SlideShare une entreprise Scribd logo
1  sur  76
Satellite Remote Sensing
1. Types of Remote Sensing Based
on Source of Energy Platform
2. Types of Satellite
3. Types of Sensors
4. Limitations of Remote Sensing
5. Basic Components of an Ideal
Remote Sensing System
6. Resolution Definition and types.
Introduction to Remote sensing
RS System capture radiation in different wavelength
reflected/ emitted by the earth’s surface features and
recorded it either directly on the film as in case of aerial
photography or in digital medium letter is used for generating
the images.
R.S. provides valuable data over vast area in a short time
about resources, meteorology and environment leading to
better resource management and accelerating national
development.
The four organizations are engaged in remote sensing
related activities besides several other central and state gov.
and educational institutes:-
1.ISRO
2.SAC
3.NNRMS
4.NRSA
Remote Sensing -
Remote sensing is defined as the science which deals with obtaining
information about objects on earth surface by analysis of data,
received from a remote platform.
Remote sensing can be either passive or active. Active systems have their
own source of energy whereas the passive systems depend upon the solar
illumination or self emission for remote sensing
Principles of Remote Sensing
Detection and discrimination of objects or surface features means detecting and
recording of radiant energy reflected or emitted by objects or surface material. Different
objects return different amount and kind of energy in different bands of the
electromagnetic spectrum, incident upon it. This unique property depends on the
property of material
Stages in Remote Sensing
1. Emission of electromagnetic radiation, or EMR (sun/self-
emission)
2.Transmission of energy from the source to the surface of
the earth, as well as absorption and scattering
3. Interaction of EMR with the earth's surface: reflection and
emission
4. Transmission of energy from the surface to the remote
sensor
5. Sensor data output
6. Data transmission, processing and analysis
Aerial Remote Sensing
Aerial photography is the most commonly used form of remote sensing
and is widely used for topographic mapping, surveys for geological, soil
and forestry mapping, engineering, town planning and environmental
surveys on larger scale.
Remote Sensing Satellites
As is known to us, many countries around the globe now have remote
sensing satellite programs for land resources survey, environmental
impact assessment, weather forecasting and ocean science studies.
METSAT satellite programs for weather monitoring and LANDSAT
satellite program for land resources surveys, both launched by the USA
since 1960 and 1972.
France has also started an ambitious 'SPOT' satellite series
program with the launching of SPOT-1 on 22nd February, 1986.
Japan has launched Marine Observation Satellite (MOS-1) on 19th
Feb. 1987.
RADARSAT is Canada's first remote sensing satellite launched
during 1990.
European Space Agency (ESA) has launched Earth Resources
Satellite (ERS-1) in 1991.
India has launched a number of experimental remote sensing
satellites, Bhaskara-I (June, 1979) and Bhaskara-II (Nov., 1981),
Indian Experimental Satellite
INSAT series of satellite, multipurpose Geostationary satellite
program, has among many sensors,
(i) Very High Resolution Radiometer (VHRR) and (ii) Data Collection
System
Details of IRS Series of Satellites
IRS 1A 1988
1B 1991
1C 1995
1D 1997
P6 2003
cartosat1-2005
cartosat2-2007
Satellite Data Receiving Station
The Govt. of India authorized NRSA to set up a Satellite Receiving
Station to receive digital data from LANDSAT series of Satellites
launched by NASA/USA. This LANDSAT Receiving Station started
functioning since January, 1980 situated at Shadnagar, 55 km. south
of Hyderabad.
Data Acquisition Systems In Remote Sensing two types
1. Image forming ( active sensor system photography)
2. non image forming (passive sensor system satellite
digital mode)
Imaging (Image forming) Image forming systems are again
of two types - framing type and scanning type. In the framing
type, entire frame of image is acquired instantaneously in the
basic image unit e.g. in a frame camera used in photography.
In scanning type, the information is acquired sequentially
from the surface in bits of picture elements or pixels, point by
point and line by line, which may be arranged after acquisition
into a frame format
Non imaging type of sensors, are used to record a
spectral quantity or a parameter as a function of time or
distance ( such as Gamma radiation, magnetic field,
temperature measurement etc.) They are mostly used
for ground observation and in study of atmosphere and
meteorology. These sensors do not form image and as
such, are not used in operational remote sensing but
give detailed information on spectral characteristics of
the target .Such data is collected by sensor system in
satellite and transmitted to earth, where it is received
and recorded at Ground Station.
Characteristics of LISS-3/ LISS-4
LISS-3 Spectral Bands
B2 0.52-0.59 μm
B3 0.62-0.68 μm
B4 0.77-0.86 μm
B5 1.55-1.70 μm
LIV B2 0.52-0.59 μm B3 0.62 - 0.68 B4 0.77 - 0.86
spatial resolution
L3 23.5 m for bands 2,3,4 70.5 m for band 5
L4 5.8 m (at nadir)
Equivalent focal length (bands 2, 3, 4/ band 5) 347.5
mm/301.2 mm
Swath 141 km for bands 2,3,4 148 km for band 5 23.9 km
MS mode 70 km PAN mode
Satellite Data is recorded and products are available on
following media
Satellite data products are available in the following types of formats -
High Density Digital Tape (HDDT)
Quick Look Film
Computer Compatible Tape(CCT), Digital Audio Tape(DAT)
Compact Disc(CD-ROM)
70 mm film
240 mm Black and White film positive/negative in individual band.
Black and White paper prints & enlargement in individual band
240 mm False Colour Composite (FCC) Film
TYPES OF SENSORS:-
Optical Sensors used in remote sensing systems
MSS
T M
HRV
LISS I.II
LISS III
LISS IV
PAN
WIFS
Remote Sensing Sensors
Sensor is a device that gathers energy (EMR or other), converts it
into a signal and presents it in a form suitable for obtaining
information about the target under investigation. These may be
active or passive depending on the source of energy
Sensors used for remote sensing can be broadly classified as
those operating in Optical Infrared (OIR) region and those
operating in the microwave region. OIR and microwave sensors
can further be subdivided into passive and active
Active sensors use their own source of
energy. Earth surface is illuminated through energy emitted
by its own source, a part of its reflected by the surface in the
direction of the sensor is received to gather the information.
Passive sensors receive solar electromagnetic energy
reflected from the surface or energy emitted by the surface
itself. These sensors do not have their own source of energy
and can not be used at night time, except thermal sensors.
Again, sensors (active or passive) could either be imaging,
like camera, or Sensor which acquire images of the area and
non-imaging types like non-scanning radiometer or
atmospheric sounders.
Sensors which operate in this region
are :
Aerial cameras : 0.38 um to 0.9 um
Thermal scanners : 3 um to 5 um
: 8 um to 16 um
Multi spectral scanner : 0.3 um to 1.1 um
Microwave wavelengths : 1mm to 1 meter (Sensors which
operate in these wavelengths / frequencies are mostly active
systems like RADAR)
Multispectral Scanner (MSS) used in Landsat series
satellites
i) Multispectral scanner (Optical Mechanical Scanner)
onboard Landsat series of satellites of U.S.A. (L1, L2, L3, L4 & L5)
gives line scan type imagery using an oscillating mirror to
continuously scan the earth surface perpendicular to the spacecraft
velocity. Six lines are scanned simultaneously in each of the four
spectral bands for each mirror sweep. Spacecraft motion
provides the along-track progression of the scan lines. Radiation
is sensed simultaneously by an array of six detectors each of
