Intro. LIDAR REMOTE SENSING BHARATH B, NITK, Surathkal

Dept, of Applied Mechanics Page 1

1. INTRODUCTION

LIDAR (light detection and ranging, also LADAR) is an optical remote sensing

technology that can measure the distance to, or other properties of a target by illuminating the

target with light, often using pulses from a laser. LIDAR technology has application in

Geomatics, archaeology, geography, geology, geomorphology, seismology, forestry, remote

sensing and atmospheric physics. The acronym LADAR (Laser Detection and Ranging) is

often used in military contexts. The term laser radar is sometimes used even though LIDAR

does not employ microwaves or radio waves and is not therefore in reality related to radar.

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 10µm to the UV (250nm) 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.

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2. LIDAR SYSTEM

2.1 Principle behind lidar System:

Lidar is an active remote sensing technique using laser light. The lidar system

measures the round-trip time for a pulse of laser (light amplification by stimulated emission

of radiation) energy to travel between the sensor and the target. This incident pulse of energy

interacts with the earth features and is reflected back to the target. The travel time of the pulse

from initiation until it returns to the sensor is measured, and it provides a distance or range

from the instrument to the object (hence the common use of the term „laser altimetry‟ which

is now generally synonymous with lidar). Since the speed of light is a constant, the time from

pulse emission to pulse return can be accurately measured (Table 1).

Lidar echo time to measurement range conversion

(speed of the light c = 3.0E8 m/s)

1 ns 0.15 m 5.9 in

1 ms

10 m

100 ms

1000 ms (1 ms)

150 m

1.5 km

15 km

150 km

492 ft

0.93 statute mile (0.81 n mile)

9.32 statute mile (8.1 n mile)

93.2 statute mile (81 n mile)

Table 1

2.2 Mechanism of LiDAR system:

A typical laser scanner can be subdivided into the following key units: laser ranging

unit, opto-mechanical scanner, control and processing unit. The ranging unit comprises the

emitting laser and the electro-optical receiver (Figure 1 a, b). The transmitting and receiving

apertures (typically 8–15 cm diameter) are mounted so that the transmitting and receiving

paths share the same optical path. This assures that object surface points illuminated by the

laser are always in the field of view (FOV) of the optical receiver. The narrow divergence of

the laser beam defines the instantaneous field of view (IFOV). Typically, the IFOV ranges

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from 0.3 mrad to 2 mrad. The theoretical physical limit of the IFOV is determined by

diffraction of light, which causes image blurring. Therefore, the IFOV is a function of the

transmitting aperture and wavelength of light.

Figure 1.a

Figure 1.b

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3. COMPONENTS

3.1 Major components to a LIDAR system:

Laser

600–1000nm 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.

LiDAR Instrument

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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.

Optics Scanner

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. The commonly used photo-

detector is Avalanche photodiodes.

Photodiode

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).

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GPS IMU

4. WORKING OF LIDAR SYSTEM:

Lidar for terrestrial applications generally operate in the wavelength range of 900–

1064 nm, where vegetation reflectance is high. Lidar systems incorporate rapid laser pulsing

with GPS for position (x, y, z) and an inertial measurement unit (IMU) for orientation (pitch,

yaw and roll) of the sensor. As with any GPS activity, the lidar system requires initialization

with a surveyed-point, ground GPS base location and differential post-processing corrections.

In addition, a tested alignment process for the GPS position of the sensor and the IMU

orientation parameters is required to verify the accuracy of the lidar data sets. These systems

are able to record up to five returns per pulse, which demonstrates the value of lidar to

discriminate not only the top and bottom points of canopy, but also surfaces in between, viz.

understorey.

Procedure:

LiDAR measures distances by sending pulses of laser light that strike and reflect from

the surfaces of the earth. The LiDAR system then measures the time of pulse return. The

measured times are converted to distance-from-sensor data using the formula D=c*t/2

(where, D=distance, c=speed of light, t=time). A LiDAR system consists of several advanced

technologies that allow conversion of the distance-from-sensor data into accurately

georeferenced data in near real time. This greatly facilitates getting the LiDAR data into our

GIS applications.

