Remote sensing and aerial photography study notes. Including concept and history of RS, visual image interpretation, digital image interpretation, application of RS, digital imaging, application of remote sensing etc.
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1. INTRODUCTION TO REMOTE SENSING
1.1: CONCEPT REMOTE SENSING
Remote Sensing is the process or technique of obtaining information about an object,
area or phenomenon through the analysis of data acquired by a device without being in
contact with the object, area or phenomenon being studied (Chandra, 2002b).
According to CCRS (Canada Centre for Remote Sensing), Remote Sensing is the
science of acquiring information about the earth’s surface without actually being in contact
with it. This is done by sensing and recording reflected or emitted energy and processing,
analyzing and applying that information.
1.2: COMPONENTS OF REMOTE SENSING
Platform: The vehicle which carries a sensor. i.e. satellite, aircraft, balloon, etc.
Sensors: Device that receives electromagnetic radiation and converts it into a signal that
can be recorded and displayed as either numerical data or an image. It can be Landsat TM,
Landsat ETM, and ALOS.
1.3: ELEMENTS/PROCESSES OF REMOTE SENSING
1. Energy Source or Illumination (A) - the first requirement for remote sensing is to
have an energy source which illuminates or provides electromagnetic energy to the target
of interest.
2. Radiation and the Atmosphere (B) - as the energy travels from its source to the
target, it will come in contact with and interact with the atmosphere it passes through.
This interaction may take place a second time as the energy travels from the target to the
sensor.
3. Interaction with the Target (C) - once the energy makes its way to the target through
the atmosphere, it interacts with the target depending on the properties of both the target
and the radiation.
4. Recording of Energy by the Sensor (D) - after the energy has been scattered by, or
emitted from the target, we require a sensor (remote - not in contact with the target) to
collect and record the electromagnetic radiation.
5. Transmission, Reception, and Processing (E) - the energy recorded by the sensor
has to be transmitted, often in electronic form, to a receiving and processing station
where the data are processed into an image (hardcopy and/or digital).
6. Interpretation and Analysis (F) - the processed image is interpreted, visually and/or
digitally or electronically, to extract information about the target which was illuminated.
7. Application (G) - the final element of the remote sensing process is achieved when we
apply the information we have been able to extract from the imagery about the target in
order to better understand it, reveal some new information, or assist in solving a
particular problem.
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1.4: TYPES OF REMOTE SENSING
It can be of two types: Active and Passive remote sensing.
1. Active sensors have its own source of light or illumination. In particular, it actively sends
a wave and measures that backscatter reflected back to it.
2. Passive sensors measure reflected sunlight emitted from the sun. When the sun shines,
passive sensors measure this energy.
1.5: SOURCE OF ENERGY
Electromagnetic radiation: It is a kind of radiation including visible light, radio waves, gamma
rays, and X-rays, in which electric and magnetic fields vary simultaneously. Their range band is
called EM spectrum.
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Energy: Energy is the ability to do work. In the process of doing work, energy is often transferred
from one body to another or from one place to another. The three basic ways in which energy
can be transferred include conduction, convection, and radiation.
Wavelength and frequency: Electromagnetic radiation is expressed by wavelength and
frequency. Wavelength refers to the length of the wave cycle and Frequency refers to the
number of cycles of a wave passing a fixed point per unit of time.
The radiation range:
1. Gamma: 10-14
meter
2. X-rays: 10-12
meter
3. Ultraviolet ray: 10-8
meter
4. Visible: 10-6
meter
5. Infrared: 10-4
meter
6. Microwave: 10-2
meter
7. Radio wave: 100
or 1 meter
Spectral regions used for remote earth observation:
i. Visible spectrum (0.4-0.7 µm): it is the frequency range for human eye. Medium solar
radiation. Subdivided in red, green and blue.
ii. Near infrared (0.7-1.1 µm): Also called photographic reflected IR. It is the solar energy
reflected by anybody. Its behavior is similar to the visible spectrum.
iii. Middle infrared (1.1-8 µm): solar radiation and emission band. The atmosphere is
significantly affected. It is exploited to measure vapor of water, ozone aerosol etc.
iv. Thermal infrared (8-14 µm): radiation emitted by the bodies themselves. It may be
determined by the body temperature. Images are available regardless the time of capture
(any time of the day).
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v. Microwave (1 mm- 1 m): It is used by the active sensors mostly. There is a growing
interest in remote sensing to use this particular band in data acquisition.
1.6: INTERACTION WITH THE ATMOSPHERE
1. Absorption: Absorption is the process by which radiant energy is absorbed and
converted into other forms of energy. Ozone, Carbon dioxide and water vapors are the
3 elements of absorption.
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2. Scattering: Atmospheric scattering is unpredictable diffusion of radiation by particles in
the atmosphere. Scattering is the process where an atom, molecule or particle redirects
energy.
i. Rayleigh scattering: Atmospheric gas or small molecule scatters radiation by a
process known as Rayleigh scattering. Rayleigh scatter is common when radiation
interacts with atmospheric molecules and other tiny particles that are much
smaller in diameter than the wavelength of the interacting radiation. The effect of
Rayleigh scatter is inversely proportional to the fourth power of wavelength.
ii. Mie Scattering: Another type of scatter is Mie scatter, which exists when
atmospheric particle diameters essentially equal to the energy wavelengths being
sensed. Water vapor and dust are major causes of Mie scatter. This type of scatter
tends to influences longer wavelengths compared to Rayleigh scatter. Although
Rayleigh scatter tends to dominate under most atmospheric conditions, Mie
scatter is significant in slightly overcast ones. Examples: water vapor, smoke
particles, fine dust etc.
iii. Raman Scattering: It caused by atmospheric particles which are lagers, smaller
or equal to the wavelength of the radiation being sensed. Example: gaseous
molecules, water droplets, fumes or dust particle. It causes loss or gain of energy
and consequently increase or decrease of wavelength.
iv. Non-selective Scattering: It comes when the diameters of the particles causing
scatter are much (10 times) larger than the energy wavelengths being sensed.
Water droplets, for example, cause such scatter. They commonly have a diameter
in the 5 to 100 µm (micro meter, 10-6 m) range and scatter all visible and Reflected
IR wavelengths about equally. Examples: water droplets, ice crystals, volcanic ash,
Smog etc.
3. Refraction: When EMR encounters substances of different densities, air and water,
refraction may take place. Refraction refers to the bending of light when it passes from
one medium to another. Retraction occurs because the media are of different densities
and the difference of speed of EMR in different media.
4. Transmission: A material transmits light when it allows the light to pass through it.
Transparent materials allow all the light to pass through them so that you can easily see
what is on the other side. Examples of transparent materials are glass, water, and air.
Translucent materials scatter the light that passes through them.
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1.7: INTERACTION WITH THE TARGET
Electromagnetic radiation that passes through the earth's atmosphere without being absorbed or
scattered reaches the earth's surface to interact in different ways with different materials
constituting the surface. When electromagnetic energy is incident on any given earth surface
feature, three fundamental energy interactions with the feature are possible.
There are three ways in which the total incident energy will interact with earth's surface
materials. These are
Absorption
Transmission
Reflection
Absorption (A) occurs when radiation (energy) is absorbed into the target while transmission (T)
occurs when radiation passes through a target. Reflection (R) occurs when radiation "bounces"
off the target and is redirected.
How much of the energy is absorbed, transmitted or reflected by a material will depend upon:
Wavelength of the energy
Material constituting the surface, and
Condition of the feature.
Reflection from surfaces occurs in two ways:
1. When the surface is smooth, we get a mirror-like or smooth reflection where all (or
almost all) of the incident energy is reflected in one direction. This is called Specular
Reflection and gives rise to images.
2. When the surface is rough, the energy is reflected uniformly in almost all directions. This
is called Diffuse Reflection and does not give rise to images.
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Vegetation:
A chemical compound in leaves called chlorophyll strongly absorbs radiation in the red and blue
wavelengths but reflects green wavelengths.
Leaves appear "greenest" to us in the summer, when chlorophyll content is at its
maximum. In autumn, there is less chlorophyll in the leaves, so there is less absorption
and proportionately more reflection of the red wavelengths, making the leaves appear red
or yellow (yellow is a combination of red and green wavelengths).
The internal structure of healthy leaves act as excellent diffuse reflectors of near-infrared
wavelengths. If our eyes were sensitive to near-infrared, trees would appear extremely
bright to us at these wavelengths. In fact, measuring and monitoring the near-IR
reflectance is one way that scientists can determine how healthy (or unhealthy) vegetation
may be.
Water:
Longer wavelength visible and near infrared radiation is absorbed more by water than shorter
visible wavelengths. Thus water typically looks blue or blue-green due to stronger reflectance at
these shorter wavelengths, and darker if viewed at red or near infrared wavelengths.
If there is suspended sediment present in the upper layers of the water body, then this
will allow better reflectivity and a brighter appearance of the water.