four spectral bands from 0.5 to 1.1 micrometers. The detectors’
outputs are sampled, encoded and formatted into continuous
digital data
(ii)Thematic Mapper (TM) used in Landsat series satellites
Landsat 4 & 5 have onboard a new payload called "Thematic Mapper"
with 7 spectral bands & ground resolution of 30 meters. This is in addition
to the MSS payload which is identical to those carried onboard Landsat 1
& 2 and replaces RBV payload. TM is also an Optical Mechanical
Scanner, similar to MSS; however, being a 2nd generation line scanning
sensor, it ensures better performance characteristics in terms of (i)
improved pointing accuracy and stability, (ii) high resolution, (iii) new and
more number of spectral bands, (iv) 16 days repetitive coverage (v) high
scanning efficiency using bi-directional scanning and (vi) increased
quantization levels. For achieving the bi-directional scanning, a scanline
corrector (SLC) is introduced between the telescope and focal plane. The
SLC ensures parallel lines of scanning in the forward and reverse
direction.
iii)High Resolution Visible (HRV) Imager used in SPOT
Satellite
The French SPOT-1 spacecraft carries two nominally identical High
Resolution Visible (HRV) imagers, which can be operated independently
or in various coupled modes. In contrast to the oscillating mirror design
used in the Landsat imaging system, HRV cameras use Charge Coupled
Devices (CCD) array as the sensing element for the first time in space
environment. Each of the two cameras can be operated in either
multispectral (20 m resolution) mode or panchromatic (10 m resolution)
mode. The swath covered is 60 Km; and the cameras can be tilted offset
upto 27° on either side of Nadir. Thus any point within a width of 950 km.,
centered on the satellite track can be observed by programmed camera
control. SPOT-1 has stereo coverage capability in orbit with tiltable
cameras, which again provides stereo image pair al most similar to metric
camera air photo.
(iv)Linear Image Self Scanning (LISS) Camera
used in IRS-1A ,1B
Indian Remote Sensing Satellite (IRS-1A) fully designed and
fabricated by the Indian Space Research Organization
(ISRO) was launched on March 17th, 1988 by Russian
launcher. It has four spectral bands in the range of 0.45 to
0.86 μm (0.45 to 0.53 μm to 0.59 μm, 0.62 to 0.68 μm and
0.77 to 0.86 μm) in the visible and near infrared range with
two different spatial resolution of 72.5 m. and 36.25 meter
from one no. of open LISS-1 and two nos. of LISS-2 cameras
respectively. It provides repetitive coverage after every 22
days. Like all other LANDSAT/ SPOT missions which are
designed for global coverage IRS is also in sun synchronous,
polar orbit at about 900 km altitude and cover a width of 148
km. on ground. It uses linear array detectors (CCD) like
SPOT.
v) Linear Imaging Self Scanning Camera-3 (LISS-3
This camera is configured to provide imageries in three
visible bands as well as in short-wave infrared band. The
resolution and swath for visible bands are 23.5 m and 142
km, respectively. The detector is a 6000 element CCD
based linear array with a pixel dimension of 10μm by 7 μm.
The detector is placed at the focus of a refractive type
optical system consisting of eight lens elements, which
provides a focal length of 360 mm.
The processing of the analogue output video signal is
similar to that of PAN. For this camera, a 7-bit digitization is
used which gives an intensity variation of 128 levels.
Linear Imaging Self-Scanning Camera-4 (LISS-4)
LISS-4 camera serves the dual purpose of acquiring 70 km swath,
mono images giving continuity to the PAN camera of 1C/ 1D. In its
normal mode it acquires 23 km swath 3 band multispectral imagery,
which can be positioned anywhere in the 70 km coverage of Mono
mode. The enhanced dynamic range of 10 bits is intended to serve the
worldwide requirement of radiometric ranges. The stereo capability of
1C/ 1D is retained to provide the across track stereo to the
requirement of the users.
Panchromatic camera (PAN)
The PAN camera is configured to provide the imageries of
the Earth in visible spectrum, in a panchromatic band (0.5-
0.75 m) with a geometric resolution of greater than 10 m
and a swath of 70 km. The camera uses an off-axis
reflective type optics system consisting of three mirrors for
providing the required focal length. A 7μm pixel sized CCD
is being used as the detector element. Using three linear
array charge-coupled detectors covers the total swath of 70
km and each of these detectors covers aswath of about
The central detector is offset from the other two detectors
by a distance in focal plane that corresponds to 8.6 km on
the ground. The other two detectors cover swath of 24 km
each adjacent to the central CCD. These two detectors are
aligned with an accuracy of 30 arc sec-1. The overlap of
the central swath with the side swaths is 600 m on the
ground. Each of the detectors provides four analogue
outputs, which are independently processed by video
chains, converted to digital and providing a data handling
system for formatting. For a PAN data compatible with the
expected signal to noise ratio, a 6-bit digitization is used
which gives 64 radiometric gray levels.
Characteristics of PAN camera
Geometric resolution from altitude of 817 km 5.8 m Effective focal length
for optics 980 mm Swath 70 km Field-of-view for optics ±2.5o (across
track) ±0.3o (along track) Spectral band 0.5-0.75 μm
viii) Wide Field Sensor (WiFS)
This camera operates in two bands B3: 0.62 μm to 0.68 μm (Red) and
B4: 0.77 μm to 0.86 μm (NIR). Each band uses a 2048 element CCD
with an element size of 13 μm by 13 μm. A wide-angle refractive
optics system with 8-lens elements is used with a focal length of
about 56 mm. This payload required to cover a ground swath of 770
km with a resolution of 188 m. This ground swath with the selected
817 km orbit can provide the required repetivity for the intended
application.
To cover the 770 km, two separate band assemblies are
used for each band. Thus the entire swath in each band is
covered by two detectors. Each of the detectors covers half
of the swath. The signal processing chain in similar to
LISS-3 wherein the analogue video signal is converted to 7
bits and given to data handling system for formatting. Table
gives the characteristics of WiFS camera.
Characteristics of WiFS
Band 3 0.62-0.68 μm
Band 4 0.77-0.86 μm Resolution 188.3 m
Swath 810 km
Radiometric resolution 7 bits Band-to-band registration
±0.25 pixel
Advanced Wide Field Sensor (AWiFS) with a spatial
resolution of 56 m providing a swath of 740 km. The camera operates in
the Visible, Near Infra Red and Short Wave Infra Red spectral bands.
AWiFS is a unique camera having the capability to take the imagery of
the world repeatedly every 5 days, in the fields of agriculture, land and
water resources management, and, disaster management.
SATELLITE TYPES
1 LANDSAT Series
2. MODIS ,ASTER
3 SPOT Series
4. IRS SERIES
5. IKONOS
6. LIDAR
7. RADAR
8. SRTM
LANDSAT Series of Satellites
NASA, with the co-operation of the U.S. Department of Interior, began a
conceptual study of the feasibility of a series of Earth Resources Technology
Satellites (ERTS). ERTS-1 was launched on July 23, 1972. It represented the
first unmanned satellite specifically designed to acquire data about earth
resources on a systematic, repetitive, medium resolution, multispectral basis.
It was primarily designed as an experimental system to test that feasibility of
collecting earth resources data from unmanned satellites. Just prior to the
launch of ERTS-B on January 22nd 1975, NASA officially renamed the ERTS
programme as "LANDSAT" programme. All subsequent satellites in the series
carried the Landsat designation. So far five Landsat satellites have been
launched successfully, Table highlights the characteristics of the Landsat
series satellites mission. There have been four different types of sensors
included in various combinations on these missions.
