1.
Geoprocessing Sciences
Geoinformatics
•
•
•
•
Remote Sensing
Geographic Information Systems (GIS)
Global Positioning Systems (GPS)
Geodesy (from Greek –
geodaisia,"division of the Earth")
• Surveying
• Automated Cartography
• and many others

2.
Remote Sensing Process

3.
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.
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.
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.
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.
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).
Interpretation and Analysis (F) - the processed image is interpreted, visually and/or digitally
or electronically, to extract information about the target which was illuminated.
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.

4.
Ideal Remote Systems
EM
Energy Source
Sensor
Data Recorder
Required
Information
USER
Requirements
Reflected Energy
1. Uniform Energy Source
2. Non-interfering Atmosphere
Target
Absorbed
Transmitted Energy
3. A Series of Unique energy
interaction at earth surface
4. A super sensor
5. A real time data handling system
6. Multiple data user

5.
Remote Sensing System
In respect to type of Energy Resources, it can be classified by two way;
1. Passive System
It detect the reflected or emitted radiation from natural source (Sun’s
energy)
2. Active System
The sensor emits radiation which is directed towards the target to be
investigated. The radiation reflected from that target is detected and
measured by the sensor. Advantages include the ability to obtain
measurements anytime.

6.
Platforms and Type
Sensor: An instrument that collect and record energy reflected or emitted from a
target or surface. Sensor must reside on board stable platform.
Platform types: 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

7.
Satellite Characteristics
Orbits selection can vary in terms of altitude (their height above the Earth's
surface) and their orientation and rotation relative to the Earth. We consider two
types of orbits: geostationary & near-polar.
geostationary
•high altitudes ( about 36,000 km),
•revolve at speeds which match the
rotation of the Earth,
•West to East orientation
•observe and collect information continuously over
specific areas.
•Weather and communications satellites commonly
have these types of orbits.

8.
Near-polar orbits:
North-south orbit which, in conjunction with the Earth's rotation (west-east), allows
them to cover most of the Earth's surface over a certain period of time.
Inclination of the orbit relative to a line running between the North and South poles.
These satellite orbits are sun-synchronous such that they cover each area of the
world at a constant local time of day called local sun time.
This ensures consistent illumination conditions
when acquiring images in a specific season over
successive years, or over a particular area over a
series of days.
This is an important factor for monitoring changes
between images or for mosaicking adjacent images
together

9.
Swath
The sensor "sees" a certain portion of the Earth's surface. The area imaged on the
surface, is referred to as the swath.
The satellite's orbit and the rotation of the Earth work together to allow complete
coverage of the Earth's surface( cycle of orbits).
In near-polar orbits, areas at high latitudes will be imaged more frequently than the
equatorial zone due to the increasing overlap in adjacent swaths as the orbit paths
come closer together near the poles.

10.
Electromagnetic Radiation (EMR)
According to Wien's Displacement Law
shows how the spectrum of black body radiation at any temperature is
related to the spectrum at any other temperature. If we know the shape of the
spectrum at one temperature, we can calculate the shape at any other
temperature. Spectral intensity can be expressed as a function of wavelength or
of frequency.
peak
T
2.898 106 nm.K

11.
According to James Clark Maxwell, EMR can be considered as
Electromagnetic radiation (EM radiation or EMR) is a form
of energy emitted and absorbed by charged particles, that travels
through space at the speed of light.
It consists of two fluctuating fields
1. Electric Field (E)
2. Magnetic Field (M)
both fields are at right angles with each other and perpendicular
to the direction of propagation

12.
Electromagnetic Radiation of Black-body
(Light Intensity)
Black body radiation has a characteristic, continuous frequency
spectrum that depends only on the body's temperature

13.
Solar Radiation
Gamma Ray: < 0.03nm
X-Ray: 0.03 nm – 3 nm
Ultraviolet: 3 nm -0.4 µm
Visible: 0.4 µm – 0.7 µm
Infrared: 0.7 µm – 0.1 cm
Micro Wave: 0.1 cm – 30 cm
Radio Wave: > 30 cm
Short Waves
Long Waves