Since LiDAR is an active sensor, LiDAR data can be acquired day or night, as long as the

atmosphere is clear. LiDAR generates very large datasets it is not uncommon for the system

to collect 50-100 thousand positions per second. Despite their large size, the data can be post-

processed to provide highly accurate and detailed DEMs; topographic maps; vegetation

heights, structure, densities and more.

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The four major components of LiDAR :

1. Aircraft. Rotor-wing (helicopters) and

fixed-wing (airplanes) aircraft are used to

collect LiDAR data. The laser scanner is

precision mounted on the bottom of the

aircraft. Typically, a minimum two-

person crew (pilot and operator) is

required.

2. GPS. LiDAR requires precise real-time

positioning. A major part of the position

solution is provided by using GPS

technologies in a differential kinematic

mode. This involves finding or

establishing a well-surveyed GPS base

station and co-initializing with the airborne GPS. The GPS provides the XYZ

location of the aircraft, but this is just part of the position solution required.

3. INS. An inertial navigation system (INS) provides another critical part of the position

solution. The INS records the pitch, roll and yaw of the aircraft (i.e., the angle that

the body of the LiDAR sensor is pointing). Thus, the INS position and the GPS

position give us the location of the sensor and the angle that is pointing.

4. Laser Scanner System. The laser scanner system is the heart of the LiDAR system,

it includes the laser source, the laser detector, the scanning mechanism, the

electronics for timing the pulses and returns, and the computing power to process and

record the data in real time.

4.1 The Laser Source:

The term LASER stands for "Light Amplification by Stimulated Emission of Radiation"

and is a device that controls the way photons are released.

Light from a laser has two unusual and valuable characteristics:

1. It is monochromatic (the lasers used for terrestrial surface applications are in the near

infrared portion of the spectrum) and

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2. It is very directional. Current lidar laser systems are capable of emitting tens of

thousands of laser pulses each second.

The Laser Detector

The laser detector is mounted with the laser. Its job is to detect the laser light that is

reflected from the target back to the aircraft. Now, it may be helpful to point out that even

though the laser may be sending out several thousand laser pulses per second, there is

sufficient time to detect all of the reflected pulses before the next pulse is sent. In addition,

the intensity value of each LiDAR return is often recorded. Intensity images can be very

useful.

The Scanning Mechanism

The most common scanning mechanism is the oscillating mirror, however, there are

others including: rotating polygon scanners, fiber scanners, and Palmer scanners. Each has

slightly different properties and resulting scanner patterns.

Timing Electronics

Timing is everything in LiDAR. The laser is sending 4,000 to 100,000 light pulses per

second. Each pulse may reflect up to five return pulses at the speed of light. Each return must

be precisely timed in order to obtain an accurate range (using the formula D = c*t/2).

Computing Power

The computing resources to record and process LiDAR should not be taken for

granted. LiDAR generates a lot of data in a very short time, staggering amounts of data for

large areas. Data must be recorded, and often processed, in real-time (although significant

portions of the processing is post-mission). Consider that each LiDAR return is numbered has

its range calculated, then the look angle is determined, and the GPS and IMU data have to be

incorporated. Finally, the LiDAR range and look angle information is converted to

geographic X,Y, and Z coordinates.

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5.LIDAR DATA:

The LiDAR Data comprises of 4 attributes,

X (longitude)

Y (latitude)

Z (Elevation)

Intensity of light reflected back is recorded

5.1 Characteristics and quality of LiDAR data

Swath width

Number of beam tracks

Footprint (at 400 km)

Footprint spacing

Track spacing

Pulses per second

Wavelength

Coverage

Elevation accuracy

Waveform digitization

Samples per waveform

Sample precision

Pulse detection dynamic range

8 km

3

25 m (60 @ mu @rad)

Contiguous over land (approx.)