CHARACTERISTICS OF LANDSAT MISSION
Sensor
System
Spectral
resolution
Spatial
resolution
Scan
width
Revisit Orbital
Altitude
IN KM
Launch
MSS B4 .5-.6
B5 .6-.7
B6 .7-.8
B7 .8-1.1
79X79 185 18 918 L1-72
L2-75
L3-78
L-4-82
TM B1 .45-.52
B2 .52-60
B3 .63-.69
B4 .76-.90
B5 1.55-1.75
B6 10.4-12.5
B7 2.08-2.35
30X30
120X120
185 16 710 L-5-1984
Multispectral Scanner (MSS) systems, Thematic Mapper (TM) and
Enhanced Thematic Mapper (ETM).
After more than two decades of success, the LANDSAT program
realized its first unsuccessful mission with the launch failure of
Landsat-6 on October 5, 1993. The sensor included on-board was
the Enhanced Thematic Mapper (ETM). To provide continuity with
Landsat -4 and -5 the ETM incorporated the same seven spectral
bands and the same spatialresolutions as the TM. The ETM's major
improvement over the TM was addition of an eighth panchromatic
band operating in 0.50 to 0.90μm ranges a spatial resolution of 15m.
Landsat-7 includes two sensors: the Enhanced Thematic Mapper
plus (ETM+) and the High Resolution Multispectral Stereo Imager
(HRMSI).
Characteristics of spectral bands of Aster
subsystem Band
no.
Spectral range Spatial
resolution
VNIR 1
2
3
4
.52-.60
.63-.69
.78-.86
.86-.92
15M
SWIR 5
6
7
8
9
10
1.600-1.700
2.145-2.185
2.185-2.225
2.235-2.285
2.295-2.365
2.360-2.430
30M
TIR 11
12
13
14
15
8.125-8.475
8.475-8.825
8.925-9.275
10.25-10.95
10.95-11.65
90M
SPOT SATELLITE
name launch sensors bands Spectral
range
resolution swath revisit
Spot-5 May 2005 Ms/vmi
4 .43-1.75 1 600x120km 1
spot
4
98 hrv 4
1
10
20
60 26
Spot
2-3
1990
1998 3
1
10
20
60 26
spot
1
1986 3
1
10
20
60 26
SPOT Series of Satellite
French Government in joint programme with Sweden and Belgium
undertook the development of Systeme Pour l'Observation de la Terre
(SPOT) program. Conceived and designed by the French Centre
National d'Etudes Spatiales (CNES), SPOT has developed into a large-
scale international programme with ground receiving stations and data
distribution outlets located in more than 30 countries. It is also the first
system to have pointable optics. This enables side-to-side off-nadir
viewing capabilities, and it affords full scene stereoscopic imaging from
two different satellite tracks permitting coverage of the same area. SPOT-
1 was retired from full-time services on December 31, 1990. The SPOT-2
satellite was launched on January 21, 1990, and SPOT-3 was launched
on September 25, 1993 Spot 4 was launched on 26 March 1998. SPOT-
1, -2 and -3 have identical orbits and sensor systems,
SPOT-4 includes the additional 20m-resolution
band in the mid-infrared portion of the spectrum (between 1.58 and 1.75μm).
This band is intended to improve vegetation monitoring and mineral
discriminating capabilities of the data. Furthermore, mixed 20m and 10m
data sets will be co-registered on-board instead of during ground processing.
This will be accomplished by replacing the panchromatic band of SPOT-1, -2
and -3 (0.49 to 0.73 μm) with red band from these systems (0.61 to 0.68
μm). This band will be used to produce both 10m black and white images
and 20m multispectral data. Another change in SPOT-4 is the addition of a
separate wide-field-of-view, sensor called the Vegetation
SPOT-5 is the latest in France's series of Earth observing
satellites, all of which were sent into orbit by Arianespace. Since the
first SPOT satellite was launched in 1986, the SPOT system has
sought to provide continuity of service and constantly improved
quality of
products for users. Spot 5 is the fifth satellite in the SPOT series,
placed into orbit by an Ariane5 launcher in May 2002.
IRS Satellite Series
The Indian Space programme has the goal of harnessing space
technology for application in the areas of communications,
broadcasting, meteorology and remote sensing. The important
milestones crossed so far are Bhaskara-1 and 2 (1979) the
experimental satellites, which carried TV Cameras and Microwave
Radiometers. The Indian Remote Sensing Satellite was the next logical
step towards the National operational satellites that directly generates
resources information in a variety of application areas such as forestry,
geology, agriculture and hydrology. IRS -1A/1B, carried Linear Self
Scanning sensors LISS-I & LISS-II. IRS-P2 launched in October 1994
on PSLV-D2 (an indigenous launch vehicle). IRS-1C, launched on
December 28, 1995, which carried improved sensors like LISS-III,
WiFS, PAN Camera, etc. Details of IRS series platforms are given in
the following section. IRS-P3 was launched into the sun synchronous
orbit by another indigenous launch vehicle PSLV - D3 on 21.3.1996
from Indian launching station Sriharikota (SHAR). IRS-1D was
launched on 29 September 1997 and IRS-P4 was launched on 26 May
1999.
Detatils of IRS Series Satellites
Name Launch Sensors Types Band
s
Spectral
range
Resol
ution
Swath Revisit
DAYS
IRS
1A
1988 L-I
L-II
MS 4 72.5
36.25
148
74
22
1B 1991 L-I
L-II
MS
4 72.5
22
1C Dec95 WiFS
LIII
PAN
MS
MS
PAN
2
3+1
1
R,NIR
G,R,NIR
SWIR1.55
-1.70
.50-.75
189
23.5
70
5.8
810
142
148
70
5
24
1D SEPT
97
774 24
Detatils of IRS Series Satellites
Nam
e
Launch Sensors Types Band
s
Spectral
range
Resol
ution
Swath Revisit
DAYS
Irs-
p6
oct200
3
AWiFS
LISS-III
LISS-IV
MS
PAN
MS
MS
3
1
3+1
3
G,R,NIR
SWIR1.5
5-1.70
GRNIR
SWIR
GRNIR
56
23
5.8
740
141
23MX
70PAN
5
24
Detatils of IRS Series Satellites
Name Launch Sensors Types Band
s
Spectral
range
Resol
ution
Swath Revisit
DAYS
Irs-
p6
oct2003 AWiFS
LISS-III
LISS-IV
MS
PAN
MS
MS
3
1
3+1
3
G,R,NIR
SWIR1.55
-1.70
GRNIR
SWIR
GRNIR
56
23
5.8
370,
740
141
23MX
70PAN
5
24
Detatils of IRS Series Satellites
Name Launch Sensors Types Band
s
Spectral
range
Resol
ution
Swath Revisit
DAYS
Irs-
p6
oct2003 AWiFS
LISS-III
LISS-IV
MS
PAN
MS
MS
3
1
3+1
3
G,R,NIR
SWIR1.55
-1.70
GRNIR
SWIR
GRNIR
56
23
5.8
370,
740
141
23MX
70PAN
5
24
Details of IRS Series of Satellites
Cartosat - 1
IRS-P6 (Resource -sat)
IRS-P4 (Oceansat)
IRS-1D
IRS-1C
IRS-1B
IRS-1A
Cartosat-may2005
irs-p6-oct2003
irs-p4 –may1999
irs-1d-sep1997
irs-1c-dec-1995
irs-1b-1991
irs-1a-1988
IRS-P4 (Oceansat-1)
IRS-P4 carries an Ocean Colour Monitor (OCM) and a Multi-frequency
Scanning Microwave Radiometer (MSMR), launched on May 26 1999.
OCM has 8 narrow spectral
bands operating in visible and near-infrared bands (402-885 nm) with a
spatial resolution of 350 m and swath of 1500 kms. IRS P4 OCM thus
provides highest spatial resolution compared to any other contemporary
satellites in the international arena during this time frame. The MSMR
with its all weather capability is configured to have measurements at 4
frequencies (6.6, 10.6, 18 & 26 GHZ) with an overall swath of 1500 km.
The spatial resolution is 120, 80, 40 and 40 kms for the frequency bands
of 6.6, 10.6, 18 and 26 GHz. MSMR will also be in a way a unique sensor
as no other passive microwave radiometer is operational in the civilian
domain today and will be useful for study of both physical oceanographic
and meteorological parameters.
RESOURCESAT-1
RESOURCESAT-1 was launched by ISRO's Polar Satellite
Launch Vehicle, PSLV-C5, from Satish Dhawan Space
Centre-SHAR on October 17, 2003. RESOURCESAT-1
carries three cameras on board:
A multi-spectral high spatial resolution camera, namely,
Linear Imaging Self Scanner-4 (LISS-4) providing a spatial
resolution of 5.8 m and a swath of 23 km. It operates in the
Visible and Near Infra Red spectral bands.
(ii) A multi-spectral Linear Imaging Self Scanner-3 (LISS-3),
which has a spatial resolution of 23 m and a swath of 141
km. It operates in the Visible, Near Infra Red and Short
Wave Infra Red spectral bands.
FCC Car Nicobar
IRS-P6-LISS-III BANDS 4
DATE OF PASS-
FEB.16,2005
R 24 Meter
IKONOS
The IKONOS-2 satellite was launched in September 1999
and has been delivering commercial data since early
2000. IKONOS is the first of the next generation of high
spatial resolution satellites. IKONOS data records 4
channels of multispectral data at 4-meter resolution and