14.
Electromagnetic Spectrum
It is the range of all possible
frequencies/wavelength of
electromagnetic radiation.
Longest wavelength: size
of universe
Shortest Wavelength:
vicinity of atomic
distances
Short wave
Long wave
Gamma Ray: < 0.03 nm
X-Ray: 0.03 nm – 3 nm
Ultraviolet: 3 nm -0.4 µm Visible:
0.4 µm – 0.7 µm
Infrared: 0.7 µm -0.1 cm
Micro Wave: 0.1 cm -30 cm
Radio Wave: > 30 cm

15.
Electromagnetic Spectral Regions
REGION
WAVELENGTH
REMARKS
Gamma ray
< 0.03 nm
Incoming radiation is completely absorbed by the upper atmosphere and is not available for
remote sensing
X ray
0.03 nm – 3 nm
Completely absorbed by atmosphere. Not employed in remote sensing.
Ultraviolet
3 nm – 0.4 µm
Incoming wavelengths less than 0.3 µm are completely absorbed by ozone in the upper
atmosphere
Photographic
UV band
0.3 µm – 0.4 µm
Transmitted through atmosphere. Detectable with film and photo-detectors, but atmospheric
scattering is severe
Visible
0.4 µm – 0.7 µm
Imaged with film and photo-detectors. Includes reflected energy peak of earth at 0.5 µm.
Infrared
0.7 µm – 100 µm
Interaction with matter varies with wavelength. Atmospheric transmission windows are
separated by absorption band
Reflected IR
0.7 µm – 3.0 µm
Reflected solar radiation that contain no information about the thermal properties of
materials. The band from 0.7 to 0.9 µm is detectable with film and is called the photographic
IR band.
Thermal IR
3 µm – 15 µm
8 µm – 14 µm
Principal atmospheric windows in the thermal region. Images at these wavelengths are
required by optical-mechanical scanners and special vidicon system but not by film.
Microwave
0.1 cm – 30 cm
Longer wavelengths can penetrate clouds, fog, and rain. Images may be acquired in the active
or passive mode.
Radar
0.1 cm – 30 cm
Active form of microwave remote sensing. Radar images are acquired at various wavelength
bands.
Radio
> 30 cm
Longest wavelength portion of electromagnetic spectrum. Some classified radars with very
long wavelength operate in this region.

16.
Specific bands of wavelengths are only used for remote
sensing purpose

17.
Visible Spectrum
VIOLET :
BLUE:
GREEN:
YELLOW:
ORANGE:
RED:
0.400 - 0.446 µm
0.446 - 0.500 µm
0.500 - 0.578 µm
0.578 - 0.592 µm
0.592 - 0.620 µm
0.620 - 0.700 µm
Spectral Band in remote
sensing
Band 1: Blue band (0.4 – 0.5 µm)
Band 2 : Green band (0.5 – 0.6 µm)
Band 3 : Red band (0.6 – 0.7 µm)

18.
Infrared Spectrum
Near Infrared (NIR) : (0.78 -3 µm)
can be recorded on film.
Mid Infrared (MIR) : (3 µm - 50 µm)
can be detected using electro-optical sensors.
Far Infrared (FIR) : (50 µm -1000 µm) or Thermal IR
can only be detected using electro-optical sensors.

19.
Remote Sensing Electromagnetic Spectrum
Only some part of EM spectrum is useful for Remote Sensing Purpose.
Wavelength of EM energy used by Remote sensor is called as Spectral
Range or Spectral band.
Wavelength Range:
Visible Region:
0.4 µm – 0.7 µm
Infrared Region: 0.7 µm – 1 cm
Microwave Region: 1 cm – 30 cm
Based on Wavelength Region Remote Sensing is three type:
Visible & Reflective IR Remote Sensing
Thermal IR Remote sensing
Microwave Remote Sensing

20.
Energy, Atmosphere, and Surface Interactions

21.
Attenuation of Solar Radiation/ EM Energy
Depends upon:
Causes:
1. Energy Interaction with Atmosphere
a). scattering
b). refraction
c). atmospheric absorption
2. Energy Interaction with Surface / target
a). Reflection
b). Absorption at surface
c). Transmission
a). Differences in path
length
b). Magnitude of the
energy signal that is
being sensed
c). Atmospheric
conditions present
d). The wavelengths
involved.

