In this report I will explain the importance of remote sensing in general and explaining one of the most important system or application which is LIDAR (light detection and ranging) and I will explain all its types and uses and applications and the components and advantage of this system and how it works then I will mention the imaging system with explaining the primary and secondary return imaging in LiDAR

1. Differentiation between primary and
secondary LIDAR system of Remote
Sensing
Student Name: Copyright
Class: 4th
Stage
Course Title: Remote Sensing
Department: Geomatics (Surveying) Engineering
College of Engineering
Salahaddin University-Erbil
Academic Year 2019-2020

2. 1
Abstract
In this report I will explain the importance of remote sensing in general and explaining
one of the most important system or application which is LIDAR (light detection and
ranging) and I will explain all its types and uses and applications and the components
and advantage of this system and how it works then I will mention the imaging system
with explaining the primary and secondary return imaging in LiDAR.
LIDAR (Light Detection And Ranging) as a new high resolution earth space
information technology, has the characteristics of short data production cycle, little
influence by different weather, high degree of automation etc. Aiming at discussions
on making DEM, DOM and the point cloud processing, this paper briefly describes the
LIDAR data processing technology, states the present situation of this application in
aspects of national economic construction and military detection. And then the
application prospect forecast is put forward.
So all above I will explain in this report briefly with examples for the imaging system
I mean primary and secondary returns LIDAR system imaging.

3. 2
Table of content
Subject page
Abstract.......................................................................................................................... 1
Table of content............................................................................................................. 2
Chapter One - Introduction............................................................................................ 3
Chapter Two - Background & Review.......................................................................... 6
2.1. Present and Future Use System........................................................................... 6
2.2. LiDAR projects and applications........................................................................ 6
Chapter Three - Method ................................................................................................ 7
How LiDAR Works?.................................................................................................. 7
3.1. Lidar laser returns................................................................................................ 8
3.2. Image Acquisition ............................................................................................. 10
3.3. Lidar Imagery.................................................................................................... 11
3.4 Multiple return LiDAR ...................................................................................... 13
Chapter four - Theory.................................................................................................. 14
Conclusion................................................................................................................... 15
Reference..................................................................................................................... 16

4. 3
Chapter One - Introduction
In this chapter I introduce the remote sensing generally and LIDAR definition first of
all, remote sensing is the use of reflected and emitted energy to measure the physical
properties of distant objects and their surroundings. Thus, remote sensing is a source
of basic data, a science, and a tool. The measurements, whether recorded on a strip
chart, magnetic tape, or film, are the data. Remote sensing is a science because the
procedure consists of obtaining relative or absolute measurements, processing these
data either manually or by machine, interpreting the results, or drawing meaningful
conclusions. It is a tool because the conclusions can be used for making inventories of
resources and for solving ecological problems. Remote sensing includes the older
sciences of photography, photogrammetry, and airborne geophysical surveying as well
as newer techniques that use other parts of the electromagnetic spectrum. Many sensors
and techniques in remote sensing have application to hydrological problems and
studies. This paper describes the development of remote sensing and current areas of
hydrological research.
LiDAR, or light detection ranging (sometimes also referred to as active laser scanning)
is one remote sensing method that can be used to map structure including vegetation
height, density and other characteristics across a region. LiDAR directly measures the
height and density of vegetation on the ground making it an ideal tool for scientists
studying vegetation over large areas ,so LIDAR is a method or system for measuring
distances (ranging) by illuminating the target with laser light and measuring the
reflection with a sensor. Differences in laser return times and wavelengths can then be
used to make digital 3-D representations of the target. It has terrestrial, airborne, and
mobile applications.
The term LIDAR was originally a portmanteau of light and radar, It is now also used
as an acronym of "light detection and ranging and "laser imaging, detection, and
ranging Lidar sometimes is called 3-D laser scanning, a special combination of a 3-D
scanning and laser scanning.
Lidar is commonly used to make high-resolution maps, with applications in surveying,
geodesy, geomatics, archaeology, geography, geology, geomorphology, seismology,
forestry, atmospheric physics, and laser guidance.