one panchromatic channel with 1-meter resolution. This
means that IKONOS is first commercial satellite to deliver
near photographic quality imagery of anywhere in the
world from space.
Radiometric Resolution: Data is collected as 11 bits per
pixel (2048 gray tones). Timings of collecting / receiving
IKONOS data and satellite orbit characteristics vary
considerably depending on accuracy of product, extent
and area.
Advantages and Limitations of
Remote Sensing
The major advantages of remote sensing over the ground - based
methods are:
1.Synoptic view: Remote sensing process facilitates the study of
various features of earth's surface in their spatial relation to each
other and helps to delineate the required features and
phenomenon.
2.Accessibility: Remote sensing process makes it possible to
gather information about the inaccessible area when it is not
possible to do ground survey like in mountainous areas or foreign
lands.
3.Time: Since information about a large area can be gathered
quickly, the techniques save time and efforts of human beings/ or
mass.
4.Multi-disciplinary applications: The data gathered by remote
sensing process can be used by the users of different disciplines
like, geology, forestry land use etc.
Limitations of Remote Sensing Technology
1. Since resolution of the data from LISS-III is 23.5 M
the linear forest cover along roads, canals, bunds, rail of the
width less than the resolution are generally not be recorded.
2. young plantations and species having less chlorophyll
contents in their crown do not give proper reflectance and as
a result are difficult to be interpreted correctly.
3. considerable details on ground may be obscured in areas
having clouds and shadows. It is difficult to interpret such
areas without the help of collateral data.
4. variation in spectral reflectance during leaf less period
poses problems in interpretation.
5. gregarious occurrence of bushy vegetation, such as
lantana, sugarcane etc, often poses problems in delineation
of forest cover, as their reflectance is similar to that of tree
canopy.
Appropriate season for aerial/satellite data acquisition in forestry
1. Humid/moist evergreen and semi-evergreen
forests of western ghats and eastern ghats
January-February
2. Humid and moist evergreen and semi-evergreen
Andaman and
Nicobar Islands
February-March
forests of north-east India and
3.
Tropical moist deciduous forests of northern and
central India
December-January
4.
Temperate evergreen forests of western Himalayas
March-May
Temperate, sub-alpine, alpine evergreen, deciduous forests of Jammu
6.
Arid and semi-arid dry deciduous and scrub forest
October-December Mangrove for
period
5. Jammu and Kashmir
BASIC COMPONENTS OF AN IDEAL REMOTE SENSING
SYSTEM
1. Uniform energy source
2. A non interfering atmosphere
3. A series of unique energy- matter interactions at the
earth’s surface
4 A super sensor
5. A real-time data processing and supply system
6. Multiple data users
1.This source would provide energy over all
wavelength at a constant, known ,high level of output
irrespective of time and place.
2’This would be an atmosphere that would not modify
the energy from the source in any manner, whether
that energy were on its way to the earth’s surface or
coming from it. Again, ideally, this would irrespective
of wavelength, time, place and sensing altitude
involved.
3;These interactions would generate
reflected or emitted signals that not
only are selective with respect to
wavelength, but also are known,
invariant and unique to each and
every earth surface feature type and
subtype of interest.
4. This would be a sensor, highly
sensitive to all wavelengths, yielding
spatially detailed data on the absolute
brightness form a scene as a function of
wavelength throughout the spectrum.
This super sensor would be simple and
reliable. Require virtually no power or
space and be accurate and economical
to operate.
5.In this system, the instant the radiance wavelength
response over a terrain element was generated, it
would be transmitted to the ground, geometrically and
radio metrically corrected as necessary and processed
in to a readily interpretable format. Each data
observation would be recognized as being unique to the
particular terrain element form which came. This
processing would be performed nearly
instantaneously(real time) providing timely information.
6.These people would have knowledge of great depth both
of their respective disciplines and of remote sensing
data acquisition and analysis techniques. The same set
of data would become various forms of information for
different users, because of their wealth of knowledge
about the particular earth resources being sensed. This
information would be available to them faster, at less
expense and over larger areas than information
collected in any other manner, wise decision about how
best to manage the earth resources under scrutiny and
theses management decisions would be implemented.
Resolution
Resolution is defined as the ability of the system to
render the information at the smallest discretely
separable quantity in terms of distance (spatial),
wavelength band of EMR (spectral), time (temporal)
and/or radiation quantity (radiometric).
RESOLUTIN TYPES AND DEFINITIONS
TYPES:-
1. Spatial resolution
2. Spectral Resolution
3. Radiometric Resolution
4. Temporal Resolution
original image
1m pixel 2m pixel 5m pixel
10m pixel
30m pixel 
Object identification depending upon pixel size
Spatial resolution— the area on the earth’s surface that
can be seen by a sensor as being separate from its
surroundings and is represented by a pixel.
is the projection of a detector element or a slit onto the
ground. In other words scanners spatial resolution is the
ground segment sensed at any instant. It is also called
ground resolution element (GRE). The spatial resolution at
which data are acquired has two effects –the ability to
identify various features and quantify their extent
Spectral Resolution – the range of wavelength that satellite
imaging system can detect , it refers to the width and number of spectral
bands. the narrow band the greater spectral resolution.
describes the ability of the sensor to define fine wavelength intervals i.e.
sampling the spatially segmented image in different spectral intervals,
thereby allowing the spectral irradiance of the image to be determined.
Short wavelength
Visible range
blue band 0.45---0.52
Green band 0.52---0.60
Red band 0.60---0.70
IR 0.70---3.0
Thermal 3---5
8---14
Microwaves 1 mm ---1 m
Radiometric Resolution
is a measure of the sensor to differentiate the smallest change in the
spectral reflectance/remittance between various targets. The radiometric
resolution depends on the saturation radiance and the number of
quantization levels. Thus, a sensor whose saturation is set at 100%,
reflectance with an 8 bit resolution will have a poor radiometric sensitivity
compared to a sensor whose saturation radiance is set at 20%
reflectance and 7 bit digitization.
Temporal Resolution
is obtaining spatial and spectral data at certain time intervals. Temporal
resolution is the capability of the satellite to image the exact same area
at the same viewing angle at different periods of time. The temporal
resolution of a sensor depends on a variety of factors, including the
satellite/sensor capabilities, the swath overlap and latitude.
Suggested books
1) Lillesand Thomas M. & Kiefer Ralph 2003 : Remote
Sensing and Image Interpretation Third Edition John Villey
2) Campbell John B. 1996 : Introduction to Remote
Sensing, Taylor & Francis
3) Floyd F. Sabins : Remote Sensing and Principles and
Image Interpretation(1987)
4) Manual of Remote Sensing IIIrd Edition : American
Society of Photogrammtery and Remote Sensing 210, Little
Falls Street, Falls Church, Virginia-22046 USA.
5) George Joseph. 1996: Imaging Sensors ; Remote
Sensing Reviews, vol 13,Number 3-4.
6) P.J. Curran, 1985. Physical aspects of Remote Sensing
Longman Group UR Ltd, England.