The apparent color of the water will show a slight shift towards longer wavelengths.
Suspended sediment (S) can be easily confused with shallow (but clear) water, since these
two phenomena appear very similar.
Chlorophyll in algae absorbs more of the blue wavelengths and reflects the green, making
the water appear greener in color when algae is present.
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The topography of the water surface (rough, smooth, floating materials, etc.) can also lead
to complications for water-related interpretation due to potential problems of specular
reflection and other influences on color and brightness.
We can see from these examples that, depending on the complex make-up of the target
that is being looked at, and the wavelengths of radiation involved, we can observe very
different responses to the mechanisms of absorption, transmission, and reflection.
Spectral Response of Materials:
By measuring the energy that is reflected (or emitted) by targets on the Earth's surface over a
variety of different wavelengths, we can build up a spectral response for that object. The spectral
response of a material to different wavelengths of EMR can be represented graphically as a
Spectral Reflectance Curve.
It may not be possible to distinguish between different materials if we were to compare their
response at one wavelength. But by comparing the response patterns of these materials over a
range of wavelengths (in other words, comparing their spectral reflectance curves), we may be
able to distinguish between them. For example, water and vegetation may reflect somewhat
similarly in the visible wavelengths but are almost always separable in the infrared.
Spectral response can be quite variable, even for the same target type, and can also vary with
time (e.g. "green-ness" of leaves) and location.
1.8: INTERPRETATION AND ANALYSIS
Data alone cannot be used for decision making. They need to be analyzed and interpreted. There
are two major process of interpretation and analysis.
1. Analogue image interpretation
2. Digital image processing
1.8.1. Analogue/visual Image Interpretation:
It’s a process of visually exploring data to understand and comprehend. Refers to the size, shape,
shadow, color, parallax, pattern, texture, size and association.
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1.8.2: Digital image processing
Digital image processing is the use of computer algorithms to perform image processing on digital
images. Human eyes can only see 40-50 shades of grey when there can be 256 shades of grey.
These other bands that human eyes cannot see can be analyzed digitally. It includes statistical and
syntactical analysis.
The elements of analysis of digital image processing are-
1. Enhanced map
2. Orthophoto map
3. Thematic map
4. Spatial database file
5. Statistics
6. Graph
Details technique will be discussed in the chapter ‘Digital Image Interpretation’.
1.9: ADVANTAGES OF REMOTES SENSING
1. Provides a regional view
2. Provides repetitive looks at the same area
3. Remote sensors "see" over a broader portion of the spectrum than the human eye
4. Sensors can focus in on a very specific bandwidth in an image or a number of bandwidths
simultaneously
5. Provides geo-referenced, digital, data
6. Some remote sensors operate in all seasons, at night, and in bad weather
1.10: APPLICATION OF REMOTE SENSING
1. Land use mapping
2. Forest and agriculture application
3. Telecommunication planning
4. Environmental application
5. Hydrology and coastal mapping
6. Urban planning
7. Emergency and hazards
8. Global change and methodology
1.11: LIMITATION OF REMOTE SENSING
1. Expensive
2. Sophisticated
3. Power set of tools
4. Lack of fund
5. Human errors
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2. REMOTE SENSING PLATFORM AND SENSOR
CHARACTERISTICS
2.1: CHARACTERISTICS OF IMAGE
Electromagnetic energy may be detected either photographically or electronically.
The photographic process uses chemical reactions on the surface of light-sensitive film to
detect and record energy variations.
It is important to distinguish between the terms images and photographs in remote
sensing.
An image refers to any pictorial representation, regardless of what wavelengths or remote
sensing device has been used to detect and record the electromagnetic energy.
A photograph refers specifically to images that have been detected as well as recorded
on photographic film.
The black and white photo to the left, of part of the city of Ottawa, Canada was taken in
the visible part of the spectrum. Photos are normally recorded over the wavelength range
from 0.3 µm to 0.9 µm - the visible and reflected infrared. Based on these definitions, we
can say that all photographs are images, but not all images are photographs.
Therefore, unless we are talking specifically about an image recorded photographically,
we use the term image.
A photograph could also be represented and displayed in a digital format by subdividing
the image into small equal-sized and shaped areas, called picture elements or pixels, and
representing the brightness of each area with a numeric value or digital number.
Indeed, that is exactly what has been done to the photo to the left. In fact, using the
definitions we have just discussed, this is actually a digital image of the original photograph!
The photograph was scanned and subdivided into pixels with each pixel assigned a digital
number representing its relative brightness.
The computer displays each digital value as different brightness levels.
Sensors that record electromagnetic energy, electronically record the energy as an array
of numbers in digital format right from the start.
These two different ways of representing and displaying remote sensing data, either
pictorially or digitally, are interchangeable as they convey the same information.
In previous sections we described the visible portion of the spectrum and the concept of
colours.
We see colour because our eyes detect the entire visible range of wavelengths and our
brains process the information into separate colours. Can you imagine what the world
would look like if we could only see very narrow ranges of wavelengths or colours? That
is how many sensors work.
The information from a narrow wavelength range is gathered and stored in a channel, also
sometimes referred to as a band.
We can combine and display channels of information digitally using the three primary
colours (blue, green, and red).
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The data from each channel is represented as one of the primary colours and, depending
on the relative brightness (i.e. the digital value) of each pixel in each channel, the primary
colours combine in different proportions to represent different colours.
2.2: REMOTE SENSING PLATFORMS
Platform
The vehicle or carrier for a remote sensor to collect and record energy reflected or emitted
from a target or surface is called a platform. The sensor must reside on a stable platform removed
from the target or surface being observed. Platforms for remote sensors may be situated on the
ground, on an aircraft or balloon (or some other platform within the Earth's atmosphere), or on
a spacecraft or satellite outside of the Earth's atmosphere.
Typical platforms are satellites and aircraft, but they can also include radio-controlled aero-planes,
balloons kits for low altitude remote sensing, as well as ladder trucks or 'cherry pickers' for
ground investigations. It can be of 3 types-
1. Ground based sensors
2. Aerial platforms
3. Satellite platforms
2.2.1: Ground Based Sensors
Ground-based sensors are often used to record detailed information about the surface which is
compared with information collected from aircraft or satellite sensors. In some cases, this can be
used to better characterize the target which is being imaged by these other sensors, making it
possible to better understand the information in the imagery.
Ground based sensors may be placed on a ladder, scaffolding, tall building, cherry-picker, crane,
etc.
2.2.2: Aerial Platforms
Aerial platforms are primarily stable wing aircraft, although helicopters are occasionally used.
Aircraft are often used to collect very detailed images and facilitate the collection of data over
virtually any portion of the Earth's surface at any time.
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2.2.3: Satellite Platforms
In space, remote sensing is sometimes conducted from the space shuttle or, more commonly,
from satellites. Satellites are objects which revolve around another object - in this case, the Earth.
For example, the moon is a natural satellite, whereas man-made satellites include those platforms
launched for remote sensing, communication, and telemetry (location and navigation) purposes.
2.3: ACTIVE AND PASSIVE PLATFORM
See 1.4
2.4: IMAGE REFERENCING SYSTEM
Image referencing system also called worldwide referencing system is a process of identifying
geographical location with satellite. According to USGS, The Worldwide Reference System
(WRS) is a global notation system for Landsat data. It enables a user to inquire about satellite
imagery over any portion of the world by specifying a nominal scene center designated by PATH
and ROW numbers. The WRS has proven valuable for the cataloging, referencing, and day-to-
day use of imagery transmitted from the Landsat sensors.
It has two elements-
1. Path: An orbit is the course of motion taken by satellite in space and the ground is called
a path.
2. Row: Row refers to the latitudinal centre line of a frame of imagery.
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3. HISTORY OF REMOTE SENSING
3.1: SECTIONS OF RS HISTORY
It can be described in 3 sections-
1. The early age (1609-1907)
2. The middle age (1908-1945)
3. The modern age (1946-onwards)
3.2: IMPORTANT PERIODS
The beginning: photography and flight (1858-1918)
Rapid developments in photogrammetry (1918-1939)
Military imperatives (1939-1945)
Cold wars and environmental concerns (1946-1971)
Dawning of a new age (1972-1986)
Commercialization, and geo-location (1986-1999)
No place left to hide (2000-future)
3.3: IMPORTANT EVENTS
1839 PHOTOGRAPHY WAS INVENTED
1858 Parisian Photographer, Gaspard Felix Tournachon used a balloon to ascend
to a height of 80m to obtain the photograph over Bievre, France
1882 Kites were used for photography
1909 Airplanes were used as a platform for photography
1910-20 World War I. Aerial reconnaissance: Beginning of photo interpretation
1920-50 Aerial photogrammetry was developed
1934 American Society of Photogrammetry was established. Radar development
for military use started
1940'S Color photography was invented
1940'S Non-visible portions of electromagnetic spectrum, mainly near-infrared,
training of photo-interpretation
1950-1970 Further development of non-visible photography, multi-camera
photography, color-infrared photography, and non-photographic sensors.