22.
Energy Interaction with Atmosphere
Scattering :


redirection of light by particles
can be in any direction
(unpredictable)
Scattering of EM radiation by a cloud

23.
General Effects of Scattering




causes skylight (allows us to see in shadow)
forces image to record the brightness of the atmosphere
in addition to the target.
directs reflected light away from the sensor, decreasing
spatial detail (fuzzy images)
tends to make dark objects lighter and light objects
darker (reduces contrast)

24.
Types of scattering
Depending on the relationship between the diameter of the scattering
particle (a) and the wavelength of the radiation (λ), it can be three type;
1. Rayleigh Scattering
2. Mie Scattering
3. Non-selective scattering
Scattering of EM radiation by a cloud

25.
Rayleigh Scattering
( or molecular scattering)
a <<
•
Rayleigh scatter is common when radiation interacts with
atmospheric molecules (gas molecules) and other tiny particles
(aerosols) that are much smaller in diameter that the wavelength
of the interacting radiation. (mainly due to Oxygen and Nitrogen
molecule)
•
Scattering intensity is proportional to λ-4. As a result, short
wavelengths are more likely to be scattered than long
wavelengths.
•
It is common high in the atmosphere
•
Rayleigh scatter is one of the principal causes
of haze in imagery. Visually haze diminishes the
crispness or contrast of an image.
•
It is responsible for blue sky.

26.
Mie Scatter
(mean particle diameter 0.1 to 10 times of
• Mie scatter exists when the atmospheric particle diameter is
essentially equal to the energy wavelengths being sensed.
• Examples: Water vapour, smoke particles, fine dust particles
• Scattering intensity is proportion to
diameter)
-4 to
0
(depending upon particle
• This type of scatter tends to influence longer wavelengths than
Rayleigh scatter.
• Clear atmosphere has both Rayleigh and Mie scattering. Their
combined influence is between -0.7 to -2

27.
Non-selective scatter
a>
• Non-selective scatter is more of a problem, and occurs
when the diameter of the particles causing scatter are
much larger than the wavelengths being sensed.
• Water droplets, that commonly have diameters of
between 5 and 100 m, can cause such scatter, and can
affect all visible and near - to - mid-IR wavelengths
equally.
• Consequently, this scattering is “non-selective” with
respect to wavelength. In the visible wavelengths, equal
quantities of blue green and red light are scattered.

28.
Refraction


bending of light when it passes
through two media
degrades spectral signatures on
hot- humid days

29.
Atmospheric Absorption
Mostly caused by atmospheric contents:

ozone

carbon dioxide

water vapour

Oxygen

Dust Particle

30.
Energy Interaction with Surface / target
Reflection


the bouncing of electromagnetic energy from a surface
type of reflection is dependent on the size of the surface
irregularities relative to the incident wavelength.
Types of Reflection
1.
Specular Reflectance
2.
Diffuse/Lambertian Reflectance

31.
Specular Reflectance

light is reflected in a single direction - 'mirror'
reflection
specular reflectance helps and hinders remote
sensing.
Diffuse/Lambertian Reflectance

 energy is reflected equally in all directions
 many natural surfaces act as a diffuse reflector
to some extent.

32.
ENERGY INTERACTIONS WITH EARTH
SURFACE MATERIALS
EMR incident on any earth surface will interact in three fundanental ways – various fractions of
the energy will be reflected, absorbed and/or transmitted.
EI ( ) = ER ( ) + ET ( ) + EA ( )
Where;
EI = incident energy
ER = reflected energy
EA = absorbed energy
ET = transmi fted energy
( ) = denotes all components are a function of wavelength
ER ( ) = E I( )- [EA ( ) + ET ( )]
Reflection + Transmission + Absorption = 100%

33.
Resolution means the ability and quality of a sensor to view/detect
the objects. In satellite sensor it is four types; spatial, spectral,
Temporal and Radiometric
It is generally believed that improvements in
resolution increases the
probability that phenomena may be remotely
sensed more accurately.
The trade-off is that any improvement in
resolution usually will
require additional data - processing capability
for either human or
computer - assisted analysis.

