Remote sensing involves detecting and measuring electromagnetic energy emanating or reflected from distant objects without physically coming into contact with them. It works by measuring variations in electromagnetic energy distributions from platforms like aircrafts and satellites. An ideal remote sensing system would have a uniform energy source, a non-interfering atmosphere, unique surface interactions, a highly sensitive super sensor, real-time data handling and knowledgeable users. However, real systems have shortcomings like non-uniform energy, atmospheric interference, similar surface signatures, limited sensor capabilities, and need for human data processing. Remote sensing provides large area coverage and monitoring over time at relatively low costs but requires skilled interpretation.
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concepts of RM.ppt
1. (i) Basic Concepts of Remote
Sensing
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
Introduction and Basic Concepts
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2. Objectives
Introduction to remote sensing
Basic concepts
Electromagnetic energy
Remote sensing platforms
Types of remote sensing
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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3. Remote Sensing
The art and science of obtaining information about an object or feature without
physically coming in contact with that object or feature
Remote sensing can be used to measure
– Variations in acoustic wave distributions
– Variations in force distributions (e.g., gravity meter)
– Variations in electromagnetic energy distributions
Remotely collected data through various sensors
may be analyzed to obtain information about the
objects or features under investigation
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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http://geoportal.icimod.org
4. Remote Sensing of Electromagnetic Energy
Variation in electromagnetic energy can be measured using photographic or non-
photographic sensors
Remote sensing of Electromagnetic energy is used for earth observation
“Remote sensing is detecting and measuring electromagnetic energy emanating or
reflected from distant objects made of various materials, so that we can identify and
categorize these objects by class or type, substance and spatial distribution”
[American Society of Photogrammetry, 1975]
Surface parameters are inferred through the measurement and interpretation of the
electromagnetic energy / radiation from the Earth’s surface
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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5. Electromagnetic Energy
Electromagnetic energy or electromagnetic radiation (EMR)
Energy propagated in the form of an advancing interaction between electric and
magnetic fields (Sabbins, 1978)
Travels with the velocity of light
Visible light, ultraviolet rays, infrared, heat, radio waves and x-rays are different forms
Expressed either in terms of frequency (f) or wave length (λ) of radiation
Shorter wavelengths have higher energy content and longer wavelengths have
lower energy content
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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h = Planck's constant (6.626 x 10-34 Joules-sec)
c = Speed of light (3 x 108 m/sec)
f = Frequency expressed in Hertz
λ = wavelength in micro meters (µm)
E = h.c.f or h.c / λ
6. Electromagnetic Energy…
EMR spectrum : Distribution of the continuum of energy plotted as a function of
wavelength (or frequency)
In remote sensing terminology, electromagnetic energy is generally expressed in terms of
wavelength, λ.
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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7. Principles of Remote Sensing
Different objects reflect or emit different amount of energy in different bands of
the electromagnetic spectrum differently
Depends on the properties of
– The target material
– The incident energy (angle of incidence, intensity and wavelength)
Uniqueness of the reflected or emitted electromagnetic radiation is used to detect and
discriminate the objects or surface features
Sensor & Platform in remote sensing
Sensor: A device used to detect the reflected or emitted electromagnetic radiation
– Cameras and scanners
Platform: A vehicle used to carry the sensor
– Aircrafts and satellites
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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8. Stages in Remote Sensing
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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A. Emission of electromagnetic radiation
• The Sun or an EMR source located on the platform
B. Transmission of energy from the source to the object
• Absorption and scattering of the EMR while transmission
C. Interaction of EMR with the object and subsequent reflection and emission
D. Transmission of energy from the object to the sensor
E. Recording of the energy at the sensor
• Photographic or non-photographic
F. Transmission of the recorded information
to ground station
G. Processing of the data into digital or hard
copy image
H. Analysis of data
9. Passive/ Active Remote Sensing
A simple analogy:
Passive remote sensing is similar to taking a picture with an ordinary camera
Active remote sensing is analogous to taking a picture with camera having built-in flash
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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10. Passive Remote Sensing
Passive remote sensing: Source of energy is that naturally available
– Solar energy
– Energy emitted by the Earth etc.
Most of the remote sensing systems work in passive mode using solar energy
– Solar energy reflected by the targets at specific bands are recorded using sensors
– For ample signal strength received at the sensor, wavelengths capable of traversing
through the atmosphere without significant loss, are generally used
The Earth will also emit some radiation since its ambient temperature is about 300o K.