Contenu connexe

Tendances

Scanners, image resolution, orbit in remote sensing, pk mani
Scanners, image resolution, orbit in remote sensing, pk maniScanners, image resolution, orbit in remote sensing, pk mani
Scanners, image resolution, orbit in remote sensing, pk maniP.K. Mani
 
Multispectral remote sensing
Multispectral remote sensingMultispectral remote sensing
Multispectral remote sensingDharmendera Meena
 
Sensors for remote sensing
Sensors for remote sensingSensors for remote sensing
Sensors for remote sensingMohsin Siddique
 
Basic of Remote Sensing
Basic of Remote SensingBasic of Remote Sensing
Basic of Remote Sensinggueste5cfed
 
hyperspectral remote sensing and its geological applications
hyperspectral remote sensing and its geological applicationshyperspectral remote sensing and its geological applications
hyperspectral remote sensing and its geological applicationsabhijeet_banerjee
 
Chapter 3: Remote sensing Technology
Chapter 3: Remote sensing TechnologyChapter 3: Remote sensing Technology
Chapter 3: Remote sensing TechnologyShankar Gangaju
 
HYPERSPECTRAL RS IN MINERAL MAPPING
HYPERSPECTRAL RS IN MINERAL MAPPINGHYPERSPECTRAL RS IN MINERAL MAPPING
HYPERSPECTRAL RS IN MINERAL MAPPINGAbhiram Kanigolla
 
Sentinel 2
Sentinel 2Sentinel 2
Sentinel 2Openmaps
 
Introduction to Landsat
Introduction to LandsatIntroduction to Landsat
Introduction to LandsatNizam GIS
 
Introduction to Synthetic Aperture Radar (SAR)
Introduction to Synthetic Aperture Radar (SAR)Introduction to Synthetic Aperture Radar (SAR)
Introduction to Synthetic Aperture Radar (SAR)NopphawanTamkuan
 
Platforms of Remote sensing and GIS
Platforms of Remote sensing and GISPlatforms of Remote sensing and GIS
Platforms of Remote sensing and GISMouna Guru
 
Thermal remote sensing and its applications
Thermal remote sensing and its applicationsThermal remote sensing and its applications
Thermal remote sensing and its applicationschandan00781
 
Remote sensing satellites with sensors
Remote sensing satellites with sensorsRemote sensing satellites with sensors
Remote sensing satellites with sensorsAnchit Garg
 
Remote sensing - Scanners
Remote sensing - ScannersRemote sensing - Scanners
Remote sensing - ScannersPramoda Raj
 

Tendances (20)

remote sensing
remote sensingremote sensing
remote sensing
 
Scanners, image resolution, orbit in remote sensing, pk mani
Scanners, image resolution, orbit in remote sensing, pk maniScanners, image resolution, orbit in remote sensing, pk mani
Scanners, image resolution, orbit in remote sensing, pk mani
 
Remote sensing
Remote sensing   Remote sensing
Remote sensing
 
Multispectral remote sensing
Multispectral remote sensingMultispectral remote sensing
Multispectral remote sensing
 
Basic of Geodesy
Basic of GeodesyBasic of Geodesy
Basic of Geodesy
 
Sensors for remote sensing
Sensors for remote sensingSensors for remote sensing
Sensors for remote sensing
 
Photogrammetry 1.
Photogrammetry 1.Photogrammetry 1.
Photogrammetry 1.
 
Basic of Remote Sensing
Basic of Remote SensingBasic of Remote Sensing
Basic of Remote Sensing
 
hyperspectral remote sensing and its geological applications
hyperspectral remote sensing and its geological applicationshyperspectral remote sensing and its geological applications
hyperspectral remote sensing and its geological applications
 
Chapter 3: Remote sensing Technology
Chapter 3: Remote sensing TechnologyChapter 3: Remote sensing Technology
Chapter 3: Remote sensing Technology
 
Microwave remote sensing
Microwave remote sensingMicrowave remote sensing
Microwave remote sensing
 
HYPERSPECTRAL RS IN MINERAL MAPPING
HYPERSPECTRAL RS IN MINERAL MAPPINGHYPERSPECTRAL RS IN MINERAL MAPPING
HYPERSPECTRAL RS IN MINERAL MAPPING
 
Sentinel 2
Sentinel 2Sentinel 2
Sentinel 2
 
Introduction to Landsat
Introduction to LandsatIntroduction to Landsat
Introduction to Landsat
 
Introduction to Synthetic Aperture Radar (SAR)
Introduction to Synthetic Aperture Radar (SAR)Introduction to Synthetic Aperture Radar (SAR)
Introduction to Synthetic Aperture Radar (SAR)
 
Basic remote sensing and gis
Basic remote sensing and gisBasic remote sensing and gis
Basic remote sensing and gis
 
Platforms of Remote sensing and GIS
Platforms of Remote sensing and GISPlatforms of Remote sensing and GIS
Platforms of Remote sensing and GIS
 