34.
Temporal Resolution
Revisit of sensor to same area
Temporal Resolution:
how often do we observe?
• Temporal - how often the sensor acquires data, e.g. every 30
days.

35.
Represents the frequency with which a satellite can re-visit an area of interest
and acquire a new image.
Depends on the instrument's field of vision, and the satellite's orbit.
Remote Sensor Data Acquisition
June 1, 2006
June 17, 2006
16 days
July 3, 2006

36.
Radiometric Resolution
D e g re e o f d e t a i l o b s e r v e d ?
Radiometric - the
sensitivity of
detectors to scale
small differences in
electromagnetic
energy.

37.
0
0
7-bit
(0 - 127)
8-bit
(0 - 255)
0
0
9-bit
(0 - 511)
10-bit
(0 - 1023)
Radiometric resolution, or radiometric sensitivity refers to the number of digital levels
used to express the data collected by the sensor. In general, the greater the number of
levels, the greater the detail of information.

38.
Spatial Resolution
1. Spatial Resolution:
• Spatial
m, etc.
what size we can resolve?
- the size of the field-of-view, e.g. 10 x 10 m or 5 x 5
SPATIAL : Smallest unit that can be resolved
•This represents the ability of the sensor to detect and distinguish small objects
and fine detail in larger objects.
• Depends on the instrument's sensitivity and distance from the object, and
defines the pixel size of a digital image.
•
The fineness of detail visible in an image.
– (course) Low resolution – smallest features not discernable
– (fine) High resolution – small objects are discernable
•
Factors affecting spatial resolution
– Atmosphere,
– haze,
– smoke,
– low light,
– particles or blurred sensor systems

39.
Better spatial resolution
resolution = ~200 m
resolution = ~10 m

40.
Spatial
Resolution
Imagery of residential
housing in Mechanicsville,
New York, obtained on June
1, 1998, at a nominal spatial
resolution of
0.3 x 0.3 m (approximately 1
x 1 ft.) using a digital
camera.

41.
30 m
Landsat TM ( 8 bit )
10 m
SPOT PAN ( 8 bit )
5.6 m
IRS 1C PAN ( 6 bit )
1m
IKONOS ( 11 bit )

42.
Spectral Resolution
2. Spectral Resolution: what wavelengths do we use?
 SPECTRAL : Sensitive to specific wavelength intervals
• Spectral - the number and size of spectral regions ,the sensor
records data in, e.g. blue, green, red, near-infrared, thermal infrared,
microwave (radar).

43.
The term spectral
resolution refers to
the width of spectral
bands that a
satellite imaging
system can detect.
Often satellite
imaging systems
are multi-spectral
meaning that they
can detect in
several discrete
bands, it is the
width of these
bands that spectral
resolution refers
too. The narrower
the bands, the
greater the spectral
resolution.

44.
SPECTRAL RESOLUTION
Landsat TM

45.
Spatial Resolution:
the space between my Data Points (per ha.)
80 m = 1.5
30 m = 11
23.5 m = 18
10 m = 100
5 m = 400
1 m = 10000
 Spectral Resolution:
the “Various Colors” of my Data Points
 Radiometric Resolution:
How well I can distinguish my Data Points
 Temporal Resolution:
the number of times that I can see my Data Points
T1
T2
T3
.. .. ..

46.
Spectral Reflectance
Curve
The energy reaching surface is called irradiance and the
energy reflected by the surface is called radiance.
All matter is composed of atoms and molecules with particular
compositions. Therefore matter will reflect wavelength with respect
to the inner state.
A graph of the spectral reflectance of an object as a function
of wavelength is called a spectral curve.
Also known as color readability.

