Fundamentals of remote sensing (Webinar)

ARGHYADEEP SAHA
BSc (Hons.) in Geography (2019 - 2022)
ADAMAS UNIVERSITY, KOLKATA, INDIA
INTERN at GRAPHY BY UNACADEMY, INDIA
Fundamentals of
Remote Sensing
Visit - https://arghyadeep.graphy.com/ 1
Webinar will start within 2 minutes.
Take your seats.
Animation Courtesy - NASA

Credit - ISRO
Credit - NASA
INTRODUCTION

BASIC TERMINOLOGY
Image - A visual delineation of entity.
Analog Image
• Produced over Drawing Sheets.
• Produced by Pictographic Detectors.
• Might delineate as Gray Sheds.
Digital Image
• Bring out by Electro-Perceptible.
• Composed of Array of Square
Boxes.

DIGITAL IMAGE
Source – Google Earth
• Composed of pixels.
• Each pixel has an associated values.
• Pixels / Square boxes with high brightness is of
higher number and vice versa.
• Gray level which is a record of variation in
radiant energy in discreate form.
Source – DN values
obtained from C

REMOTE SENSING
Remote sensing is the collection of data about the object and environment without being in direct physical contact with the
object.
Light hits the retina → Photoreceptors turn the Light into Electrical Signals → These electrical signals
travel from the retina through the optic nerve to the brain → Then the brain turns the signals into
the images we see.
This phenomenon will work under the limitation to visible region of Electro Magnetic Spectrum.
0.4 – 0.7 μm

EMR
E LE CT RO MAGNE T I C RADI AT I ON
• Form of energy, transported through space in the form of periodic disturbances
of electric and magnetic fields.
• Travel with the speed of light ; c = 299792458 m/s ≈ 3x108 m/sec.
• Speed of light = frequency x wavelength.
→
E = Electric Field
→
B = Magnetic Field

EMR
Frequency = 1Hz

EMR
Relationship between Wavelength (λ) and Frequency (v) for
Electromagnetic Waves. (JAMES CLERK MAXWELL)
v=c/λ where, c is the speed of light.
Where, h = 6.626 x 10-34 (Planck’s Constant)
Relationship between Energy (E) and Frequency (v) for
Electromagnetic Waves.
E =hv
Considering,
v = c/λ
E = hc/v
Hence, shorter wavelengths have high energy and vice versa.

EMR
ELECTRO MAGNETIC RADIATION
Stephen Boltzmann Law:
This law states that the energy emitted by a blackbody per second is the product of the emissivity of that body, the
Stefan-Boltzmann constant, the surface area of the body and the fourth power of the absolute temperature of that body.
Total Emitted Radiation – σT4
Where, σ = 5.6697 x 10-8 W.m-2 .K-4 (Stephen-Boltzmann constant)
Important –
• ‘0’ → Perfect Reflecting Body.
• ‘1’ → Perfect Blackbody.
• ‘0’ / ‘1’ → Natural Body.

WIEN’S DISPLACEMENT LAW
λmaxT = 2897.9 μmK
T = absolute temperature
The relationship between peak wavelength of emittance
and the temperature of the material.

EMS
E LE CT RO MAGNE T I C SP E CT RUM

Reflection
Visible
VNIR
SWIR
Thermal Infrared
Microwaves
Emission
Back Scattering
EWR
ELECTROMAGNETIC
WAV E LE NG T H RA NG E

ABSORPTION FEATURE
Incident Light Reflected Light
Scattered Light Emitted Energy
Absorb Energy
Transmission
Reason –
• Internal Atomic Structure.
• Materialistic Composition.
Spectral Analysis

ELEMENTS INVOLVED
IN REMOTE SENSING
Irradiance
Scattered
Radiation
R e f l e c t i o n P r o c e s s
Thermal Emission
ATM Emission

TYPES OF REMOTE SENSING
Passive Remote Sensing Active Remote Sensing

TYPES OF ORBITS
Credit - The European Organization for the
Exploitation of Meteorological Satellites.
Polar Orbiting Satellites –
• Inclination between 80° - 100°.
• The satellite passes North-South or vv.
• 14 Orbits/day.
Used –
• Earth’s Explorations.

TYPES OF ORBITS
Credit - Wikipedia.
Geostationary / Geosynchronous Satellites –
• Circular orbit and orbital period is synchronized with rotation period of earth.
• Repeating ground track – fixed paths
Sun-synchronous –
• Satellite passes over the same part of the Earth at roughly the same local
time each day .
• Two fixed times: day and night.
Used –
• Weather Monitoring.
• Tele – Communications.
• Broadcasting.
• Defense Purpose.

TYPES OF ORBITS
Low inclination orbits –
• Orbit altitude is 160 km.
• Orbital period is about 87 - 88 minutes.
Used –
• Acquiring Images.
• High Spatial Resolution.
Credit – NASA Earth Observatory.