4 km

290 over land (approx.)

1064 nm

Between 67° N and S

< 1 m in low slope terrain

250 mega samples/s

10–200, average = 50

10 bits

100 : 1

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6. APPLICATION:

6.1 Agriculture

Agricultural Research Service scientists have developed a way to incorporate LIDAR

with yield rates on agricultural fields. This technology will help farmers direct their resources

toward the high-yield sections of their land.

LIDAR also can be used to help farmers determine which areas of their fields to apply

costly fertilizer. LIDAR can create a topological map of the fields and reveals the slopes and

sun exposure of the farm land. Researchers at the Agricultural Research Service blended this

topological information with the farm land‟s yield results from previous years. From this

information, researchers categorized the farm land into high-, medium-, or low-yield zones.

This technology is valuable to farmers because it indicates which areas to apply the expensive

fertilizers to achieve the highest crop yield.

6.2 Archaeology

LIDAR has many applications in the field of archaeology including aiding in the

planning of field campaigns, mapping features beneath forest canopy, and providing an

overview of broad, continuous features that may be indistinguishable on the ground. LIDAR

can also provide archaeologists with the ability to create high-resolution digital elevation

models (DEMs) of archaeological sites that can reveal micro-topography that are otherwise

hidden by vegetation. LiDAR-derived products can be easily integrated into a Geographic

Information System (GIS) for analysis and interpretation. For example at Fort Beausejour -

Fort Cumberland National Historic Site, Canada, previously undiscovered archaeological

features have been mapped that are related to the siege of the Fort in 1755. Features that

could not be distinguished on the ground or through aerial photography were identified by

overlaying hillshades of the DEM created with artificial illumination from various angles.

With LiDAR the ability to produce high-resolution datasets quickly and relatively cheaply

can be an advantage. Beyond efficiency, its ability to penetrate forest canopy has led to the

discovery of features that were not distinguishable through traditional geo-spatial methods

and are difficult to reach through field surveys.

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6.3 Geology and soil science

High-resolution digital elevation maps generated by airborne and stationary LIDAR

have led to significant advances in geomorphology, the branch of geoscience concerned with

the origin and evolution of Earth's surface topography. LIDAR's abilities to detect subtle

topographic features such as river terraces and river channel banks, measure the land surface

elevation beneath the vegetation canopy, better resolve spatial derivatives of elevation, and

detect elevation changes between repeat surveys have enabled many novel studies of the

physical and chemical processes that shape landscapes. In addition to LIDAR data collected

by private companies, academic consortia have been created to support the collection,

processing and archiving of research-grade, publicly available LIDAR datasets. The National

Center for Airborne Laser Mapping (NCALM), supported by the National Science

Foundation, collects and distributes LIDAR data in support of scientific research and

education in a variety of fields, particularly geoscience and ecology.

In geophysics and tectonics, a combination of aircraft-based LIDAR and GPS have

evolved into an important tool for detecting faults and measuring uplift. The output of the two

technologies can produce extremely accurate elevation models for terrain that can even

measure ground elevation through trees. This combination was used most famously to find

the location of the Seattle Fault in Washington, USA. This combination is also being used to

measure uplift at Mt. St. Helens by using data from before and after the 2004 uplift. Airborne

LIDAR systems monitor glaciers and have the ability to detect subtle amounts of growth or

decline. A satellite based system is NASA's ICESat which includes a LIDAR system for this

purpose. NASA's Airborne Topographic Mapper is also used extensively to monitor glaciers

and perform coastal change analysis. The combination is also used by soil scientists while

creating a soil survey. The detailed terrain modelling allows soil scientists to see slope

changes and landform breaks which indicate patterns in soil spatial relationships.