Satellite sensor development - Very High Resolution Radiometer (VHRR),
Launch of weather satellites such as Nimbus and TIROS
1962 The term "Remote Sensing" first appeared
1972 The launch of Landsat-1, originally ERTS-1,Remote sensing has been
extensively investigated and applied since then
1982 Second generation of Landsat sensor: Thematic Mapper
1986 French SPOT-1 High Resolution Visible sensors MSS, TM, HRV have been
the major sensors for data collection for large areas all over the world.
Such data have been widely used in natural resources inventory and
mapping. Major areas include agriculture, forest, wet land, mineral
exploration, mining, etc.
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1980-90 Earth-Resources Satellite from other countries such as India, Japan, and
USSR. Japan's Marine Observing Satellite (MOS - 1)
1986- A new type of sensor called an imaging spectrometer, has been developed.
developers: JPL, Moniteq,ITRES and CCRS.
Products: AIS, AVIRIS, FLI, CASI, SFSI, etc. A more detailed
description of this subject can be found in Staenz (1992).
1990- Proposed EOS aiming at providing data for global change monitoring.
Various sensors have been proposed.
Japan's JERS-1 SAR,
European ERS Remote Sensing Satellite SAR,
Canada's Radarsat
Radar and imaging spectrometer data will be the major theme of
this decade and probably next decade as well
3.4: LANDSAT MISSIONS
Mission Year Task
Landsat 1 1972-1978 Obtaining information on agricultural and forestry resources,
geology and mineral resources, hydrology and water resources,
geography, cartography, environmental pollution, oceanography
and marine resources, and meteorological phenomena.
Landsat 2 1975-1983 To acquire global, seasonal data in medium resolution from a near-
polar, sun-synchronous orbit.
Landsat 3 1978-1983 Providing a global archive of satellite imagery
Landsat 4 1982-1993 Thematic Mapper
Landsat 5 1984-2013 More developed Thematic Mapper
Landsat 6 1993- More developed Thematic Mapper
Landsat 7 1999- To refresh the global archive of satellite photos, providing up-to-
date and cloud-free images
Landsat 8 2013- Collect and archive medium resolution (30-meter spatial
resolution) multispectral image data
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3.4.1: Landsat Application
Remote sensing provides information about geographic spaces, like ecosystems that allows
scientists to predict the distribution of species, as well as detecting both natural occurring and
anthropogenic generated changes in a greater scale than traditional data provided by field work.
It also presents data more accurately than models that are derived from field work. The different
bands in Landsat, with diverse spectral range provide highly differentiated applications. There are
big and diverse applications of Landsat imagery and satellite date in general, ranging from ecology
to geopolitical matters. Land cover determination has become a very common use of Landsat
Imagery and remotely sensing generated images all around the world.
Usages are-
Natural Resource Management
Agroindustry
Forestry
Climate change and environmental disasters
The shrinking of the Aral Sea
Yellowstone park historic fires
Glacier retreat
Discovery of new species
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4. DIGITAL IMAGING
4.1: DIGITAL IMAGE
A digital image typically composed of picture elements (pixels) located at the intersection of
each row and column and each band of imagery. Associated with each pixel is a number known
as Digital Number (DN) or Brightness Value (BV), that depicts the average radiance of a
relatively small area within a scene. A smaller number indicates low average radiance from the
area and the high number is an indicator of high radiant properties of the area. The size of this
area effects the reproduction of details within the scene. As pixel size is reduced more scene
detail is presented in digital representation.
4.2: CHARACTERISTICS OF DIGITAL IMAGE RESOLUTION
There are 4 types of resolution of digital image.
1. Spatial resolution
2. Spectral resolution
3. Temporal resolution
4. Radiometric resolution
4.2.1: Spatial resolution
Spatial Resolution describes how much detail in a photographic image is visible to the human eye.
The ability to "resolve," or separate, small details is one way of describing what we call spatial
resolution. A measure of the size of the pixel is given by the Instantaneous Field of Views (IFOV)
which is dependent on the latitude and the viewing angle of sensor.
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4.2.2: Spectral Resolution
Spectral resolution is related to the width of spectral wavelength band that the sensor is sensitive
to. A system which measures a large number of bands which encompass the narrow range of
electromagnetic spectrum is said to have a high spectral resolution.
4.2.3: Temporal Resolution
Temporal resolution refers to how often data are obtained from the same area. It is the minimum
time between two successive image acquisitions over the surface of the earth. Temporal
considerations area-
Leaf on/leaf off
Tidal stage
Seasonal difference
Shadows
Phonological difference
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Relationship to field sampling
4.2.4: Radiometric Resolution
A film or sensors sensitivity to magnitude of the electromagnetic energy determines the
radiometric resolution. Every time an image is acquired by a sensor, its sensitivity to the
magnitude of the electromagnetic energy determines the radiometric resolution. The finer the
radiometric resolution of a sensor, the more sensitive it is to detecting small differences in
reflected or emitted energy.
The maximum number of brightness levels available depends on the number of bits used in
representing the energy recorded. Thus, if a sensor used 8 bits to record the data, there would
be 28
=256 digital values available, ranging from 0 to 255.
4.3: PAN/MULTISPECTRAL IMAGING
4.3.1: Multispectral Image and Panchromatic Image
Multispectral image: A multispectral image is one that captures image data within
specific wavelength ranges across the electromagnetic spectrum.
Panchromatic image: Panchromatic images are created when the imaging sensor is
sensitive to a wide range of wavelengths of light, typically spanning a large part of the
visible part of the spectrum. Here is the thing, all imaging sensors need a certain minimum
amount of light energy before they can detect a difference in brightness.
4.3.2: Multispectral scanner (MSS)
Many electronic (as opposed to photographic) remote sensors acquire data using scanning
systems, which employ a sensor with a narrow field of view (i.e. IFOV) that sweeps over the
terrain to build up and produce a two-dimensional image of the surface. Scanning systems can be
used on both aircraft and satellite platforms and have essentially the same operating principles. A
scanning system used to collect data over a variety of different wavelength ranges is called a
multispectral scanner (MSS), and is the most commonly used scanning system.
4.3.3: MSS of PAN/MULTISPECTRAL Imaging
There are two main modes or methods of scanning employed to acquire multispectral image
data-
1. Across-track scanning
2. Along-track scanning.
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4.3.3.1: Across-track Scanning
Across-track scanners scan the Earth in a series of lines. The lines are oriented perpendicular to
the direction of motion of the sensor platform (i.e. across the swath). Each line is scanned from
one side of the sensor to the other, using a rotating mirror (A). As the platform moves forward
over the Earth, successive scans build up a two-dimensional image of the Earth´s surface. The
incoming reflected or emitted radiation is separated into several spectral components that are
detected independently. The UV, visible, near-infrared, and thermal radiation are dispersed into
their constituent wavelengths. A bank of internal detectors (B), each sensitive to a specific range
of wavelengths, detects and measures the energy for each spectral band and then, as an electrical
signal, they are converted to digital data and recorded for subsequent computer processing.
The IFOV (C) of the sensor and the altitude of the platform determine the ground resolution cell
viewed (D), and thus the spatial resolution. The angular field of view (E) is the sweep of the
mirror, measured in degrees, used to record a scan line, and determines the width of the imaged
swath (F).
4.3.3.2: Along-track Scanning
Along-track scanners also use the forward motion of the platform to record successive scan lines
and build up a two-dimensional image, perpendicular to the flight direction. However, instead of
a scanning mirror, they use a linear array of detectors (A) located at the focal plane of the image
(B) formed by lens systems (C), which are "pushed" along in the flight track direction (i.e. along
track). These systems are also referred to as push broom scanners, as the motion of the detector
array is analogous to the bristles of a broom being pushed along a floor. Each individual detector
measures the energy for a single ground resolution cell (D) and thus the size and IFOV of the
detectors determines the spatial resolution of the system. A separate linear array is required to
measure each spectral band or channel. For each scan line, the energy detected by each detector
of each linear array is sampled electronically and digitally recorded.
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4.3.4: Landsat MSS, Landsat TM, Landsat ETM
4.3.4.1: Landsat MSS
Landsat MSS was the first which used across track technique. The Multispectral Scanner (MSS)
sensor acquired imagery of the earth from July 1972 to January 1999 on board Landsat 1 through
5. Imagery collected during the first decade of these missions predates most other operational
imaging efforts, providing a unique view of the earth not available elsewhere. These early missions
also offered the first digital remote sensing products to the earth science community.
4.3.4.2: Landsat TM
A more sophisticated multispectral imaging sensor. Named TM has added to Landsat 4, 5 and 6.
These TMS flew on redesigned, more advanced platforms. Although similar in operational modes
to MSS, the TM consists of 7 bands that possess various characteristics.