PLATFORMS
S p a c e B o r n e A i r B o r n e G r o u n d B a s e d
S p a c e S h u t t l e
7
0
0
–
9
0
0
k
m
S a t e l l i t e
1
8
5
–
5
7
5
k
m
A i r c r a f t w i t h S A R
D r o n e w i t h S A R
1
0
–
1
2
k
m
1
0
0
–
1
5
0
m
S p e c t r o r a d i o m e t e r

IMAGE REFERENCING SYSTEM
• Is a referencing system for locating satellite image
scenes.
• Path is the descending orbit of the satellite.
• Row refers to the latitudinal center line of a frame of
imagery.
• The Path number is always given first, followed by the
Row number.
Example –
The notation 129-051, for example, relates to
Path number 129 and Row number 051.

APPLICATIONS OF REMOTE
SENSING IMAGES
Lithological Mapping –
• The lithologically bound epigenetic /syngeneic deposits are formed due to strong preference of host rocks.
Credit – RS Dept. Geological Survey of India (GSI)

SENSING IMAGES
Zone Mapping –
• Hydrothermal alteration is commonly indicated and can be explored through RS.
Credit – RS Dept. Geological Survey of India (GSI)

SENSING IMAGES
Paleochannels Identification –
Credit – Dr. M.G. Thakkar

SENSING IMAGES
Natural Hazard Monitoring –
Credit – NASA

SENSING IMAGES
River Morphology –
NASA recently released these images of the Padma River’s transformation over three decades in Bangladesh. Satellite imagery shows how the river has been
transforming in shape, size, and location from 1988 to 2018.

SENSING IMAGES
Land Use Land Cover Map –
Land use and Land Cover map of Maharashtra, India, during 2013-2014

SENSING IMAGES
Planetary Exploration –
Image Credit: NASA/Goddard Space Flight Center/DLR/ASU
Published: October 5, 2017

CAPABILITY OF REMOTE SENSING
• Secular Images
• Large Spatial Blanket
• Access to inaccessible areas
• Sensitive to wavelength region beyond → 0.4 μm to 0.7 μm
• Space Exploration

CLASSES OF RESOLUTION
Spatial Resolution –
Animation Courtesy – G World
• The earth surface area covered by a pixel of an image is known as spatial resolution.
High Spatial Resolution
Low Spatial Resolution

Temporal Resolution –
• Frequency at which images are recorded / captured in a specific place on the earth.
• The Landsat series of satellites have a repeat period ranging from 16 – 18 days, whereas in the case of IRS, it is 22 days.
Credit – Dr. Ranganath Ramarao Navalgund, Director & Distinguished Scientist, Space Application Centre, ISRO ( 2005-2012 )
Banda Aceh, Indonesia, Before December 2004 Banda Aceh, Indonesia, After December 2004

Spectral Resolution –
• Spectral Resolution is the range of wavelength that satellite imaging system can detect.
• It refers to the width and number of spectral bands.
• Describes the specific wavelength intervals in the EMR that a sensor can record.
Spectral Profile
Value
Wavelength
Low Spectral Resolution

Spectral Resolution –
Spectral Profile
Value
Wavelength
High Spectral Resolution

Three types of Spectral Resolution –
PA N C H R O M AT I C M U LT I S P E C T R A L H Y P E R S P E C T R A L

Why Hyper Spectral Resolution is significant ?

Radiometric Resolution
• Sensitivity of the sensor to the magnitude of the received electromagnetic energy determines the radiometric resolution.
• Finer the radiometric resolution of a sensor, if it is more sensitive in detecting small differences in reflected or emitted
energy.
1 bit 2 bit 4 bit

SENSOR TECHNOLOGY
CLA SSE S O F SE NSO RS FO R G E NE RAT I NG
I MAGE S
Whisk Broom Imaging Sensors: Across-Track

SENSOR TECHNOLOGY
I MAGE S
Push Broom Imaging Sensors: Along-Track

SENSOR TECHNOLOGY
I MAGE S
Push Broom Imaging Sensors: Along-Track (Frame Capture)

THANK YOU !
I F ANY QUE ST I ONS ?
M A I L M E – a rg h ya d e e p . s a h a @ s t u . a d a m a s u n i ve rs i t y. a c . i n ( O f f i c i a l )
rg h d p s a h a @ g m a i l . c o m ( Pe rs o n a l )
Webinar Organized By –
GRAPHY by UN AC ADEMY, I N DI A
Name – Arghyadeep Saha
Ed u cation al Bac kg rou n d – BS c ( Hon s .) in Geog rap hy. ( Pu rsu in g ) .
Ed u cation al In stitu tion – A d amas Un iversity, Kolkata, IN .
Comp lementar y S ubjec ts – Math emati c s ; Econ omic s ; Comp u ter S c ien c e an d
A p p lication s .
Skil ls & endorseme nts – C ( Basic) , C+ + (Advanced) , Remote Sensing and
Geoinformatic s ; Qu antu m GIS ( Profession al) ,S p read sh eets, Doc s, S lid es .
Presently obtain in g skills – MATLA B, R , A RC GIS , P y th on , Goog le Earth E n g in e .
S pecial Appreciations –
Dr. Hrishikesh S amant
( A s s t . P r o f / V i c e P r i n c i p a l , S t . Xa v i e r ' s C o l l a g e , M u m b a i , I n d i a )
Dr. Ranganath Ramarao N avalgund
( F o r m e r ) D i r e c t o r & D i s t i n g u i s h e d S c i e n t i s t , S p a c e A p p l i c a t i o n C e n t r e , I S R O

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