6.4 Hydrology

LIDAR offers a lot of information to the aquatic sciences. High-resolution digital

elevation maps generated by airborne and stationary LIDAR have led to significant advances

in the field of hydrology.

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6.5 Military

Few military applications are known to be in place and are classified, but a

considerable amount of research is underway in their use for imaging. Higher resolution

systems collect enough detail to identify targets, such as tanks. Here the name LADAR is

more common. Examples of military applications of LIDAR include the Airborne Laser Mine

Detection System (ALMDS) for counter-mine warfare by Arete Associates.

Utilizing LIDAR and interferometry wide area raman spectroscopy, it is possible to

detect chemical, nuclear, or biological threats at a great distance. Further investigations

regarding long distance and wide area spectroscopy are currently conducted by Sandia

National Laboratories.

6.6 Physics and astronomy

A worldwide network of observatories uses lidars to measure the distance to reflectors

placed on the moon, allowing the moon's position to be measured with mm precision and

tests of general relativity to be done. MOLA, the Mars Orbiting Laser Altimeter, used a

LIDAR instrument in a Mars-orbiting satellite (the NASA Mars Global Surveyor) to produce

a spectacularly precise global topographic survey of the red planet.

In September, 2008, NASA's Phoenix Lander used LIDAR to detect snow in the

atmosphere of Mars.

In atmospheric physics, 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. These measurements can be used to calculate

temperatures. LIDAR can also be used to measure wind speed and to provide information

about vertical distribution of the aerosol particles.

6.7 Transportation

LIDAR has been used in Adaptive Cruise Control (ACC) systems for automobiles.

Systems such as those by Siemens and Hella use a lidar device mounted on the front of the

vehicle, such as the bumper, to monitor the distance between the vehicle and any vehicle in

Intro. LIDAR REMOTE SENSING BHARATH B, NITK, Surathkal

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front of it.[22]

In the event the vehicle in front slows down or is too close, the ACC applies the

brakes to slow the vehicle. When the road ahead is clear, the ACC allows the vehicle to

accelerate to a speed preset by the driver. Refer to the Military section above for further

examples.

7. MERITS AND DEMERITS OF LIDAR:

7.1 Merits -

1. Higher accuracy - Up to the order of 10–15 cm in the vertical and 50–100 cm in the

horizontal.

2. Weather independence - Being an active sensor, it can collect data at night and clear

weather conditions.

3. Capability of canopy penetration - Unlike photogrammetry, lidar can see below

canopy in forested areas and provide topographic measurements of the surface

underneath.

4. Higher data density.

5. Independent of ground control points - Only one or two GPS ground stations are

required for improving the GPS accuracy by the differential method, thus proved to be

an ideal method for inaccessible or featureless areas like wastelands, ice sheets,

deserts, forests and tidal flats.

6. Lesser time for data acquisition and processing - The data capture and processing

time is significantly less for lidar compared to other techniques.

7. Minimum user interference - As most of the data capture and processing steps are

automatic except the maintenance of the ground GPS station.

8. Provides additional data – Laser derived intensity images help in classifying the

terrain features.

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7.2 Demerits

1. The light beam cannot penetrate tree cover and water.

This prevents accurate readings at the forest floor except in areas where there are

gaps in canopy,

Generally LiDAR cannot penetrate deeply into water due to LiDAR being in the

IR wavelength.

2. Share size of the data prevents usage

Storage (the raw data which is obtained by LiDAR will be of around 250 GB.)

Intro. LIDAR REMOTE SENSING BHARATH B, NITK, Surathkal

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CASE STUDY

8. LIDAR REMOTE SENSING FOR FORESTRY APPLICATIONS:

8.1 LIDAR Measurement of Forest Lands:

Here the above graph directly depicts the height of the forest canopy, i.e. the graph is

plotting the return signals along x- axis and height of the tree is along y-axis.

The light which has received by receiver in shorter period will represent the highest

point of tree and the light signal which has return at last represents the forest floor.