4.3.4.3: Landsat ETM+
Landsat 7 was lunched on 15 April 1999 and was designated to achieve the following objects:
1. Maintain data continuity
2. Cloud free imagery
3. Landsat type data for a global change research.
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4.4: HYPER SPECTRAL IMAGING
Hyper spectral imaging, like other spectral imaging, collects and processes information from
across the electromagnetic spectrum. The goal of hyper spectral imaging is to obtain the spectrum
for each pixel in the image of a scene, with the purpose of finding objects, identifying materials,
or detecting processes. There are two general branches of spectral imagers. There are push
broom scanners and the related whisk broom scanners, which read images over time, and
snapshot hyper spectral imaging, which uses a staring array to generate an image in an instant.
There are a lot of systems of hyper spectral imaging adopted by different governments. Three of
them are most prominent.
1. Airborne Visible / Infrared Imaging Spectrometer: The airborne visible/infrared
imaging spectrometer (AVIRIS) is the second in a series of imaging spectrometer instruments
developed at the Jet Propulsion Laboratory (JPL) for Earth remote sensing. This instrument uses
scanning optics and four spectrometers to image a 614-pixel swath simultaneously in 224
adjacent spectral bands.
2. Compact Airborne Spectrographic Imager (CASI-2): One of the hyper spectral
sensors is the Compact Airborne Spectrographic Imager (CASI), the first commercial imaging
spectrometer. This hyper spectral sensor detects a vast array of narrow spectral bands in the
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visible and infrared wavelengths, using along-track scanning. The spectral range covered by the
288 channels is between 0.4 and 0.9 µm. Each band covers a wavelength range of 0.018 µm.
3. Moderate Resolution Imaging Spectrometer (MODIS): The Moderate Resolution
Imaging Spectrometer/Spectroradiometer (MODIS) is one of a number of instruments carried on
board the Terra platform, which was launched in December 1999. MODIS provides continuous
global coverage every one to two days, and collects data from 36 spectral bands (band
designations). Two bands (1-2) have a resolution of 250 meters. Five bands (3-7) have a
resolution of 500 meters. The remaining bands (8-36) have a resolution of 1000 meters. The
swath width for MODIS is 2,330 kilometers.
4.5: THERMAL IMAGING
Many multispectral (MSS) systems sense radiation in the thermal infrared as well as the visible
and reflected infrared portions of the spectrum. However, remote sensing of energy emitted
from the Earth's surface in the thermal infrared (3 μm to 15 μm) is different than the sensing of
reflected energy. Thermal sensors use photo detectors sensitive to the direct contact of photons
on their surface, to detect emitted thermal radiation. The detectors are cooled to temperatures
close to absolute zero in order to limit their own thermal emissions. Thermal sensors essentially
measure the surface temperature and thermal properties of targets.
Thermal imagers are typically across-track scanners (like those described in the previous section)
that detect emitted radiation in only the thermal portion of the spectrum. Thermal sensors
employ one or more internal temperature references for comparison with the detected radiation,
so they can be related to absolute radiant temperature. The data are generally recorded on film
and/or magnetic tape and the temperature resolution of current sensors can reach 0.1 °C. For
analysis, an image of relative radiant temperatures (a thermogram) is depicted in grey levels, with
warmer temperatures shown in light tones, and cooler temperatures in dark tones. Imagery
which portrays relative temperature differences in their relative spatial locations are sufficient for
most applications. Absolute temperature measurements may be calculated but require accurate
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calibration and measurement of the temperature references and detailed knowledge of the
thermal properties of the target, geometric distortions, and radiometric effects.
4.5.1: Properties and equation
a. Thermal Capacity (c): The ability to absorb heat energy.
b. Thermal Conductivity (K): Heat transfer rate through a substance.
c. Thermal Inertia (P): Thermal responses in per unit area of a material.
The equation is: P= √ (K-p-c) [here, p= density]
4.6: IMAGING BY DIGITAL AERIAL CAMERA
4.6.1: Digital Aerial Camera
When the ground resolution becomes less than 1 meter than the digital cameras are very essential
to perform remote sensing. Digital Aerial Cameras are cameras that are designed to be used on
flying survey platforms. They are widely used for mapping projects in combination with
photogrammetric or LIDAR technology.
4.6.2: Advantages of Digital Aerial Camera
A completely digital flow line.
Significantly improved radiometric image quality.
The possibility to simultaneously acquire color, PAN and NIR (near infrared) Image.
4.6.3: Process of digital aerial photography
1. Mechanical shutter opens to expose the CCD sensor to light.
2. Light is converted to charge in CCD.
3. The shutter closes, blocking the light.
4. The charge is transferred to CCD output register and converted into signal.
5. The signal is digitalized and stored in computer memory.
6. The stored image is processed and displayed on the camera’s liquid crystal display, on a
computer screen or used to make hard copy print.
4.6.4: Types of Photography
Types Description Advantage Disadvantage
Panchromatic
Photography
Records variation of
EMR in visible range
of the spectrum.
Cheap and does not
sophisticated processing.
Some objects
(bridges, roads
buildings) are not
distinguishable.
Black and White
infrared
photography
Sensitivity extends to
near infrared.
Spectral reflectivity
characteristics can be
examined. Land-water
interfaces can be
distinguished in vegetation
survey.
Objects below
surface cannot be
detected.
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Natural color
photography
Sensitive to RGB
band of spectrum
individually.
Easy interpretation.
Undistinguished objects of
black and white
photography can be
distinguished.
Complex process
and expensive.
Multiband
photography
Can obtain different
band sense
simultaneously (RGB
band together).
False composition of natural
color photography can be
detected.
The camera system
is much more
complex. `
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5. VISUAL IMAGE INTERPRETATION
5.1: VISUAL IMAGE INTERPRETATION CONCEPT
Photo or image interpretation is the examination of images for the purpose of identifying objects
and judging their significance (Phillipson, 1997). The imagery that are interpreted may be acquired
using by various sensors, including analogue cameras, digital cameras, multispectral scanner and
linear sensor system.
Visual image processing does not only including the interpretation of the features of a satellite
image that can be seen, but also those features that cannot be seen and goes beyond machinery
understanding. It may include two basic objects-
1. The recognition of the object (that can be seen)
2. The true interpretation (that can be seen or cannot be)
5.2: REASONS TO INTERPRET THE IMAGE
1. Scale: aerial/regional perspective
2. 3 dimensional depth perception
3. Ability to obtain knowledge beyond our human visual interpretation
4. Ability to obtain a historical image record to document change
5.3: ELEMENTS OF IMAGE INTERPRETATION AND KEYS
1. x, y location: Longitude and latitude, meters easting and northing in a UTM grid map.
2. Size: Size of an object with the following parameters- length, width, perimeter, area and
occasionally volume.
3. Shape: geometric characteristics of an object, e.g. linear, circular, elliptical, rectangular,
parallel, centripetal, braided, striated etc.
4. Shadow: A silhouette caused by solar illumination from the side.
5. Tone/color: Gray tone: light (bright), intermediate (gray), dark (black). Color: RGB (red,
green, blue), HIS (intensity, hue, saturation)
6. Texture: Characteristics placements and arrangements of repetition tone or color. E.g.
smooth, intermediate, rough, stippled, mottled etc.
7. Pattern: Spatial arrangements of object of a ground. Example: systemic, random, circular,
elliptical, rectangular, parallel, centripetal, braided, striated etc.
8. Height/depth: Elevation (height), bathymetry (depth), volume, slope, aspect.
9. Site (elevation, slope, aspect): Elevation, slope, aspect, exposure, adjacency to water,
transportation, utilities.
10.Situation: Objects are placed in a particular order or orientation relative to one another.
11.Association: Relative phenomena are usually present.
5.4: ADVANTAGE OF VISUAL INTERPRETATION
Simple method
Inexpensive equipment
Uses brightness and spatial content of the image
Subjective and Qualitative
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Concrete
Human brain are best data processor.
Expertise in this arena will enhance the technology.
This is the backbone of remote sensing.
5.5: DISADVANTAGE OF VISUAL INTERPRETATION
Unfamiliar scale and resolutions.
Lack of understanding of physics of remote sensing.
Understanding proper spectral character of each object
Visually interpret 3 layers of information at a time.
Cannot process more than one band at a time.
Time consuming and costly.
Training and expertise required.
5.6: INFORMATION EXTRACTION BY HUMAN AND COMPUTER
Human knowledge are the best data processing method.
But they are biased, time consuming, person to person varying, and one analysis at a time
limitation.
Computer are time saving, fast and have advantages of common analyzing results, multiple
analysis at a time, accuracy control, auto correction, map generation, database updating
etc.
But there are lack of human knowledge, expensiveness, poor spatial information
extraction system and required high expertise in computer.
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5.7: METADATA
Metadata is ‘data about the data’ and it’s vital to understanding to source, currency, scale, and
appropriateness of using gis data. Metadata can be stored as an inherent part of the gis data, or
it may be stored as a separate document.