5. 4
Why LiDAR?
Scientists often need to characterize vegetation over large regions to answer research
questions at the ecosystem or regional scale. Therefore, we need tools we need tools
that can estimate key characteristics over large areas because we don’t have the
resources to measure each and every tree or shrub.
Remote sensing means that we aren’t actually physically measuring things with our
hands. We are using sensors which capture information about a landscape and record
things that we can use to estimate conditions and characteristics. To measure vegetation
or other data across large areas, we need remote sensing methods that can take many
measurements quickly, using automated sensors.
What can LiDAR generate?
1. Number of Returns
2. Return Number
3. Digital Elevation Models
4. Digital Surface Models
5. Canopy Height Model
6. Light Intensity
7. Point Classification

6. 5
LiDAR system components
There are 4 main parts of an airborne LiDAR. They work together to produce highly
accurate, usable results:
LiDAR SENSORS: As the airplane travels, sensors scan the ground from side-to-side.
The pulses are commonly in green or near-infrared bands.
GPS RECEIVERS: GPS receivers track the altitude and location of the airplane.
These tracks are important for accurate terrain and elevation values.
INERTIAL MEASUREMENT UNITS (IMU): As airplanes travel, IMUs tracks its
tilt. LiDAR systems use tilt to accurately measure incident angle of the pulse.
DATA RECORDERS: As LiDAR scans the surface, a computer records all of the
pulse returns. Then, these recordings get translated into elevation.
Data Quality
Control Quality control for a LIDAR data set from a user’s perspective involves an
evaluation of return coordinate accuracy and precision, compliance with acquisition
specifications, and data spatial consistency and completeness. Ideally, a report with
quantitative estimates of these data quality measures would be part of every laser data
delivery. Unfortunately, such reports are rare, and when they are produced, the
information included is frequently selective or incomplete, in part because, as
discussed below, the procedures involved in evaluating data quality are costly and time
consuming, especially for data over mountainous forested areas.
Some factors affecting accuracy of LiDAR;
• Quality of the hardware and software
• Knowledge of the planners, operators, office staff
• Flying height
• Scan angle (also important for vegetation penetration)
• GPS configuration (PDOP and Number of SVs)
• Distance from base station to aerial platform
• Laser power
• Laser rep rate

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Chapter Two - Background & Review
2.1. Present and Future Use System
Today a wide variety of remote sensing instruments are available for use in
hydrological studies. Gamma-ray spectrometers can be mounted in aircraft for soil
moisture and snow-water-equivalent measurements. Similarly, aircraft-mounted
television cameras and multispectral scanners can be used to measure reflected
ultraviolet to near infra-red energy; thermal scanners detect emitted infra-red
wavelengths; and SLAR and passive microwave radiometers probe the surface and
near surface characteristics of materials at these wavelengths. For regional problems
and studies, satellite data such as Skylab photographs and Landsat images are available
for analysis and interpretation.
2.2. LiDAR projects and applications
The applications in which people use LiDAR is stunning. For example, here are some
ways how we use LiDAR today:
FORESTRY: Foresters use LiDAR to better understand tree structure and shape.
SELF-DRIVING CARS: Self-driving cars use LiDAR scanner to detect pedestrians,
cyclists, stop signs and other obstacles.
ARCHAEOLOGY: Archaeologists use LiDAR to find square patterns in the ground,
which were ancient buildings and pyramids built by Mayan and Egyptian
civilizations.
HYDROLOGY: Hydrologists delineate stream orders and tributaries from LiDAR.

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Chapter Three - Method
In this chapter I explain the Principal of work of LIDAR within primary and secondary
primary secondary returns and imaging system in LIDAR.
How LiDAR Works?
LiDAR is a sampling tool. What I mean by that is that it sends over 160,000 pulses per
second. For every second, each 1 meter pixel gets about 15 pulses. This is why LiDAR
point clouds create millions of points.
LiDAR is an active remote sensing system. An active system means that the system
itself generates energy - in this case, light - to measure things on the ground. In a
LiDAR system, light is emitted from a rapidly firing laser. You can imagine light
quickly strobing from a laser light source. This light travels to the ground and reflects
off of things like buildings and tree branches. The reflected light energy then returns
to the LiDAR sensor where it is recorded.
A LiDAR system measures the time it takes for emitted light to travel to the ground
and back. That time is used to calculate distance traveled. Distance traveled is then
converted to elevation. These measurements are made using the key components of a
LIDAR system including a GPS that identifies the X, Y, Z location of the light
energyand an Internal Measurement Unit (IMU) that provides the orientation of the
plane in the sky.
LiDAR systems are very accurate because it’s being controlled in a platform. For
example, accuracy is only about 15 cm vertically and 40 cm horizontally.
Figure 1: Airborne Light Detection and Ranging (LiDAR)