47.
Spectral Reflectance Curve for VEGETATION
Generally, a leaf is built up of layers of structural fibrous organic matter, within which are
pigmented, water filled cells and air spaces. Therefore, vegetation is considered under
following features:
1. Pigmentation (i.e colour)
2. Physiological Structure (i.e leaf structure)
3. Water Content (i.e. moisture)
Each features has an effect on the reflectance, absorbance and transmittance
properties of a green leaf.
Pigment
Chlorophyll a
Chlorophyll b
b Carotene
Xanthophyll
Wavelengths Absorbed
0.43 to 0.66 microns
0.45 to 0.65 microns
blue to green
blue to green
Physiological Structure
•The discontinuities in the refractive indices within a leaf determine its near infrared reflectance.
•These discontinuities occur between membranes and cytoplasm within the upper half of the
leaf, and more importantly between individual cells and air spaces of the spongy mesophyll
within the lower half of the leaf.
Water content: detected in near and middle infrared

48.
Spectral Reflectance Curve for
SOIL
The reflectance of most soil types are similar, with an increase in reflectance with
wavelength. The dominant factors for reflectance are:
1. Moisture content
2. Organic content
3. Soil texture
4. Soil structure
5. Iron oxide content

49.
Spectral Reflectance Curve for
soils at different levels of moisture

50.
Standard Product
Received information
from satellite
+
Correction
Standard Product
After correction, raw data is converted from image coordinates system to
ground coordinate system
These are generated products using the information received from the satellite after applying
following two correction
1. Geometric Correction
2. Radiometric Correction
Causes of Geometric Correction
1. Distortion due to relative motion of satellite w. r. t. earth
2. Distortion due to earth curvature
3. Panoramic distortion arising out of tilt angle
Steps for Correction
1. by establishing a mapping b/w the output space as defined by user.
2. by transforming the input data into this defined output space

51.
Causes of Radiometric Correction
1. Non-uniform response of the detector and detector elements
2. Detector element failure
3. data loss during communication
4. Narrow dynamic range
5. Image to image variation
Steps for Correction
1. Detector normalization
2. Framing of received scene
3. Failed / degraded detector correction
4. Line loss correction

52.
Data reception, transmission and processing

53.
Remote Sensing and Image Interpretation
Photographic / Image interpretation is defined as the act of examining photographic
images for the purpose of identifying objects and judging their significances.
Image interpretation process is a complex task and require several tasks to be
conducted in a well defined routine consisting of the following process:
1. Classification : (determination of presence or absence of objects)
2. Enumeration : (listing and counting of objects which are visible in image)
3. Mensuration : (measurement of objects in terms of length, area, volume,
height)
4. Delineation: (outlining the regions of homogenous objects or areas.
The most important tasks for spatial interpretation is to establish interpretation
keys, i.e. identifying the typical spatial and spectral patterns of known geographical
features.

54.
Elements of Image Interpretation










TONE / COLOUR
PATTERN
TEXTURE
SIZE
SHAPE
SHADOW
LOCATION
ASSOCIATION
SCALE
RESOLUTION
Interpretation Key
 Selective Key
 Elimination Key

55.
Elements of Image Interpretation
Shape - refers to the general outline of objects. Regular geometric shapes are usually indicators
of human presence and use. Some objects can be identified almost solely on the basis of their
shapes: for example - the Pentagon Building, (American) football fields, cloverleaf highway
interchanges
Size - The size of objects must be considered in the context of the scale of a photograph. The
scale will help you determine if an object is a stock pond or Lake Minnetonka.
Tone - Tone refers to the relative brightness or color of elements on a photograph. It is, perhaps,
the most basic of the interpretive elements because without tonal differences none of the other
elements could be discerned.
Texture - The impression of "smoothness" or "roughness" of image features is caused by the
frequency of change of tone in photographs. It is produced by a set of features too small to
identify individually. Grass, cement, and water generally appear "smooth", while a forest
canopy may appear "rough".
Site - refers to topographic or geographic location. This characteristic of photographs is especially
important in identifying vegetation types and landforms. For example, large circular
depressions in the ground are readily identified as sinkholes in central Florida, where the
bedrock consists of limestone.
Association - Some objects are always found in association with other objects. The context of an
object can provide insight into what it is. For instance, a nuclear power plant is not (generally)
going to be found in the midst of single-family housing.
Pattern - (spatial arrangement) -- The patterns formed by objects in a photo can be diagnostic.
Consider the difference between (1) the random pattern formed by an unmanaged area of trees
and (2) the evenly spaced rows formed by an orchard.