Thermal remote sensing and its applications
Thermal remote sensing and its applicationsThermal remote sensing and its applications
Thermal remote sensing and its applications
 
Remote sensing satellites with sensors
Remote sensing satellites with sensorsRemote sensing satellites with sensors
Remote sensing satellites with sensors
 
Remote sensing - Scanners
Remote sensing - ScannersRemote sensing - Scanners
Remote sensing - Scanners
 

En vedette

Ppt on remote sensing system
Ppt on remote sensing systemPpt on remote sensing system
Ppt on remote sensing systemAlisha Korpal
 
Remote sensing ppt
Remote sensing pptRemote sensing ppt
Remote sensing pptcoolmridul92
 
The Invention Of Satellite
The Invention Of SatelliteThe Invention Of Satellite
The Invention Of Satellitesjenglishclub
 
Remote Sensing Platforms and Sensors
Remote Sensing Platforms and SensorsRemote Sensing Platforms and Sensors
Remote Sensing Platforms and SensorsUday kumar Devalla
 
REMOTE SENSING
REMOTE SENSINGREMOTE SENSING
REMOTE SENSINGKANNAN
 
Fundamentals of remote sensing
Fundamentals of remote sensingFundamentals of remote sensing
Fundamentals of remote sensingAshok Peddi
 
Basics of Remote Sensing
Basics of Remote SensingBasics of Remote Sensing
Basics of Remote SensingAkash Tikhe
 
.remote sensing.Ece 402 unit-2
.remote sensing.Ece 402 unit-2.remote sensing.Ece 402 unit-2
.remote sensing.Ece 402 unit-2Vandana Verma
 
Lec 3 level 3-nu(nitrogen metabolism)
Lec 3  level 3-nu(nitrogen metabolism)Lec 3  level 3-nu(nitrogen metabolism)
Lec 3 level 3-nu(nitrogen metabolism)dream10f
 
Indian remote sensing satellite mission
Indian remote sensing satellite missionIndian remote sensing satellite mission
Indian remote sensing satellite missionadevekar
 
A presention on remote sensing & its application (1)
A presention on remote sensing & its application (1)A presention on remote sensing & its application (1)
A presention on remote sensing & its application (1)Ankit Singh
 
Gis in telecomm ppt
Gis in telecomm pptGis in telecomm ppt
Gis in telecomm pptAtiqa khan
 
Components of Remote Sensing
Components of Remote SensingComponents of Remote Sensing
Components of Remote SensingAbby Varghese
 
A Brief Introduction to Remote Sensing Satellites
A Brief Introduction to Remote Sensing Satellites A Brief Introduction to Remote Sensing Satellites
A Brief Introduction to Remote Sensing Satellites Alireza Rahimzadeganasl
 
Introduction to GIS and its Applications
Introduction to GIS and its ApplicationsIntroduction to GIS and its Applications
Introduction to GIS and its ApplicationsNAXA-Developers
 

En vedette (20)

Ppt on remote sensing system
Ppt on remote sensing systemPpt on remote sensing system
Ppt on remote sensing system
 
Remote sensing ppt
Remote sensing pptRemote sensing ppt
Remote sensing ppt
 
The Invention Of Satellite
The Invention Of SatelliteThe Invention Of Satellite
The Invention Of Satellite
 
Remote Sensing Platforms and Sensors
Remote Sensing Platforms and SensorsRemote Sensing Platforms and Sensors
Remote Sensing Platforms and Sensors
 
REMOTE SENSING
REMOTE SENSINGREMOTE SENSING
REMOTE SENSING
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
Fundamentals of remote sensing
Fundamentals of remote sensingFundamentals of remote sensing
Fundamentals of remote sensing
 
Basics of Remote Sensing
Basics of Remote SensingBasics of Remote Sensing
Basics of Remote Sensing
 
.remote sensing.Ece 402 unit-2
.remote sensing.Ece 402 unit-2.remote sensing.Ece 402 unit-2
.remote sensing.Ece 402 unit-2
 
Lec 3 level 3-nu(nitrogen metabolism)
Lec 3  level 3-nu(nitrogen metabolism)Lec 3  level 3-nu(nitrogen metabolism)
Lec 3 level 3-nu(nitrogen metabolism)
 
Indian remote sensing satellite mission
Indian remote sensing satellite missionIndian remote sensing satellite mission
Indian remote sensing satellite mission
 
A presention on remote sensing & its application (1)
A presention on remote sensing & its application (1)A presention on remote sensing & its application (1)
A presention on remote sensing & its application (1)
 
Indian remote sensing
Indian remote sensingIndian remote sensing
Indian remote sensing
 
Remote Sensing ppt
Remote Sensing pptRemote Sensing ppt
Remote Sensing ppt
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
Gis in telecomm ppt
Gis in telecomm pptGis in telecomm ppt
Gis in telecomm ppt
 
Sensors
SensorsSensors
Sensors
 
Components of Remote Sensing
Components of Remote SensingComponents of Remote Sensing
Components of Remote Sensing
 
A Brief Introduction to Remote Sensing Satellites
A Brief Introduction to Remote Sensing Satellites A Brief Introduction to Remote Sensing Satellites
A Brief Introduction to Remote Sensing Satellites
 
Introduction to GIS and its Applications
Introduction to GIS and its ApplicationsIntroduction to GIS and its Applications
Introduction to GIS and its Applications
 

Similaire à Remote sensing

Remote sensing-presentaion
Remote sensing-presentaionRemote sensing-presentaion
Remote sensing-presentaionMouna Guru
 
Remote Sensing Data Acquisition,Scanning/Imaging systems
Remote Sensing Data Acquisition,Scanning/Imaging systemsRemote Sensing Data Acquisition,Scanning/Imaging systems
Remote Sensing Data Acquisition,Scanning/Imaging systemsdaniyal rustam
 
Remote Sensing: Meaning, Concept and Components | Geography
Remote Sensing: Meaning, Concept and Components | GeographyRemote Sensing: Meaning, Concept and Components | Geography
Remote Sensing: Meaning, Concept and Components | GeographySrimantaKarak
 
Remote sensing by priyanshu kumar,9608684800
Remote sensing by priyanshu kumar,9608684800Remote sensing by priyanshu kumar,9608684800
Remote sensing by priyanshu kumar,9608684800PRIYANSHU KUMAR
 
Continuing chapter rs.pptx
Continuing chapter rs.pptxContinuing chapter rs.pptx
Continuing chapter rs.pptxThomasHundasa1
 
passive and active remote sensing systems, characteristics and operations
passive and active remote sensing systems,  characteristics and operationspassive and active remote sensing systems,  characteristics and operations
passive and active remote sensing systems, characteristics and operationsNzar Braim
 
Unit 1 introduction to remote sensing
Unit  1 introduction to remote sensing Unit  1 introduction to remote sensing
Unit 1 introduction to remote sensing Dhanalakshmi Dasari
 
Remote sensing by abhishek mahajan
Remote sensing by abhishek mahajanRemote sensing by abhishek mahajan
Remote sensing by abhishek mahajanAbhishek Mahajan
 
Remote sensing and application by Nikhil Pakwanne
Remote sensing and application by Nikhil PakwanneRemote sensing and application by Nikhil Pakwanne
Remote sensing and application by Nikhil PakwanneNIKHIL PAKWANNE
 