Examples of information (this is not a comprehensive list) contained within metadata are: creation
date of the gis data, gis data author, contact information, source agency, map projection and
coordinate system, scale, error, explanation of symbology and attributes, data dictionary, data
restrictions, and licensing. Essentially, metadata is a description of the gis data set that helps the
user understand the context of the data.
Metadata is also known as Image Support Data (ISD). This file specifies the basic characteristics
of an image. It contains all the information regarding the product/Image like the date and time of
acquisition, solar zenith angle , azimuth angle, number of Rows , number of columns, number of
bands, spatial, radiometric resolution, order number , file type etc., Metadata file of imagery come
with in the CD along with the satellite imagery product ordered in MTL format. This file helps
us in knowing about the satellite image and for calculating the reflectance for every pixel.
5.8: RADAR IMAGE INTERPRETATION
Radar images have certain characteristics that are fundamentally different from images obtained
by using optical sensors such as Landsat, SPOT or aerial photography. These specific
characteristics are the consequence of the imaging radar technique, and are related to radiometry
(speckle, texture or geometry).
During radar image analysis, the interpreter must keep in mind the fact that, even if the image is
presented as an analog product on photographic paper, the radar "sees" the scene in a very
different way from the human eye or from an optical sensor; the grey levels of the scene are
related to the relative strength of the microwave energy backscattered by the landscape elements.
Radar interpretation elements:
Tone: Radar imagery tone can be defined as the average intensity of the backscattered
signal. High intensity returns appear as light tones on a positive image, while low signal
returns appear as dark tones on the imagery.
Shape: It can be defined as spatial form with respect to a relative constant contour or
periphery, or more simply the object's outline. Some features (streets, bridges, airports...)
can be distinguished by their shape. It should be noted that the shape is as seen by the
oblique illumination: slant range distance of the radar.
Structure: The spatial arrangement of features throughout a region with recurring
configuration.
Size: The size of an object may be used as a qualitative recognition element on radar
imagery. The size of known features on the imagery provides a relative evaluation of scale
and dimensions of other terrain features.
Texture: Characteristics placements and arrangements of repetition tone or color. E.g.
smooth, intermediate, rough, stippled, mottled etc.
Speckles: A detailed analysis of the radar image shows that even for a single surface type,
important grey level variations may occur between adjacent resolution cells. These
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variations create a grainy texture, characteristic of radar images. This effect, caused by
the coherent radiation used by radar systems, is called speckle. It happens because each
resolution cell associated with an extended target contains several scattering centres
whose elementary returns, by positive or negative interference, originate light or dark
image brightness.
Tone Speckle
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6. DIGITAL IMAGE PROCESSING
6.1: DIGITAL IMAGE PROCESSING CONCEPT
Digital image processing is the application of algorithms of on digital images to perform
processing, analysis and information extraction. The data processing in remote sensing is
dominantly treated as digital image processing.
6.2: CATEGORIZATION OF IMAGE PROCESSING
1. Image pre-processing
2. Image enhancement
3. Image transformation
4. Image classification
6.2.1: Image pre-processing
Preprocessing or image restoration and rectification refers to correcting sensor and platform
specific radiometric and geometric distortion of data.
Geometric correction: Geometric correction includes correcting for geometric
distortions due to sensor earth geometry variations, and conversions of data to real world
ordinance on the earth’s surface.
It may include several factors-
The perspective of the sensors optics
The motion of the scanning system
The platform altitude and velocity
The terrain relief
The curvature and rotation of the earth
Processes are-
Selection of method
Determination of parameters
Accuracy check
Interpolation and resampling
Radiometric Correction: Radiometric corrections include correcting the data for
sensor irregularities and unwanted sensor and atmospheric noise, and converting the data
so they accurately represent the reflected or emitted radiation measured by the sensors.
It is classified into:
a. Detector response calibration
i. De-stripping
ii. Removal of missing scan line
iii. Vignetting removal
iv. Random noise removal
b. Sun angle and topographic correction
c. Atmospheric correction
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Geocoding: A procedure called resampling is used to determine the DN to placein the
new pixel location of the corrected output image. The resultant image is called geo coded
image.
6.2.2: Image enhancement
It can be defined as the conversion of the image quality to a better and more understandable level
for future extraction of image interpretation.
Two major types of enhancements are-
a. Contrast stretching: to increase the tonal distinction between various features in a scene.
b. Spatial filtering: to enhance specific spatial patterns of an image.
Contrast enhancement is the changing the original values to increase the contrast between targets
and their backgrounds.
Procedure of image enhancement:
1. Image reduction
2. Image magnification
3. Color compositing
4. Transect extraction
5. Contrast enhancement
6.2.3: Image transformation
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Image transformations typically involve the manipulation of multiple bands of data, whether from
a single multispectral image or from two or more images of the same area acquired at different
times (i.e. multitemporal image data). Either way, image transformations generate "new" images
from two or more sources which highlight particular features or properties of interest, better
than the original input images.
It includes-
Intensity, hue, saturation (HIS) images
Spectral/band rationing
Principal component analysis
Synergistic images
Non image data sets
Important transformations:
Image arithmetic operation
PCT (principal component transformation)
Tasseled cap transformation (TCT)
Fourier transformation
Image fusion
6.2.4: Image classification
Image classification is the process of assigning land cover classes to pixels. For example, these 9
global land cover data sets classify images into forest, urban, agriculture and other classes.
In general, these are three main image classification techniques in remote sensing:
Unsupervised image classification
Supervised image classification
Object-based image analysis
Knowledge based Image Analysis
Unsupervised classification: The process of segmenting an image into spectral class based on
natural grouping found in the data. It first groups pixels into “clusters” based on their properties.
In order to create “clusters”, analysts use image clustering algorithms such as K-means and
ISODATA. For the most part, they can use this list of free remote sensing software to create
land cover maps.
Supervised classification: The process of using sample of known identify to classify pixels of
unknown identity. Users select representative samples for each land cover class. The software
then uses these “training sites” and applies them to the entire image. Supervised classification
uses the spectral signature defined in the training set. For example, it determines each class on
what it resembles most in the training set. The common supervised classification algorithms are
maximum likelihood and minimum-distance classification.
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Unsupervised Supervised
Object-based Classification: Supervised and unsupervised classification is pixel-based. In other
words, it creates square pixels and each pixel has a class. But object-based image classification
groups pixels into representative shapes and sizes. This process is multi-resolution segmentation
or segment mean shift
Supervised-unsupervised classification timeline
Supervised vs. Unsupervised:
Supervised:
In Supervised Classification, the analyst identifies the classes by image
interpretation techniques and collects signatures for making feature classes.
Prior decision
Information classes to spectral classes
Unsupervised:
The software tool itself classifies the image into specified number of classes by
grouping nearly matching pixel values for making feature classes.
Posterior decision
Spectral classes to information classes.
6.3: ADVANTAGES OF DIGITAL IMAGE INTERPRETATION
Cost-effective for large geographic areas
Cost-effective for repetitive interpretations
Cost-effective for standard image formats
Consistent results
Simultaneous interpretations of several channels
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Complex interpretation algorithms possible
Speed may be an advantage
Explore alternatives
6.4: DISADVANTAGE OF DIGITAL IMAGE INTERPRETATION
Expensive for small areas
Expensive for one-time interpretations
Start-up costs may be high
Requires elaborate, single-purpose equipment
Accuracy may be difficult to evaluate
Requires standard image formats
Data may be expensive, or not available
Preprocessing may be required
May require large support staff
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7. AERIAL PHOTOGRAPHY
7.1: NATURE OF ARERIAL PHOTOGRAPHY
An aerial photograph, in broad terms, is any photograph taken from the air. Normally, air
photos are taken vertically from an aircraft using a highly-accurate camera. There are several
things you can look for to determine what makes one photograph different from another of the
same area including type of film, scale, and overlap. Other important concepts used in aerial
photography are stereoscopic coverage, fiducial marks, focal length, roll and frame numbers, and
flight lines and index maps.
7.1.1: Basic concepts of aerial photography:
Film: most air photo missions are flown using black and white film, however colour, infrared,
and false-colour infrared film are sometimes used for special projects.
Focal length: the distance from the middle of the camera lens to the focal plane (i.e. the film).
As focal length increases, image distortion decreases. The focal length is precisely measured when
the camera is calibrated.
Scale: the ratio of the distance between two points on a photo to the actual distance between
the same two points on the ground (i.e. 1 unit on the photo equals "x" units on the ground).
Large Scale - Larger-scale photos (e.g. 1:25 000) cover small areas in greater detail. A
large scale photo simply means that ground features are at a larger, more detailed size.
The area of ground coverage that is seen on the photo is less than at smaller scales.