9. 8
As a plane travels in the air, LiDAR units scan the ground from side-to-side. While
some pulses will be directly below at nadir, most pulses travel at an angle (off-nadir).
So when a LiDAR system calculates elevation, it also accounts for angle.
Typically, linear LiDAR has a swath width of 3,300 ft. But new technologies like
Geiger LiDAR can scan widths of 16,000 ft. This type of LiDAR can cover much wider
footprints compared to traditional LiDAR.
The distance of the object = (Speed of Light x Time of Flight) / 2…….Eq (1)
3.1. Lidar laser returns
Laser pulses emitted from a LIDAR system reflect from objects both on and above the
ground surface: vegetation, buildings, bridges, and so on. One emitted laser pulse can
return to the LIDAR sensor as one or many returns. Any emitted laser pulse that
encounters multiple reflection surfaces as it travels toward the ground is split into as
many returns as there are reflective surfaces.
The first returned laser pulse is the most significant return and will be associated with
the highest feature in the landscape like a treetop or the top of a building. The first
return can also represent the ground, in which case only one return will be detected by
the LIDAR system.
Multiple returns are capable of detecting the elevations of several objects within the
laser footprint of an outgoing laser pulse. The intermediate returns, in general, are used
for vegetation structure, and the last return for bare-earth terrain models.The last return
Figure 2: number
of returns

10. 9
will not always be from a ground return. For example, consider a case where a pulse
hits a thick branch on its way to the ground and the pulse does not actually reach the
ground. In this case, the last return is not from the ground but from the branch that
reflected the entire laser pulse.
Figure 3: LiDAR returns when laser pulses hit the ground and trees

11. 10
3.2. Image Acquisition
Use wavelengths in the visible (e.g., 0.532 μm, green, for penetration of water bodies)
or near infrared (e.g., 1.64 μm for sensitivity to vegetation, ability to detect open water,
and freedom from atmospheric scattering) regions of the spectrum.
Several alternative designs for imaging LIDAR instruments are in use (Habib, 2010).
Figure 4 presents a schematic representation of a typical LIDAR system: (1) the
system’s laser (coordinated by the electronic component) generates a beam of coherent
light, transmitted by a fiber optic cable to (2) a rotating mirror, offset to provide a
scanning motion.
The laser light is directed to a bundle of fiber optic cables that can be twisted to transmit
the light as a linear beam. The oscillating motion of the mirror scans the laser beam
side to side along the cross-track axis of the image, recording many thousands of
returns each second. Because a LIDAR scanner is well integrated with GPS, IMU, and
timing systems, these pulses can be associated with specific points on the Earth’s
surface.
F
Figure 4: Schematic diagram of a LIDAR scanner.

12. 11
3.3. Lidar Imagery
Lidar imagery is acquired in parallel strips that match to form a continuous image of a
region. In Figure 4 the upper image shows the raw LIDAR data, with each pixel
representing the elevation of a specific point on the ground. Light tones represent
higher elevations, darker tones represent lower elevations. The lower image is formed
from the same data but is represented using a hill-shading technique that assumes that
each pixel is illuminated from the upper left corner of the image. This effect creates
image texture reminiscent of an aerial photograph, usually easier for casual
interpretation. enlargements of portions of the same image, selected to show some of
the distinctive qualities of LIDAR imagery. Depicts an interstate interchange, with
structures, forests, pastureland, and cropland, represented with precision and detail. a
nearby region. A deep quarry is visible at the center.
Open land and forest are again visible. The parallel strips visible near the upper right
Of this image depict mature corn fields—an indication of the detail recorded by these
Images. Coherent representation of the terrain. Plate 12 shows this effect rather well:
the upper portion of the illustration shows the original postings, whereas the lower half
shows the systematic grid formed by the interpolation process.
Thus each return from the ground surface can be precisely positioned in xyz space to
provide an array that records both position and elevation. For small-footprint LIDAR’s,
horizontal accuracy might be in the range of 20–30 cm and vertical accuracy in the
range of 15–20 cm. Therefore, the array, or image, forms a detailed DEM. With the
addition of ground control (points of known location that can be accurately located
within the imaged region, often found using GPS), LIDAR can provide data
comparable in detail and positional accuracy to those acquired by photogrammetric
analysis of aerial photographs. A LIDAR can record different kinds of returns from the
terrain. Some returns, known as primary returns, originate from the first objects a
LIDAR pulse encounters—often the upper surface of a vegetation canopy (Figure 5).
In addition, portions of a pulse pass through gaps in the canopy into the interior
structure of leaves and branches to lower vegetation layers and the ground surface
itself. This energy creates echoes known as secondary, or
Partial, returns. Therefore, for complex surfaces such as forests with multiple canopies,
some portions of a pulse might be reflected from upper and middle portions of the
canopy and other portions from the ground surface at the base (Figure 6).