– Passive sensors can also be used to measure the Earth’s radiance
– Not very popular as the energy content is very low
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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11. Active Remote Sensing
Active remote sensing: Energy is generated and emitted from a sensing
platform towards the targets
Energy reflected back by the targets are recorded
Longer wavelength bands are used
Example: Active microwave remote sensing (radar)
– Pulses of microwave signals are sent towards the target from the radar antenna
located on the air / space-borne platform
– The energy reflected back (echoes) are recorded at the sensor
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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12. Remote Sensing Platforms
Ground level remote sensing
Very close to the ground (e.g., Hand held
camera)
Used to develop and calibrate sensors for
different features on the Earth’s surface
Aerial remote sensing
Low altitude aerial remote sensing
High altitude aerial remote sensing
Space-borne remote sensing
Space shuttles
Polar orbiting satellites
Geo-stationary satellites
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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Modified from
http://www.ilmb.gov.bc.ca/risc/pubs/aqu
atic/aerialvideo/assets/figure1.gif
13. Air-borne Remote sensing
Downward or sideward looking sensors mounted on aircrafts are used to obtain images
Very high spatial resolution images (20 cm or less) can be obtained
Drawbacks:
– Less coverage area and high cost per unit area of ground coverage
– Mainly intended for one-time operations, whereas space-borne missions offer
continuous monitoring of the earth features
LiDAR, analog aerial photography, thermal imagery and digital photography are
commonly used in airborne remote sensing
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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14. Space-borne Remote sensing
Sensors are mounted on space shuttles or satellites orbiting the Earth
– Geostationary and Polar orbiting satellites
– Example: Landsat satellites, Indian remote sensing (IRS) satellites, IKONOS, SPOT satellites,
AQUA and TERRA (NASA), and INSAT satellite series
Advantages:
– Large area coverage, less cost per unit area of coverage
– Continuous or frequent coverage of an area of interest
– Automatic/ semi-automatic computerized processing and analysis.
Drawback: Lower resolution
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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15. An Ideal Remote Sensing System
Basic components of an ideal remote sensing system
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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i. A uniform energy source
ii. A non-interfering atmosphere
iii. A series of unique energy/matter interactions at the Earth's surface
iv. A super sensor
iv. A real-time data handling system
v. Multiple data users
16. An Ideal Remote Sensing System…
Basic components of an ideal remote sensing system
i. A uniform energy source : Provides constant, high level of output over all wavelengths
ii. A non-interfering atmosphere: Does not modify the energy transmitted through it
iii. A series of unique energy/matter interactions at the Earth's surface: Generates reflected
/ emitted signals that are
Selective with respect to wavelength and
Unique to each object or earth surface feature type
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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17. An Ideal Remote Sensing System…
Basic components of an ideal remote sensing system…
iv. A super sensor : Simple, accurate, economical and highly sensitive to all wavelengths
Yields data on the absolute brightness (or radiance) from a scene as a function of wavelength.
v. A real-time data handling system: Generates radiance-wavelength response and
processes into an interpretable format in real time
vi. Multiple data users : Possess knowledge in remote sensing techniques and in their
respective disciplines. Use the collected information in their respective disciplines
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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18. A Real Remote Sensing System- Shortcomings
Energy Source
Ideal system: Constant, high level of output over all wavelengths
Real system:
Usually non-uniform over various wavelengths
Energy output vary with time and space
Affects the passive remote sensing systems
– The spectral distribution of reflected sunlight varies both temporally and spatially
– Earth surface features also emit energy in varying degrees of efficiency
A real remote sensing system needs calibration for source characteristics.
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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19. A Real Remote Sensing System…
The Atmosphere
Ideal system: A non-interfering atmosphere
Real system:
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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https://earth.esa.int/
Atmosphere modifies the spectral
distribution and strength of the energy
transmitted through it
The effect of atmospheric interaction varies
with the wavelength associated, sensor
used and the sensing application
Calibration is required to eliminate or
compensate these atmospheric effects
20. A Real Remote Sensing System…
The Energy/Matter Interactions at the Earth's Surface
Ideal system: A series of unique energy/matter interactions
Real system:
Spectral signatures may be similar for different material, making the differentiation difficult
Lack of complete understanding of the energy/matter interactions for surface features
The Sensor
Ideal system: A super sensor
Real system:
Fixed limits of spectral sensitivity i.e., they are not sensitive to all wavelengths.
Limited spatial resolution (efficiency in recording spatial details).
Sensor selection requires a trade-off between spatial resolution and spectral sensitivity.
– For example, photographic systems have very good spatial resolution , but poor spectral sensitivity.
Non-photographic systems have poor spatial resolution.
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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21. A Real Remote Sensing System…
The data handling system
Ideal system: A real-time data handling system
Real system:
Real time data handling almost impossible as human intervention is necessary for processing
sensor data
The multiple data users
Ideal system: Users having knowledge in their domain and in remote sensing techniques
Real system:
Success of a remote sensing mission lies on the user who transforms the data into information
User should have
– Thorough understanding of the problem
– Wide knowledge in the data generation
– Knowledge in data interpretation
– Knowledge to make best use of the data
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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22. Advantages of Remote Sensing
Major advantages of remote sensing are
Provides data for large areas
Provide data of very remote and inaccessible regions
Able to obtain imagery of any area over a continuous period of time
– Possible to monitor any anthropogenic or natural changes in the landscape
Relatively inexpensive when compared to employing a team of surveyors
Easy and rapid collection of data
Rapid production of maps for interpretation
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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23. Limitations of Remote Sensing
Some of the drawbacks of remote sensing are
The interpretation of imagery requires a certain skill level
Needs cross verification with ground (field) survey data
Data from multiple sources may create confusion
Objects can be misclassified or confused
Distortions may occur in an image due to the relative motion of sensor and source
D. Nagesh Kumar, IISc
Remote Sensing: M1L1
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