Small Scale - Smaller-scale photos (e.g. 1:50 000) cover large areas in less detail. A small
scale photo simply means that ground features are at a smaller, less detailed size. The area
of ground coverage that is seen on the photo is greater than at larger scales.
Fiducial marks: small registration marks exposed on the edges of a photograph. The distances
between fiducial marks are precisely measured when a camera is calibrated, and this information
is used by cartographers when compiling a topographic map.
Overlap: is the amount by which one photograph includes the area covered by another
photograph, and is expressed as a percentage. The photo survey is designed to acquire 60%
forward overlap (between photos along the same flight line) and 30% lateral overlap (between
photos on adjacent flight lines).
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Stereoscopic Coverage: the three-dimensional view which results when two overlapping
photos (called a stereo pair), are viewed using a stereoscope. Each photograph of the stereo pair
provides a slightly different view of the same area, which the brain combines and interprets as a
3-D view.
Roll and Photo Numbers: each aerial photo is assigned a unique index number according to
the photo's roll and frame. For example, photo A23822-35 is the 35th annotated photo on roll
A23822. This identifying number allows you to find the photo in NAPL's archive, along with
metadata information such as the date it was taken, the plane's altitude (above sea level), the focal
length of the camera, and the weather conditions.
Flight Lines and Index Maps: at the end of a photo mission, the aerial survey contractor plots
the location of the first, last, and every fifth photo centre, along with its roll and frame number,
on a National Topographic System (NTS) map. Photo centres are represented by small circles,
and straight lines are drawn connecting the circles to show photos on the same flight line.
7.2: TYPES OF AERIAL PHOTOGRAPHY
a. Vertical
b. Low oblique
c. High oblique
d. Trimetrogon
e. Multiple Lens Photography
f. Convergent Photography
g. Panoramic
a. Vertical. A vertical photograph is taken with the camera pointed as straight down as possible.
Allowable tolerance is usually + 3° from the perpendicular (plumb) line to the camera axis. The
result is coincident with the camera axis. A vertical photograph has the following characteristics:
1. The lens axis is perpendicular to the surface of the earth.
2. It covers a relatively small area.
3. The shape of the ground area covered on a single vertical photo closely
approximates a square or rectangle.
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4. Being a view from above, it gives an unfamiliar view of the ground.
5. Distance and directions may approach the accuracy of maps if taken over flat
terrain.
6. Relief is not readily apparent.
Relationship of the vertical aerial photograph with the ground.
Vertical photograph.
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b. Low Oblique. This is a photograph taken with the camera inclined about 30° from the
vertical. It is used to study an area before an attack, to substitute for a reconnaissance, to
substitute for a map, or to supplement a map. A low oblique has the following characteristics:
1. It covers a relatively small area.
2. The ground area covered is a trapezoid, although the photo is square or
rectangular.
3. The objects have a more familiar view, comparable to viewing from the top of a
high hill or tall building.
4. No scale is applicable to the entire photograph, and distance cannot be measured.
Parallel lines on the ground are not parallel on this photograph; therefore,
direction (azimuth) cannot be measured.
5. Relief is discernible but distorted.
6. It does not show the horizon.
Relationship of low oblique photograph to the ground.
Low oblique photograph.
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c. High Oblique. The high oblique is a photograph taken with the camera inclined about 60°
from the vertical. It has a limited military application; it is used primarily in the making of
aeronautical charts. However, it may be the only photography available. A high oblique has the
following characteristics:
1. It covers a very large area (not all usable).
2. The ground area covered is a trapezoid, but the photograph is square or
rectangular.
3. The view varies from the very familiar to unfamiliar, depending on the height at
which the photograph is taken.
4. Distances and directions are not measured on this photograph for the same
reasons that they are not measured on the low oblique.
5. Relief may be quite discernible but distorted as in any oblique view. The relief is
not apparent in a high altitude, high oblique.
6. The horizon is always visible.
Relationship of high oblique photograph to the ground.
High oblique photograph.
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d. Trimetrogon. This is an assemblage of three photographs taken at the same time, one
vertical and two high obliques, in a direction at right angle to the line of flight. The obliques, taken
at an angle of 60° from the vertical, sidelap the vertical photography, producing composites from
horizon to horizon.
Relationship of cameras to ground for trimetrogon photography (three cameras).
e. Multiple Lens Photography. These are composite photographs taken with one camera
having two or more lenses, or by two or more cameras. The photographs are combinations of
two, four, or eight obliques around a vertical. The obliques are rectified to permit assembly as
verticals on a common plane.
f. Convergent Photography. These are done with a single twin-lens, wide-angle camera, or
with two single-lens, wide-angle cameras coupled rigidly in the same mount so that each camera
axis converges when intentionally tilted a prescribed amount (usually 15 or 20°) from the vertical.
Again, the cameras are exposed at the same time. For precision mapping, the optical axes of the
cameras are parallel to the line of flight, and for reconnaissance photography, the camera axes
are at high angles to the line of flight.
g. Panoramic. The development and increasing use of panoramic photography in aerial
reconnaissance has resulted from the need to cover in greater detail more and more areas of the
world.
1. To cover the large areas involved, and to resolve the desired ground detail, present-
day reconnaissance systems must operate at extremely high-resolution levels.
Unfortunately, high-resolution levels and wide-angular coverage are basically
contradicting requirements.
2. A panoramic camera is a scanning type of camera that sweeps the terrain of interest
from side to side across the direction of flight. This permits the panoramic camera
to record a much wider area of ground than either frame or strip cameras. As in
the case of the frame cameras, continuous cover is obtained by properly spaced
exposures timed to give sufficient overlap between frames. Panoramic cameras are
most advantageous for applications requiring the resolution of small ground detail
from high altitudes.
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Other Types:
Kite Aerial Photography
Balloon Aerial Photography
Helicopter Aerial Photography
Radio controlled Aerial Photography
7.3: IMPORTANCE OF AERIAL PHOTOGRAPHY
1. Photograph and map relation to operation (from photo to map)
2. Utilization of photographic production and capabilities
3. Utilization by ground forces (forms/physical features, long range uses, tactical uses, photo
interpreter terms)
4. Utilization by air force
5. Utilization by naval force
7.4: APPLICATION OF AERIAL PHOTOGRAPHY
1. Defense
2. Area survey
3. Urban planning
4. Transportation of road network
5. Forest conservation
6. Resource management
7. Tourism
8. Water resource management
9. Weather and climate
10. Other (topographic map, shape of land and mass, features of historical and archeological site,
environmental studies, civilian and military surveillance, recreational purpose, artistic projects,
property surveys and analysis)
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8. APPLICATION OF REMOTE SENSING
8.1: LAND COVER AND LAND USE STUDY ON AGRICULTURE
Crop production forecasting
Assessment of crop damage and crop progress
Horticulture, Cropping Systems Analysis
Crop Identification
Crop acreage estimation
Crop condition assessment and stress detection
Identification of planting and harvesting dates
Crop yield modelling and estimation
Identification of pests and disease infestation
Soil moisture estimation
Irrigation monitoring and management
Soil mapping
Monitoring of droughts
Land cover and land degradation mapping
Identification of problematic soils
Crop nutrient deficiency detection
Reflectance modeling
Determination of water content of field crops
Crop yield forecasting
Flood mapping and monitoring
Collection of past and current weather data
Crop intensification
Water resources mapping
Precision farming
Climate change monitoring
Compliance monitoring
Soil management practices
Air moisture estimation
Crop health analysis
Land mapping
8.2: FOREST
Forest cover monitoring/ surveillance
Forest type mapping and assessment of distribution
Forest stock mapping and preparation of working plan inputs
Forest inventory and sampling
The forest volume estimation
Stock tables preparation and yield calculation
Ecological consideration and zonation of forests
Remote sensing and biodiversity studies
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Forestry conversion studies
Forest fire damage
GIS applications in forestry
8.3: GEOMORPHOLOGY
Remote sensing and Geomorphology are two disciplines of science, where geomorphology is the
science of study of landforms of the earth. It is concerned with pattern of landform, materials and
their related processes. Geomorphology as a science deals with evolutionary processes of relief
forms of the earth and lead us to understand various processes of evolution of landforms. Remote
sensing is the science of acquiring information about an object or phenomena close to the earth’s
surface by measuring electromagnetic radiation. Remote sensing is an effective tool that enables
understanding of aerial and satellite images containing integrated information’s of the features on
the ground such as landform, ecology, available resources and impact of human interference on
the natural landscape. Land use and land cover change (LULC) is one of the focal themes in
geomorphic study. It has great significance in analysis of changing nature of land use practices,
causes of increasing intensity of resource use and changing relationship between Man’s activities
with nature.
8.4: HYDROLOGY
Remote sensing has the capability of observing several variables of hydrological interest over large
areas on a repetitive basis. These variables include surface soil moisture, surface temperature,
albedo/land cover, snow water equivalent and snow cover area. With the possible exception of
the last item there has not been extensive use of remotely sensed data in hydrological models.