Remote sensing by Priyanshu kumar, 9608684800
Remote sensing by Priyanshu kumar, 9608684800Remote sensing by Priyanshu kumar, 9608684800
Remote sensing by Priyanshu kumar, 9608684800PRIYANSHU KUMAR
 
rsgis-unitii-160731062950.pdf
rsgis-unitii-160731062950.pdfrsgis-unitii-160731062950.pdf
rsgis-unitii-160731062950.pdfBSuresh26
 
Resolution and scanning system
Resolution and scanning systemResolution and scanning system
Resolution and scanning systemAglaia Connect
 
Remote Sensing platforms and types of RS.pptx
Remote Sensing platforms and types of RS.pptxRemote Sensing platforms and types of RS.pptx
Remote Sensing platforms and types of RS.pptxaaravpatel9794
 

Similaire à Remote sensing (20)

Remote sensing-presentaion
Remote sensing-presentaionRemote sensing-presentaion
Remote sensing-presentaion
 
Remote Sensing Data Acquisition,Scanning/Imaging systems
Remote Sensing Data Acquisition,Scanning/Imaging systemsRemote Sensing Data Acquisition,Scanning/Imaging systems
Remote Sensing Data Acquisition,Scanning/Imaging systems
 
Kannan RS.ppt
Kannan RS.pptKannan RS.ppt
Kannan RS.ppt
 
Remote Sensing: Meaning, Concept and Components | Geography
Remote Sensing: Meaning, Concept and Components | GeographyRemote Sensing: Meaning, Concept and Components | Geography
Remote Sensing: Meaning, Concept and Components | Geography
 
Remote sensing by priyanshu kumar,9608684800
Remote sensing by priyanshu kumar,9608684800Remote sensing by priyanshu kumar,9608684800
Remote sensing by priyanshu kumar,9608684800
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
Continuing chapter rs.pptx
Continuing chapter rs.pptxContinuing chapter rs.pptx
Continuing chapter rs.pptx
 
passive and active remote sensing systems, characteristics and operations
passive and active remote sensing systems,  characteristics and operationspassive and active remote sensing systems,  characteristics and operations
passive and active remote sensing systems, characteristics and operations
 
Unit 1 introduction to remote sensing
Unit  1 introduction to remote sensing Unit  1 introduction to remote sensing
Unit 1 introduction to remote sensing
 
Remote sensing by abhishek mahajan
Remote sensing by abhishek mahajanRemote sensing by abhishek mahajan
Remote sensing by abhishek mahajan
 
Remote sensing and application by Nikhil Pakwanne
Remote sensing and application by Nikhil PakwanneRemote sensing and application by Nikhil Pakwanne
Remote sensing and application by Nikhil Pakwanne
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
Remote sensing by Priyanshu kumar, 9608684800
Remote sensing by Priyanshu kumar, 9608684800Remote sensing by Priyanshu kumar, 9608684800
Remote sensing by Priyanshu kumar, 9608684800
 
rsgis-unitii-160731062950.pdf
rsgis-unitii-160731062950.pdfrsgis-unitii-160731062950.pdf
rsgis-unitii-160731062950.pdf
 
Introduction to Remote Sensing
Introduction to Remote SensingIntroduction to Remote Sensing
Introduction to Remote Sensing
 
Remote+Sensing
Remote+SensingRemote+Sensing
Remote+Sensing
 
Remote sensing
Remote sensingRemote sensing
Remote sensing
 
Resolution and scanning system
Resolution and scanning systemResolution and scanning system
Resolution and scanning system
 
Remote Sensing platforms and types of RS.pptx
Remote Sensing platforms and types of RS.pptxRemote Sensing platforms and types of RS.pptx
Remote Sensing platforms and types of RS.pptx
 
Remote Sensin
Remote SensinRemote Sensin
Remote Sensin
 

Dernier

Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek SchlawackFwdays
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyAlfredo García Lavilla
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Wonjun Hwang
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfSeasiaInfotech2
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 

Dernier (20)

Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
"Subclassing and Composition – A Pythonic Tour of Trade-Offs", Hynek Schlawack
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Commit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easyCommit 2024 - Secret Management made easy
Commit 2024 - Secret Management made easy
 
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
Bun (KitWorks Team Study 노별마루 발표 2024.4.22)
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
The Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdfThe Future of Software Development - Devin AI Innovative Approach.pdf
The Future of Software Development - Devin AI Innovative Approach.pdf
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 