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8.2 Tree height estimation:

There are many difficulties in determining tree height using lidar data,

Determining the exact elevation of the ground surface poses difficulties for both

discrete and waveform lidar.

In complex canopies, elevation returned from what appears to be the ground level in

fact may be from understorey, if the understorey is dense enough to substantially

obstruct the ground surface.

Each type of lidar system represents difficulties in detecting the uppermost portion of

the plant canopy.

Underestimation of canopy height

o With discrete return lidar, very high footprint densities are required to ensure

that the highest portion of individual tree crowns is sampled.

o With waveform sampling system, a large footprint is illuminated increasing

the probability that treetops will be illuminated by the laser.

The top portion of the crown in case of Conifers may not always be of sufficient area to

register. As a significant return signal, and therefore may not be detected. Estimation of

canopy cover and ground surface is often complimentary, i.e. if one is underestimated, then

the other would be overestimated and vice versa. Canopy Cover estimates are made using the

fraction of the lidar Measurements that are considered to have been returned from the ground

surface. Large footprint lidar measurements incorporating information contained in the laser

return waveform have been used to derive canopy height and structure in a variety of canopy

closure conditions. Often, scaling factor is required to correct the Relative reflectance of

ground and canopy surfaces at the Wavelength of the laser.

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9. TECHNIQUES:

The two main techniques for mapping of vegetation of forest;

1. Small footprint LiDAR

2. Large footprint LiDAR

Small footprint LiDAR:

Small-footprint lidar systems may not be optimal for mapping forest structure.

First, small diameter beams frequently over sample crown shoulders and miss the tops

of trees so that unless many shots are taken, the true canopy topography must be

reconstructed statistically. Secondly, because of their small beam size, mapping large

areas requires extensive flying. Finally, with systems that only record first and/or last

returns, it is difficult to determine whether or not a particular shot has penetrated the

canopy all the way to ground. If this topography cannot be reconstructed, accurate

height determination is impossible because canopy height is measured relative to the

ground.

Large footprint LiDAR:

Large-footprint systems have several advantages that help avoid these

problems. First, by increasing the footprint size to at least the average crown diameter

of a canopy-forming tree (10-25 m), laser energy consistently reaches the ground even

in dense forests. The larger footprint size also avoids the biases of small-footprint

sensors that may frequently miss the tops of trees. Secondly, large-footprint systems

enable a wide image swath, which reduces the expense of mapping large forested

areas Finally, large-footprint lidar systems also digitize the entire return signal, thus

providing a vertical distribution of intercepted surfaces (or "waveform") from the top

of the canopy to the ground.

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Small vs large footprint lidar for mapping of vegetation attributes

Small diameter beams frequently miss the

tree tops.

Large footprint beams avoid missing the

tree tops frequently. By increasing the

footprint size to the approximate crown

diameter of a canopy-forming tree (~10–

25m), laser energy consistently reaches

the ground, even in dense forests.

Because of their small beam size and low

flying height, mapping large areas requires

extensive flying, thus adding to the budget.

Large footprint systems fly at higher

altitudes and enable a wide image swath,

which reduces the expense of mapping

large areas on the

ground.

Usually, small footprint systems record the

first and/or last returns, thus making it

difficult to determine if a particular shot has

penetrated

the canopy all the way to ground.

Large footprint systems digitize the entire

return signal, thus providing data on the

vertical distribution of intercepted

surfaces from the top of the canopy to the

ground.

In areas of high canopy only one in several

thousand returns may be from the ground,

thus giving rise to the risk of inaccurate

height measurement relative to the ground.

This risk is reduced in case of large

footprint lidars.

It may not be optimal for mapping forest

structures.

This has many advantages for mapping of

forest structures. But the risk is that

biases from the blurring of ground and

canopy can become large as well, again

affecting height recovery.

