs and to create animated clips on a PC. These clips might for example de­pict a roadway, river valley, urban core or forest grove, and can lend high visibility to a presenta­tion or study. To add even more value, computer animation and graphics can be added to the 3-D “fly through” to create stunning vistas and ef­fects.

Since LiDAR data can be imported and exported by most commercially available GIS packages, this infers that the vast majority of available raster and vector formats can be supported with LiDAR data as the basis.

The North Carolina Floodplain Mapping Program has chosen to use LIDAR to acquire new, highly accurate digital elevation data for floodplain mapping. Compared to traditional photogrammetric methods used to develop topographic data, LIDAR has several advantages, including:

  • LIDAR is better able to map bare earth elevations in forested or vegetated areas than other methods because only a single laser pulse needs to be able to reach between trees and the ground.
  • The post-spacing for digital elevation data derived from LIDAR is considerably denser than from traditional methods. For example, LIDAR data from eastern North Carolina have nominal point spacing of approximately 3 meters, whereas older methods typically acquire data points spaced at 10 to 30 meters.
  • Digital elevation data created from LIDAR are considerably less expensive than those created from traditional methods, especially when automated post-processing is used to generate LIDAR bare earth elevation data.

Because of the high density of mass points, LIDAR is superior for automated Hydrologic and Hydraulic (H&H) analyses and automated floodplain delineation such as that shown to the left, which is used to create Flood Insurance Rate Maps (FIRMs).

Light detection and ranging (LiDAR)technology, also called airborne laser scanning, has been available for more than a decade—long enough thatI’m ready to treat lidar as a word like radarand sonar. Airborne lidar actively sends pulses of light toward the ground; the
time taken for the pulse to return to the sensor tells us the height of whatever surface
the light beam strikes, whether roofor leaf, power line or soil. The data can
beanalyzed to provide a digital elevation model (DEM). This was the first application
to gain widespread use and continues to be the primary application. However,
the technology has improved in several ways, enabling additional applications.
To understand current lidarmarkettrends, Cary and Associates recently conducted
extensive market research using a brief online survey, a longer questionnaire,
Internet searches and interviews. The online survey was completed by 268 people
from28 countries on six continents. However, 80 percent of respondents were
from North America. The questionnaire, sent to industry experts around the world
to collect more information about areas outside North America, was completed by
20 respondents from six continents.
“Core” Applications
Two survey questions explicitly addressed the subject of lidar applications.
To create a question about current uses, we used the Internet to develop a list of 17
reportedlidar applications. That list, along with “Other,” became the possible survey
answers. Respondents were asked to markall of their applications.
As detailed in the chart at right, three applications were selected by more than
half of respondents. Topography (DEM)was the clear leader in current applications,
selected by more than threequartersof end users, followed by flood
riskmapping and watershed analysis. When one thinks of how often tsunamis,hurricanes and floods have been in thenews, with thousands of lives lost and immense
property damage, these applications make sense and can be expected to remain
top applications in the future. I think of them as the “core” lidar applications.
In interviews, some people said lidarwould be good for forestry, “but there’s no
money there.” I found it interesting that tree canopy analysis ranks fourth while
forestryranks 11th. Perhaps tree canopy analysis ranks so high in part because it is
a component of fire risk.

LiDAR mapping is a maturing technology, and applications are still being identified and devel­oped as end-users begin to work with the data. There are on-going initiatives to identify areas where the technology allows value-added prod­ucts to be generated or where it offers significant cost reductions over traditional survey methods.
LiDAR is an enabling technology. Primarily, it has allowed data to be collected that was difficult or impossible to obtain prior to its in­troduction. This is especially true in the forest industry and utility corridor arena, where it has been very difficult and expensive to getelevation models using ground-based GPS, conventional survey and/or photogrammet­ric techniques.
LiDAR is an enhancing technology. For ap­plications where a more precise DEM is re­quired, such as engineering and road de­sign and flood plain mapping, LiDAR is able to provide much more information than can be acquired by virtually any other means — at least within economic reason.
LiDAR has revolutionized the survey and mapping world. In practical terms, hydro­graphic LiDAR has been a viable survey tool since the early 1980s. With the advent of a full constellation of GPS in the early 1990s, hy­drographic LiDAR has taken a giant leap for­ward in being able to provide accurate data for difficult survey operations. Topographic LiDAR has evolved from a relative physics experiment to a useable and reliable survey tool, all since the mid 1990s. Now that the technological “chasm” is virtually crossed, and more people are buying into LiDAR,the survey and mapping industry is racing to meet the demand for services. This includes the industry’s ability to properly acquire, pro­cess and quality control the data.
LiDAR has empowered clients. The speed with which data can be collected, and the relative speed at which it can be processed compared to any other technology, has giv­en clients the power to demand products more quickly. In many cases, time saved on surveying and mapping translates into huge downstream economic gains.
LiDAR offers flexibility. Although it can be said of data collected via other methods, data collected by LiDAR is extremely versa­tile. It can be used for anything from power line detection to DEM generation in a sec­ond growth forest. This is due to the tremen­dous point density achieved from LiDAR, its accuracy, and its ability to penetrate to the ground through foliage in vegetated areas
LiDAR is unobtrusive and environmentally friendly. Unlike ground survey techniques, airborne LiDAR can be flown over areas where access is limited, impossible, or unde­sirable. Apart from the need to validate theLiDAR with ground truthing, it is not necessary to send pervasive ground crews to conduct intense survey operations. LiDAR surveying can also avoid unnecessary tree cutting and other practices that can harm the environ­ment.
In conclusion, it is hoped that this paper will have provided an insight into the possibilities of LiDAR, and will elicit discussion regarding the use of Li­DAR to conduct mapping projects. Given the versatility of the technology, and its maturation, it seems logical that any strategic plan or project should at least consider its use. If required, more information can be obtained by contacting Ter­raPoint.

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