56.
Elements of Image Interpretation
Shape
(depends on the object
outline)
Size
(relative to one
an other)
Tone
(brightness-hue,
color)
Site
(location helps
recognition)
Pattern
Association
Shadow
(features that are normally
Texture
found near object)
(smooth or coarse) (helps to determine height)

57.
Identify the following features in the image and explain how you were able to
do so based on the elements of visual interpretation
6
4
5
3
2
1.
2.
3.
4.
5.
6.
race track
river
roads
bridges
residential area
dam
1
1. Race track : its characteristic shape
2. River : contrasting tone and shape
3. Roads : bright tone and linear
feature
4. Bridges : association with river; they
cross it !
5. Residential area : the pattern that they make in conjunction with roads
6. Dam : bright tone with dark river, shape and association with river – where else would a dam be?!

58.
Combined Plus of Band 4, 5,7
MSS Band 4: Blue
(0.4 – 0.5 µm)
standard
false color
composite
(FCC): Final Image
B 3 Image
Red Filter
B 2 Image
Green Filter
B 1 Image
Blue Filter
MSS Band 5: Green
(0.5 – 0.6 µm)
Light Source
Bands plus (4, 5, 6) joined (mosaicked) to make a standard false
color composite using the three Band combinations as shown in
above image:
MSS Band 6: Red
(0.6 – 0.7 µm)

59.
False color composite

60.
True/Natural Color Image
False Color IR Image

61.
Multispectral concept of remote sensing
Format of a Multispectral Image
1
Li nes or
1
rows (i )
2
3
4 18
10
15
17
20
Col umns ( j)
2
3
4
5
15
16
18
17
18
21
22
20
22
20
24
21
23
Brigh tne ss valu e
range
(typical ly 8 bi t)
2
22
25
255
1
3
white
127
Associated
gray-scal e
gray
Ban ds (k )
4
0
X axis
black
Pict ure element (pixel) at location
Line 4, Column 4, in Band 1 has a
Bright ness Value of 24, i.e., BV 4,4,1 = 24 .
68

62.
Remote Sensing Satellite
Till date many numbers of satellites have been launched for the observation of Earth for different purposes
such as weather, meteorological, monitoring satellite since from 1960s.
Worldwide three major land satellite missions have been launched, which are
1. LANDSAT Series by USA
2. SPOT series by France
3. IRS series by India
These satellites are low-altitude satellite having an altitude of less than 1000 km above the Earth’s surface
and sensors having low spatial resolution and spectral resolution of less than 0.1 µm.
High spatial resolution Satellites
The stereo ability of SPOT and IRS –1C/ID PAN data provides a new dimension to cartographic mapping
application up to 1 : 10,000 scale.
The intense research has lead to significant improvement in spatial resolution close to 1 m. Some of
these sensors capable of acquiring such high spatial resolution are:
1. IKONS
2. Quick Bird
3. OrbView
Both types either Low or high spatial resolution satellites use different
combination of spectral band in their sensor. Therefore, on the basis of
spectral band (s) used, we have different types of remote sensors.