Nevertheless, remotely sensed data are essential for global and continental applications for which
useful estimates of hydrologic parameters can be made.
8.5: OCEANS AND COASTAL MONITORING
Ocean pattern identification:
o currents, regional circulation patterns, shears
o frontal zones, internal waves, gravity waves, eddies, upwelling zones, shallow water
bathymetry ,
Storm forecasting
o wind and wave retrieval
Fish stock and marine mammal assessment
o water temperature monitoring
o water quality
o ocean productivity, phytoplankton concentration and drift
o aquaculture inventory and monitoring
Oil spill
o mapping and predicting oil spill extent and drift
o strategic support for oil spill emergency response decisions
o identification of natural oil seepage areas for exploration
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Shipping
o navigation routing
o traffic density studies
o operational fisheries surveillance
o near-shore bathymetry mapping
Intertidal zone
o tidal and storm effects
o delineation of the land /water interface
o mapping shoreline features / beach dynamics
o coastal vegetation mapping
o human activity / impact
8.6: MONITORING OF ATMOSPHERIC CONSTITUENTS
Weather Radar
Cloud Radar
Wind Profiling Radar
HF/MF Radar
Meteor Radar
Air pollution
Assess atmospheric components, gases, aerosols and clouds
8.7: SOIL PROPERTIES
Soil map is a geographical representation showing diversity of soil types and/or soil properties in
the area of interest. It is typically the end result of a soil survey. Soil maps are most commonly
used for land evaluation, spatial planning, agricultural extension, environmental protection and
similar projects. Soil survey is the process of determining the pattern of the soil cover,
characterizing it and presenting it in understandable and interpretable form to various
users. The advancement of remote sensing technology is a boon for conducting efficient soil
surveys and mapping soil efficiently. Recent technological advances in satellite remote sensing
have helped to overcome the limitation of conventional soil survey, thus providing a new outlook
for soil survey and mapping. There is a progress of remote sensing in mapping of various soil
properties like moisture, salinity, mineralogy, vegetation, etc. using methods like optical
remote sensing, thermal infrared remote sensing, visual image interpretation, microwave remote
sensing, hyper spectral remote sensing.
8.8: DISASTER EMERGENCY RESPONSE
Geographic information system (GIS) and remote sensing (RS) are very useful and effective tools
in disaster management. Various disasters like earthquakes, landslides, floods, fires, tsunamis,
volcanic eruptions and cyclones are natural hazards that kill lots of people and destroy property
and infrastructures every year. Landslides are the most regular geological vulnerabilities in
mountain regions, particularly in Sikkim Himalaya. Remotely sensed data can be used very
efficiently to assess severity and impact of damage due to these disasters. In the disaster relief
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phase, GIS, grouped with global positioning system (GPS) is extremely useful in search and rescue
operations in areas that have been devastated and where it is difficult to find one’s bearings.
Disaster mapping is the drawing of areas that have been through excessive natural or man-made
troubles to the normal environment where there is a loss of life, property and national
infrastructures.
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APPENDIXES
ADVANTAGE AND DISADVANTAGE OF SENSOR
It mainly refers to the advantages and disadvantages of remote sensing. Plus active sensor may be
not very sustainable and passive sensor has to rely on sun; these two are disadvantages as well.
RESOLUTION
Resolution is the number of pixels (individual points of color) contained on a display monitor,
expressed in terms of the number of pixels on the horizontal axis and the number on the vertical
axis. The sharpness of the image on a display depends on the resolution and the size of the
monitor.
See 4.2 for classification.
DIFFERENCE BETWEEN IMAGE AND PHOTO
Photographs are taken in the visible portion (0.3 mm to 0.9 mm) of the electromagnetic
spectrum (EMS) and are chemically registered on papers. A photograph refers specifically
to images that have been detected as well as recorded on photographic film.
Images are taken based on the sensors, sensors measure the data based on certain
segments on the EMS which are digitally recorded and user convert it to the color image.
Aerial Photography: Aerial photography is the production of photographic images
from balloons, helicopters or airplanes; it's used primarily for mapping. In 1855, French
balloonist Gaspar Felix Tournachon patented the first aerial photography process, though
it took three years to produce the first image. Early experiments included using pigeons
equipped with automatic cameras and using biplanes in World War I to capture images
of enemy trenches. Aerial photography was successfully commercialized by Sherman
Fairchild for aerial surveys of land and cities after World War I and has been used in
government and civil applications ever since.
Satellite Imagery: The term "satellite imagery" may refer to a number of types of
digitally transmitted images taken by artificial satellites orbiting the Earth. The United
States launched the first satellite imaging system in 1960 to spy on the Soviet Union. Since
then, in addition to military applications, satellite imagery has been used for mapping,
environmental monitoring, archaeological surveys and weather prediction. Governments,
large corporations and educational institutions make the most use of these images.
Advantages of Satellite Imagery: Satellite imagery has a number of advantages. It can
be used to track weather systems, especially dangerous storms like hurricanes, with great
accuracy. Satellites circle the Earth, so their imaging activity can be repeated easily. It also
allows for much greater areas of coverage and, because all information is digital, it can be
easily integrated with software. In some cases, cloud cover does not affect results.
Advantages of Aerial Photography: Aerial photography is still a better choice for
most business and personal commercial uses than satellite imagery. Aerial photography
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costs less and, in some cases, it's more up-to-date, as many available satellite maps are
more than a year old and don't necessarily reflect recent changes or developments.
Individuals and small companies can more easily hire an aerial photographer and have
more input in the process. Resolution and clarity is likely to be higher as well, making
images easier to understand and often eliminating the need for special analysis.
LANDSAT TM
A thematic map is a map that emphasizes a particular theme or special topic such as the average
distribution of rainfall in an area. They are different from general reference maps because they
do not just show natural features like rivers, cities, political subdivisions and highways.
A Thematic Mapper (TM) is one of the Earth observing sensors introduced in the Landsat
program. The first was placed aboard Landsat 4 (decommissioned in 2001), and another was
operational aboard Landsat 5 up to 2012.
TM sensors feature seven bands of image data (three in visible wavelengths, four in infrared) most
of which have 30 meter spatial resolution. TM is a whisk broom scanner which takes multi-
spectral images across its ground track. It does not directly produce a thematic map.
The Thematic Mapper has become a useful tool in the study of albedo and its relationship to
global warming and climate change. The TM on the Landsat 5 has proven useful in determining
the amount of ice loss on glaciers due to melting.
Landsat 7 carries an enhanced TM sensor known as the Enhanced Thematic Mapper Plus (ETM+).
LANDSAT ETM/ETM+
Landsat Thematic Mapper (TM) is a multispectral scanning radiometer that was carried on
board Landsats 4 and 5. The TM sensors have provided nearly continuous coverage from July
1982 to present.
The Landsat Enhanced Thematic Mapper (ETM) was introduced with Landsat 7. ETM data
cover the visible, near-infrared, shortwave, and thermal infrared spectral bands of the
electromagnetic spectrum. The Landsat Project is a joint initiative of the U.S. Geological Survey
(USGS) and the National Aeronautics and Space Administration (NASA). Landsat's Global Survey
Mission is to establish and execute a data acquisition strategy that ensures repetitive acquisition
of observations over the Earth's land mass, coastal boundaries, and coral reefs.
The Enhanced Thematic Mapper Plus (ETM+) instrument is a fixed “whisk-broom”, eight-band,
multispectral scanning radiometer capable of providing high-resolution imaging information of the
Earth’s surface. It detects spectrally-filtered radiation in VNIR, SWIR, LWIR and panchromatic
bands from the sun-lit Earth in a 183 km wide swath when orbiting at an altitude of 705 km.
The primary new features on Landsat 7 are a panchromatic band with 15 m spatial resolution, an
on-board full aperture solar calibrator, 5% absolute radiometric calibration and a thermal IR
channel with a four-fold improvement in spatial resolution over TM.
DN
Digital number in remote sensing systems, a variable assigned to a pixel, usually in the form of a
binary integer in the range of 0–255 (i.e. a byte). The range of energies examined in a remote
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sensing system is broken into 256 bins. A single pixel may have several digital number variables
corresponding to different bands recorded.
The Remote Sensing world calls cell values are also called a digital number or DN.
In most of the imagery we work with the DN represents the strength of the signal (amount of
light) that is assigned to each grid cell (pixel).
Low or None - Lowest DN (0 is at bottom of scale)
High - Maximum value (depends on radiometric resolution)
Others - Scaled in between (number of possible increments depends on radiometric
resolution)
MPL
Micro Pulse Lidar (MPL) is a powerful, sophisticated, yet compact and affordable, laser remote
sensing system that provides continuous, unattended monitoring of the profiles and optical
properties of clouds and aerosols in the atmosphere.
KHZ
Unit of frequency, Kilo Hertz.