13. 12
The total collection of LIDAR returns for a region can be examined to separate those
returns that originated above a specified level from those that originated below that
level.
This kind of approach can then form a kind of filtering process to separate ground
returns from nonground returns and, with additional analysis, can thereby separate the
terrain surface from overlying vegetation cover and structures
(Figure 7 and Plate 13). LIDAR’s are distinctive as one of the few sensors that can
reliably differentiate between multiple imaged layers.
FIGURE 5. Schematic diagram of primary and secondary LIDAR returns.

14. 13
3.4 Multiple return LiDAR
A laser pulse has a finite diameter (~10 cm and larger). It is possible that only a part
of the diameter comes across an object. This part of pulse will reflect from there, while
the rest of the pulse keeps travelling till it encounters other objects which result in
reflection of other parts of the pulse. On receiving the reflected laser pulse, the detector
triggers when the in-coming pulse reaches a set threshold, thus measuring the time-of-
flight. The sampling of the received laser pulse can be carried out in different ways-
sampling for the most significant return, sampling for the first and last significant
return, or sampling all returns which are above threshold at different stages of the
reflected laser waveform. Accordingly, the range is measured to each of those points
wherefrom a return occurred to yield their coordinates.
In the figure shown above the first return is the most significant return. In case of
capturing of only most significant return the coordinate of the corresponding point
(here the top of tree) only will be computed. Capturing of first and last returns as
shown above will result in determination of the height of the tree. It is important to
note that last return will not always from the ground. In case of a laser pulse hitting a
thick branch on its way to ground the pulse will not reach ground thus no last return
from ground. The last return will be from the branch which reflected entire laser
pulse. Commercially available sensors at present support up to 4 returns from each
fired laser pulse and provide the option to choose among first, first and last and all 4
returns data
Figure 6: Example of multiple returns from a tree

15. 14
Chapter four - Theory
Lidar data may not accurately represent shorelines, stream channels, and ridges.
Contours derived from LIDAR data may not form hydrographically coherent surfaces
com-
FIGURE .7. Primary and secondary LIDAR returns from two forested regions. This
illustration represents LIDAR return from two separate forested areas, shown in
profile. The dots near the top of the diagram represent the returns that are received first
(primary returns), and the dots at the lower and central portions of the diagram
represent the return received later (secondary returns). Note the contrast between the
dome-shaped canopy formed by the crowns of the deciduous forest (left) and the
peaked crowns of the coniferous canopy (right). The coniferous forest has only sparse
undergrowth, while the deciduous forest is characterized by abundant undergrowth.
From Peter Sforza and Sorin Popescu.

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Conclusion
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. There are a
number of conclusions to be drawn from the information presented herein. These deal
with LiDAR technology itself, the impact of the technology on the survey and mapping
industry, and the societal and economic benefits that accrue through its use.
They have been presented below in point form, in no particular order, so Lidar remote
sensing only recently has become available as a research tool, and it has yet to become
widely available. Nevertheless, it has already been shown to be an extremely accurate
tool for measuring topography, vegetation height, and cover, as well as more complex
attributes of canopy structure and function. In addition, the basic canopy structure
measurements made with LIDAR sensors have been shown to provide highly accurate
and nonasymptotic estimates of important forest stand structure indices, such as leaf
area index and aboveground biomass. Because the basic measurements made by
LIDAR sensors are directly related to vegetation structure and function, we expect that
these findings will continue to be corroborated in a variety of biomes, with similar
results.

17. 16
Reference
[1] - Book, Introduction to Remote Sensing Fifth Edition, (James B. Campbell
Randolph H. Wynne).
[2] - Book, Lidar for ecology and conservation ( Markus Melin, Aurélie C. Shapiro,
and Paul Glover-Kapfer. 2017. WWF Conservation Technology Series
1(3).WWF-UK, Woking, United Kingdom).
[3] - https://academic.oup.com/bioscience/article/52/1/19/291259
[4]-https://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/types-of-
lidar.htm
[5] - https://www.tandfonline.com/doi/pdf/10.1080/02626667909491887
[6] - https://www.engineeringcivil.com/what-is-lidar-and-discuss-its-importance-and-
possibilities.html
[7] - https://www.fs.fed.us/pnw/pubs/pnw_gtr768.pdf
[8]- https://www.neonscience.org/lidar-basics