Table 2

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10.LIDAR BASED FORESTRY STUDIES & CHARACTERISTICS

Vegetation

parameter Methodology Forest/vegetation type Lidar system

Vegetation height Comparison with field

measurement

Temperate deciduous

and desert scrub (tiger

bush), Niger, Africa

Agricultural Research

Service profiling laser;

gallium-arsenide diode

laser;904 nm

Tree height and

stand volume

Comparison with

Ground measurement

Coastal Scots pine

trees, Sweden

Helicopter-borne,

frequency-doubled Nd:

YAG laser; 532 and

1064 nm

Basal area,

volume

and biomass

Developed a canopy

structure model

Primary tropical wet

forest, USA

NASA P-3a

oceanographic lidar;

frequency doubled Nd:

YAG laser; 532 nm

Biomass and

volume

Comparison with

forest mensuration based

data

Southern pine forest,

USA

NASA P-3a

oceanographic lidar;

frequency doubled Nd:

YAG laser; 532 nm

Individual tree

height estimation

Comparison with tree

crown architecture and

coordinate location

Tolerant hardwood

forest, Canada

Optech‟s ALTM 1225

airborne lidar system

Canopy height Multi-fractal analysis Pine Savanna, USA -

Canopy height Multi-fractal analysis Pine Savanna, USA -

DTM of forest

area

and tree height

DTM algorithm Boreal forest, Norway -

Table 3

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11. CONCLUSION:

It is obvious that lidar is an accurate, fast and versatile measurement technique, which can

complement or partly replace other geo-data acquisition technologies and open up new,

exciting areas of application. The prediction of forest parameters is either direct or indirect.

For direct measurement, a characteristic such as height is estimated by first minus last return

of the raw data alone or by applying a linear transformation to the raw data. Indirect

Estimates are most often based on first estimating a fundamental parameter such as height

which is then fed into a predictive model for biomass and volume. Laser technique may prove

most useful to detect changes in the above ground carbon stores of the tropics, where the

most rapid and significant climate and vegetation changes are expected over the next decades.

Such measurements will improve our understanding of the effects of these factors on land

degradation and the hydrological and biological systems. A combination of lidar data and

satellite remote sensing data could also be useful for describing biodiversity and monitoring

changes in biodiversity. There is a large potential for savings, if laser data and image data

could be collected simultaneously, and stand delineation and characteristics usable for

stratification could be derived from existing auxiliary data and automated methods.

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12. INFERENCE:

It is amply clear that the lidar technique has become a prominent tool to collect accurate

high-resolution, three dimensional data. In addition, the typical characteristics of lidar data

have opened up the possibility of using them for many other applications which were not

thought of earlier. Notwithstanding the increasing use of this technology the world over, it is

not yet available in India. Lidar data have potential to be effective in many disaster

management programmes, including the most frequently occurring floods in India42.

However, this technology has the potential of conserving the precious forest resources and

providing better understanding of management, which are difficult to comprehend otherwise,

due to the limitations imposed by conventional and other data-collection techniques. Forest

management strategy in India should be based on reliable, lidar-derived database on forest

structure and its productive potential.

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13. REFERENCES:

1. M. D. Behera and P. S. Roy, “Lidar remote sensing for forestry applications: The

Indian context.” published in - CURRENT SCIENCE, VOL. 83, NO. 11, 10

DECEMBER 2002.

2. Champion, H. G. and Seth, S. K., “A Revised Survey of Forest Types of India”,

Manager of Publications, Government of India, New Delhi, 1968.

3. Wehr, A. and Lohr, U., ISPRS J. Photogramm. Remote Sensing, 1999, 54, 68–82.

4. http://www.tetonconservation.org/index.cfm?id=lidar

5. https://www.e-education.psu.edu/

6. http://www2.geog.ucl.ac.uk/~plewis/lidarforvegetation/lidarRS.pdf

7. http://www.forestry.ubc.ca/LinkClick.aspx?fileticket=SnNuPQUhzAs%3D&tabid=2768

&language=en-US