63.
Remote sensing data product
National Remote Sensing Centre (NRSC) is the focal point for distribution of remote
sensing satellite data product in India and its neighboring countries.
Station: at Shadnagar (Hyderabad)
Receive the data from almost all contemporary remote sensing satellite such as:
IRS P5
IRS P6
IRS P4
IRS 1D
IRS 1C
IRS P3
ERS 1/2
NOAA series
AQUR , etc
Classification of Product
1. Level of Processing
2. Output media / scale
3. Area of coverage
LGSOWG
(Landsat Ground Station
operators Working Group)
HDH
(Hierarchical Data Format)
1. Standard Products
a)
b)
c)
d)
e)
f)
1. Photographic data
Product
a) B/W
b) FCC
2. Digital Products
a)
b)
c)
d)
e)
Geo TIFF
Fast format
LGSOWG
HDF
CCT
Path/row based
Shift along track
Quadrant product
Geo-referenced Product
Basic streo-pairs
Area of interest based
product
2. Value Added Products
a)
b)
c)
Geo-coded Product
Merged product
Ortho product
3. Derived Product

64.
Types of Remote Sensor
Most common type of sensors used in remote sensing satellites are:
1. Return Beam Vidicon (RBV)
2. Multi Spectral Scanner (MSS)
3. Thematic Mapper (TM)
4. Enhanced Thematic Mapper (ETM)
5. Enhanced Thematic Mapper Plus (ETM+)
Each of these sensors collected data over a swath width of 185 km, with a full scene being defined as
185 km x 185 km. The most popular instrument in the early days of Landsat was the Multi Spectral
Scanner (MSS) and later the Thematic Mapper (TM).
Return Beam Vidicon (RBV)
RBV sensor is essentially a camera – like instruments that took “snapshot’ image of the earth’s surface along the ground
track of the satellite. Image frames of 185 km x 185 km were acquired with each shot, repeated at 25 second intervals to
give contiguous frames in the along track direction at the equivalent ground speed of the satellite.
Multi Spectral Scanner (MSS)
The MSS senses the electromagnetic radiation from the Earth's surface in four spectral bands. Each band has a spatial
resolution of approximately 60 x 80 meters and a radiometric resolution of 64 digital numbers (6 bits). Sensing is
accomplished with a line scanning device using an oscillating mirror. Six scan lines are collected simultaneously with
each west-to-east sweep of the scanning mirror.
Thematic Mapper (TM)
The TM sensor provides several improvements over the MSS sensor including: higher spatial and radiometric resolution;
finer spectral bands; seven as opposed to four spectral bands; and an increase in the number of detectors per band (16 for
the non-thermal channels versus six for MSS). Sixteen scan lines are captured simultaneously for each non-thermal
spectral band (four for thermal band), using an oscillating mirror which scans during both the forward (west-to-east) and
reverse (east-to-west) sweeps of the scanning mirror. All channels are recorded over a range of 256 digital numbers (8 bits).

65.
Types of Sensors, Spectral Band
Sensor
Band
Spectral Range (µm)
1
0.45 - 0.52 (blue)
2
0.52 - 0.60 (green)
3
0.63 - 0.69 (red)
4
0.76 - 0.90 (near IR)
5
1.55 - 1.75 (short wave IR)
6
10.4 - 12.5 (thermal IR)
7
2.08 - 2.35 (short wave IR)
TM
All TM Bands
ETM
ETM+
PAN
0.5 – 0.9
Same as ETM with Thermal Band resolution
of 60 m

66.
Explain why data from the Landsat TM sensor
might be considered more useful than data
from the original MSS sensor.
Think about their spatial, spectral, and
radiometric resolutions and try to explain.
Explanation
There are several reasons why TM data may be considered more useful than MSS data.
1.
Although the area coverage of a TM scene is virtually the same as a MSS scene, TM offers higher
spatial, spectral, and radiometric resolution.
2.
The spatial resolution is 30 m compared to 80 m (except for the TM thermal channels, which are 120 m
to 240 m).
3.
Level of spatial detail detectable in TM data is better. TM has more spectral channels which are
narrower and better placed in the spectrum for certain applications, particularly vegetation
discrimination.
4.
Increase from 6 bits to 8 bits for data recording represents a four-fold increase in the radiometric
resolution of the data. (Remember, 6 bits = 26 = 64, and 8 bits = 28 = 256 - therefore, 256/64 = 4).
However, this does not mean that TM data are "better" than MSS data. Indeed, MSS data are still used to
this day and provide an excellent data source for many applications. If the desired information cannot be
extracted from MSS data, then perhaps the higher spatial, spectral, and radiometric resolution of TM
data may be more useful.