IFOV
IFOV (Instantaneous Field of View) Definition. A measure of the spatial resolution of a remote
sensing imaging system. Defined as the angle subtended by a single detector element on the axis
of the optical system. IFOV has the following attributes:
Solid angle through which a detector is sensitive to radiation.
The IFOV and the distance from the target determines the spatial resolution. A low
altitude imaging instrument will have a higher spatial resolution than a higher altitude
instrument with the same IFOV.
The field of view is the extent of the observable world that is seen at any given moment. In the
case of optical instruments or sensors it is a solid angle through which a detector is sensitive to
electromagnetic radiation.
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NIR
Near-infrared spectroscopy (NIRS) is a spectroscopic method that uses the near-infrared region
of the electromagnetic spectrum (from 780 nm to 2500 nm). Typical applications include medical
and physiological diagnostics and research including blood sugar, pulse oximetry, functional
neuroimaging, sports medicine, elite sports training, ergonomics, rehabilitation, neonatal
research, brain computer interface, urology (bladder contraction), and neurology (neurovascular
coupling). There are also applications in other areas as well such as pharmaceutical, food and
agrochemical quality control, atmospheric chemistry, combustion research and astronomy.
Uses are-
Astronomical spectroscopy
Agriculture
Remote monitoring
Materials Science
Medical uses
Particle measurement
Industrial uses
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Near-IR absorption spectrum of dichloromethane showing complicated overlapping overtones of mid IR
absorption features.
MICROWAVE REMOTE SENSING
Microwave sensing encompasses both active and passive forms of remote sensing. As described
in Chapter 2, the microwave portion of the spectrum covers the range from approximately 1cm
to 1m in wavelength. Because of their long wavelengths, compared to the visible and infrared,
microwaves have special properties that are important for remote sensing. Longer wavelength
microwave radiation can penetrate through cloud cover, haze, dust, and all but the
heaviest rainfall as the longer wavelengths are not susceptible to atmospheric scattering which
affects shorter optical wavelengths. This property allows detection of microwave energy under
almost all weather and environmental conditions so that data can be collected at any time.
Passive microwave sensing is similar in concept to thermal remote sensing. All objects emit
microwave energy of some magnitude, but the amounts are generally very small. A passive
microwave sensor detects the naturally emitted microwave energy within its field of view. This
emitted energy is related to the temperature and moisture properties of the emitting object or
surface. Passive microwave sensors are typically radiometers or scanners and operate in much
the same manner as systems discussed previously except that an antenna is used to detect and
record the microwave energy.
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The microwave energy recorded by a passive sensor can be emitted by the atmosphere (1),
reflected from the surface (2), emitted from the surface (3), or transmitted from the subsurface
(4). Because the wavelengths are so long, the energy available is quite small compared to optical
wavelengths. Thus, the fields of view must be large to detect enough energy to record a signal.
Most passive microwave sensors are therefore characterized by low spatial resolution.
Applications of passive microwave remote sensing include meteorology, hydrology, and
oceanography. By looking "at", or "through" the atmosphere, depending on the wavelength,
meteorologists can use passive microwaves to measure atmospheric profiles and to determine
water and ozone content in the atmosphere. Hydrologists use passive microwaves to measure
soil moisture since microwave emission is influenced by moisture content. Oceanographic
applications include mapping sea ice, currents, and surface winds as well as detection of pollutants,
such as oil slicks.
Active microwave sensors provide their own source of microwave radiation to illuminate the
target. Active microwave sensors are generally divided into two distinct categories: imaging
and non-imaging. The most common form of imaging active microwave sensors is
RADAR. RADAR is an acronym for RAdio Detection And Ranging, which essentially
characterizes the function and operation of a radar sensor. The sensor transmits a microwave
(radio) signal towards the target and detects the backscattered portion of the signal. The strength
of the backscattered signal is measured to discriminate between different targets and the time
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delay between the transmitted and reflected signals determines the distance (or range) to the
target.
Non-imaging microwave sensors include altimeters and scatterometers. In most cases these
are profiling devices which take measurements in one linear dimension, as opposed to the two-
dimensional representation of imaging sensors. Radar altimeters transmit short microwave pulses
and measure the round trip time delay to targets to determine their distance from the sensor.
Generally altimeters look straight down at nadir below the platform and thus measure height or
elevation (if the altitude of the platform is accurately known). Radar altimetry is used on aircraft
for altitude determination and on aircraft and satellites for topographic mapping and sea surface
height estimation. Scatterometers are also generally non-imaging sensors and are used to make
precise quantitative measurements of the amount of energy backscattered from targets. The
amount of energy backscattered is dependent on the surface properties (roughness) and the angle
at which the microwave energy strikes the target. Scatterometry measurements over ocean
surfaces can be used to estimate wind speeds based on the sea surface roughness. Ground-based
scatterometers are used extensively to accurately measure the backscatter from various targets
in order to characterize different materials and surface types. This is analogous to the concept of
spectral reflectance curves in the optical spectrum.
For the remainder of this chapter we focus solely on imaging radars. As with passive microwave
sensing, a major advantage of radar is the capability of the radiation to penetrate through cloud
cover and most weather conditions. Because radar is an active sensor, it can also be used to
image the surface at any time, day or night. These are the two primary advantages of radar: all-
weather and day or night imaging. It is also important to understand that, because of the
fundamentally different way in which an active radar operates compared to the passive sensors
we described in Chapter 2, a radar image is quite different from and has special properties unlike
images acquired in the visible and infrared portions of the spectrum. Because of these differences,
radar and optical data can be complementary to one another as they offer different perspectives
of the Earth's surface providing different information content. We will examine some of these
fundamental properties and differences in more detail in the following sections.
Before we delve into the peculiarities of radar, let's first look briefly at the origins and history of
imaging radar, with particular emphasis on the Canadian experience in radar remote sensing. The
first demonstration of the transmission of radio microwaves and reflection from various objects
was achieved by Hertz in 1886. Shortly after the turn of the century, the first rudimentary radar
was developed for ship detection. In the 1920s and 1930s, experimental ground-based pulsed
radars were developed for detecting objects at a distance. The first imaging radars used during
World War II had rotating sweep displays which were used for detection and positioning of
aircrafts and ships. After World War II, side-looking airborne radar (SLAR) was developed for
military terrain reconnaissance and surveillance where a strip of the ground parallel to and offset
to the side of the aircraft was imaged during flight. In the 1950s, advances in SLAR and the
development of higher resolution synthetic aperture radar (SAR) were developed for military
purposes. In the 1960s these radars were declassified and began to be used for civilian mapping
applications. Since this time the development of several airborne and spaceborne radar systems
for mapping and monitoring applications use has flourished.
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Canada initially became involved in radar remote sensing in the mid-1970s. It was recognized that
radar may be particularly well-suited for surveillance of our vast northern expanse, which is often
cloud-covered and shrouded in darkness during the Arctic winter, as well as for monitoring and
mapping our natural resources. Canada's SURSAT (Surveillance Satellite) project from 1977 to
1979 led to our participation in the (U.S.) SEASAT radar satellite, the first operational civilian
radar satellite. The Convair-580 airborne radar program, carried out by the Canada Centre for
Remote Sensing following the SURSAT program, in conjunction with radar research programs of
other agencies such as NASA and the European Space Agency (ESA), led to the conclusion that
spaceborne remote sensing was feasible. In 1987, the Radar Data Development Program (RDDP),
was initiated by the Canadian government with the objective of "operationalizing the use of radar
data by Canadians". Over the 1980s and early 1990s, several research and commercial airborne
radar systems have collected vast amounts of imagery throughout the world demonstrating the
utility of radar data for a variety of applications. With the launch of ESA's ERS-1 in 1991,
spaceborne radar research intensified, and was followed by the major launches of Japan's J-ERS
satellite in 1992, ERS-2 in 1995, and Canada's advanced RADARSAT satellite, also in 1995.
LIDAR
LIDAR, which stands for Light Detection and Ranging, is a remote sensing method that uses light
in the form of a pulsed laser to measure ranges (variable distances) to the Earth. These light
pulses—combined with other data recorded by the airborne system— generate precise, three-
dimensional information about the shape of the Earth and its surface characteristics.
A LIDAR instrument principally consists of a laser, a scanner, and a specialized GPS receiver.
Airplanes and helicopters are the most commonly used platforms for acquiring LIDAR data over
broad areas. Two types of LIDAR are topographic and bathymetric. Topographic LIDAR typically
uses a near-infrared laser to map the land, while bathymetric lidar uses water-penetrating green
light to also measure seafloor and riverbed elevations.
LIDAR systems allow scientists and mapping professionals to examine both natural and manmade
environments with accuracy, precision, and flexibility. NOAA scientists are using LIDAR to
produce more accurate shoreline maps, make digital elevation models for use in geographic
information systems, to assist in emergency response operations, and in many other applications.
LIDAR data sets for many coastal areas can be downloaded from the Office for Coastal
Management Digital Coast web portal.