67.
Other sensors
Indian Remote sensing satellites, IRS-P6 consists of three solid state cameras :
1. A medium resolution multispectral sensor - LISS-III
2. A high resolution multispectral sensor - LISS-IV
3. An Advanced Wide Field Sensor – AWiFS
LISS-III camera (Linear Image Self Scanning)
The LISS-III is a multi-spectral camera operating in four spectral bands, three in the visible and
near infra-red and one in SWIR region, as in the case of IRS-1C/1D. The new feature in LISS-III
camera is the SWIR band (1.55 to 1.7 microns), which provides data with a spatial resolution of
23.5 m unlike IRS-1C/1D (the spatial resolution is 70m).
LISS-IV Camera (Linear Image Self Scanning)
The LISS-IV camera is a multispectral high resolution camera with a spatial resolution of 5.8m.
The sensor consists of three linear odd-even pairs of CCD arrays, each with 12000 pixels. The
odd and even pixel rows are separated by 35 microns, which correspond to five scan lines. Also
the placement of the three CCDs in the focal plane is such that their imaging strips on the
ground are separated by 14.25 km in the along-track direction.
AWiFS Sensor
The AWiFS camera provides enhanced capabilities compared to the WiFS camera on-board IRS1C/1D, in terms of spatial resolution (56 m Vs 188m), radiometric resolution (10 bits Vs 7 bits)
and Spectral bands (4 Vs 2) with the additional feature of on-board detector calibration using
LEDs. The spectral bands of AWiFS are same as LISS-III.

68.
Multi-Spectral Scanner (MSS)
MSS Band 4: 0.5- 0.6 µm (Green)
MSS Band 5: 0.6- 0.7 µm (Red)
MSS Band 6: 0.7- 0.8 µm (Photo IR)
MSS Band 7: 0.8- 0.9 µm (Near IR)

69.
Satellite Series

70.
High-Resolution Satellite Systems
IKONOS (1999)
680 km orbit
Revisit is typically 1- 3 days
1 meter panchromatic
4 meter visible color /infrared
Scan width of 13 km

71.
Quickbird
(2000)
61 cm (2
foot)
panchrom
atic
2.44 meter
multi
spectral
Image side
16.5 km
1-3 day
revisit

72.
Geostationary satellites
Geostationary satellites are able to view earth from above.
As they move in synchronicity with earth's rotation, they can
provide regular coverage for a region and help in forecasting.

73.
Polar Orbiting Satellites
Polar orbits allow for lower altitudes and more image resolution.
These satellites take multiple passes of the earth before returning to
the same location.

74.
Satellite Orbits Characteristic
•
Geosynchronous Orbit
(GEO): 36,000 km above
Earth, includes commercial and
military communications
satellites, satellites providing
early warning of ballistic missile
launch.
•
Medium Earth Orbit (MEO):
includes navigation satellites
(GPS, Galileo, Glonass).
•
Low Earth Orbit (LEO): from
80 to 2000 km above
Earth, includes military
intelligence satellites, weather
satellites.

75.
Unit
Completed
…

76.
Assignment
!!!!

77.
Submission date :
1. What are the characteristics of real remote sensing system?
How do they differ from the ideal remote sensing?
2. Explain the general process involved in electromagnetic
remote sensing . Differentiate between active and passive
remote sensing system, under what condition which are
preferable?
3. What are essential difference between a raw, standard and a
geocoded imagery ? Which are most suitable in terms of
geometric quality.
4. Draw a neat diagram of electromagnetic spectrum showing
its various regions of particular interest in remote sensing?
5. Explain multiconcept in remote sensing?
6. Write characteristics of any one satellite with its
sensor, bands , swath , resolution , altitude, and repeativity ?
7. Explain the type of resolution?