Remote sensing

  • 1. Satellite Remote Sensing 1. Types of Remote Sensing Based on Source of Energy Platform 2. Types of Satellite 3. Types of Sensors 4. Limitations of Remote Sensing 5. Basic Components of an Ideal Remote Sensing System 6. Resolution Definition and types.
  • 2. Introduction to Remote sensing RS System capture radiation in different wavelength reflected/ emitted by the earth’s surface features and recorded it either directly on the film as in case of aerial photography or in digital medium letter is used for generating the images. R.S. provides valuable data over vast area in a short time about resources, meteorology and environment leading to better resource management and accelerating national development.
  • 3. The four organizations are engaged in remote sensing related activities besides several other central and state gov. and educational institutes:- 1.ISRO 2.SAC 3.NNRMS 4.NRSA
  • 4. Remote Sensing - Remote sensing is defined as the science which deals with obtaining information about objects on earth surface by analysis of data, received from a remote platform. Remote sensing can be either passive or active. Active systems have their own source of energy whereas the passive systems depend upon the solar illumination or self emission for remote sensing Principles of Remote Sensing Detection and discrimination of objects or surface features means detecting and recording of radiant energy reflected or emitted by objects or surface material. Different objects return different amount and kind of energy in different bands of the electromagnetic spectrum, incident upon it. This unique property depends on the property of material
  • 5. Stages in Remote Sensing 1. Emission of electromagnetic radiation, or EMR (sun/self- emission) 2.Transmission of energy from the source to the surface of the earth, as well as absorption and scattering 3. Interaction of EMR with the earth's surface: reflection and emission 4. Transmission of energy from the surface to the remote sensor 5. Sensor data output 6. Data transmission, processing and analysis
  • 6.
  • 7. Aerial Remote Sensing Aerial photography is the most commonly used form of remote sensing and is widely used for topographic mapping, surveys for geological, soil and forestry mapping, engineering, town planning and environmental surveys on larger scale.
  • 8. Remote Sensing Satellites As is known to us, many countries around the globe now have remote sensing satellite programs for land resources survey, environmental impact assessment, weather forecasting and ocean science studies. METSAT satellite programs for weather monitoring and LANDSAT satellite program for land resources surveys, both launched by the USA since 1960 and 1972.
  • 9. France has also started an ambitious 'SPOT' satellite series program with the launching of SPOT-1 on 22nd February, 1986. Japan has launched Marine Observation Satellite (MOS-1) on 19th Feb. 1987. RADARSAT is Canada's first remote sensing satellite launched during 1990. European Space Agency (ESA) has launched Earth Resources Satellite (ERS-1) in 1991. India has launched a number of experimental remote sensing satellites, Bhaskara-I (June, 1979) and Bhaskara-II (Nov., 1981), Indian Experimental Satellite
  • 10. INSAT series of satellite, multipurpose Geostationary satellite program, has among many sensors, (i) Very High Resolution Radiometer (VHRR) and (ii) Data Collection System
  • 11. Details of IRS Series of Satellites IRS 1A 1988 1B 1991 1C 1995 1D 1997 P6 2003 cartosat1-2005 cartosat2-2007
  • 12. Satellite Data Receiving Station The Govt. of India authorized NRSA to set up a Satellite Receiving Station to receive digital data from LANDSAT series of Satellites launched by NASA/USA. This LANDSAT Receiving Station started functioning since January, 1980 situated at Shadnagar, 55 km. south of Hyderabad.
  • 13. Data Acquisition Systems In Remote Sensing two types 1. Image forming ( active sensor system photography) 2. non image forming (passive sensor system satellite digital mode)
  • 14. Imaging (Image forming) Image forming systems are again of two types - framing type and scanning type. In the framing type, entire frame of image is acquired instantaneously in the basic image unit e.g. in a frame camera used in photography. In scanning type, the information is acquired sequentially from the surface in bits of picture elements or pixels, point by point and line by line, which may be arranged after acquisition into a frame format
  • 15. Non imaging type of sensors, are used to record a spectral quantity or a parameter as a function of time or distance ( such as Gamma radiation, magnetic field, temperature measurement etc.) They are mostly used for ground observation and in study of atmosphere and meteorology. These sensors do not form image and as such, are not used in operational remote sensing but give detailed information on spectral characteristics of the target .Such data is collected by sensor system in satellite and transmitted to earth, where it is received and recorded at Ground Station.
  • 16. Characteristics of LISS-3/ LISS-4 LISS-3 Spectral Bands B2 0.52-0.59 μm B3 0.62-0.68 μm B4 0.77-0.86 μm B5 1.55-1.70 μm LIV B2 0.52-0.59 μm B3 0.62 - 0.68 B4 0.77 - 0.86 spatial resolution L3 23.5 m for bands 2,3,4 70.5 m for band 5 L4 5.8 m (at nadir) Equivalent focal length (bands 2, 3, 4/ band 5) 347.5 mm/301.2 mm Swath 141 km for bands 2,3,4 148 km for band 5 23.9 km MS mode 70 km PAN mode
  • 17. Satellite Data is recorded and products are available on following media Satellite data products are available in the following types of formats - High Density Digital Tape (HDDT) Quick Look Film Computer Compatible Tape(CCT), Digital Audio Tape(DAT) Compact Disc(CD-ROM) 70 mm film 240 mm Black and White film positive/negative in individual band. Black and White paper prints & enlargement in individual band 240 mm False Colour Composite (FCC) Film
  • 18. TYPES OF SENSORS:- Optical Sensors used in remote sensing systems MSS T M HRV LISS I.II LISS III LISS IV PAN WIFS
  • 19. Remote Sensing Sensors Sensor is a device that gathers energy (EMR or other), converts it into a signal and presents it in a form suitable for obtaining information about the target under investigation. These may be active or passive depending on the source of energy Sensors used for remote sensing can be broadly classified as those operating in Optical Infrared (OIR) region and those operating in the microwave region. OIR and microwave sensors can further be subdivided into passive and active
  • 20. Active sensors use their own source of energy. Earth surface is illuminated through energy emitted by its own source, a part of its reflected by the surface in the direction of the sensor is received to gather the information. Passive sensors receive solar electromagnetic energy reflected from the surface or energy emitted by the surface itself. These sensors do not have their own source of energy and can not be used at night time, except thermal sensors. Again, sensors (active or passive) could either be imaging, like camera, or Sensor which acquire images of the area and non-imaging types like non-scanning radiometer or atmospheric sounders.
  • 21. Sensors which operate in this region are : Aerial cameras : 0.38 um to 0.9 um Thermal scanners : 3 um to 5 um : 8 um to 16 um Multi spectral scanner : 0.3 um to 1.1 um Microwave wavelengths : 1mm to 1 meter (Sensors which operate in these wavelengths / frequencies are mostly active systems like RADAR)
  • 22. Multispectral Scanner (MSS) used in Landsat series satellites i) Multispectral scanner (Optical Mechanical Scanner) onboard Landsat series of satellites of U.S.A. (L1, L2, L3, L4 & L5) gives line scan type imagery using an oscillating mirror to continuously scan the earth surface perpendicular to the spacecraft velocity. Six lines are scanned simultaneously in each of the four spectral bands for each mirror sweep. Spacecraft motion provides the along-track progression of the scan lines. Radiation is sensed simultaneously by an array of six detectors each of four spectral bands from 0.5 to 1.1 micrometers. The detectors’ outputs are sampled, encoded and formatted into continuous digital data
  • 23. (ii)Thematic Mapper (TM) used in Landsat series satellites Landsat 4 & 5 have onboard a new payload called "Thematic Mapper" with 7 spectral bands & ground resolution of 30 meters. This is in addition to the MSS payload which is identical to those carried onboard Landsat 1 & 2 and replaces RBV payload. TM is also an Optical Mechanical Scanner, similar to MSS; however, being a 2nd generation line scanning sensor, it ensures better performance characteristics in terms of (i) improved pointing accuracy and stability, (ii) high resolution, (iii) new and more number of spectral bands, (iv) 16 days repetitive coverage (v) high scanning efficiency using bi-directional scanning and (vi) increased quantization levels. For achieving the bi-directional scanning, a scanline corrector (SLC) is introduced between the telescope and focal plane. The SLC ensures parallel lines of scanning in the forward and reverse direction.
  • 24. iii)High Resolution Visible (HRV) Imager used in SPOT Satellite The French SPOT-1 spacecraft carries two nominally identical High Resolution Visible (HRV) imagers, which can be operated independently or in various coupled modes. In contrast to the oscillating mirror design used in the Landsat imaging system, HRV cameras use Charge Coupled Devices (CCD) array as the sensing element for the first time in space environment. Each of the two cameras can be operated in either multispectral (20 m resolution) mode or panchromatic (10 m resolution) mode. The swath covered is 60 Km; and the cameras can be tilted offset upto 27° on either side of Nadir. Thus any point within a width of 950 km., centered on the satellite track can be observed by programmed camera control. SPOT-1 has stereo coverage capability in orbit with tiltable cameras, which again provides stereo image pair al most similar to metric camera air photo.
  • 25. (iv)Linear Image Self Scanning (LISS) Camera used in IRS-1A ,1B Indian Remote Sensing Satellite (IRS-1A) fully designed and fabricated by the Indian Space Research Organization (ISRO) was launched on March 17th, 1988 by Russian launcher. It has four spectral bands in the range of 0.45 to 0.86 μm (0.45 to 0.53 μm to 0.59 μm, 0.62 to 0.68 μm and 0.77 to 0.86 μm) in the visible and near infrared range with two different spatial resolution of 72.5 m. and 36.25 meter from one no. of open LISS-1 and two nos. of LISS-2 cameras respectively. It provides repetitive coverage after every 22 days. Like all other LANDSAT/ SPOT missions which are designed for global coverage IRS is also in sun synchronous, polar orbit at about 900 km altitude and cover a width of 148 km. on ground. It uses linear array detectors (CCD) like SPOT.
  • 26. v) Linear Imaging Self Scanning Camera-3 (LISS-3 This camera is configured to provide imageries in three visible bands as well as in short-wave infrared band. The resolution and swath for visible bands are 23.5 m and 142 km, respectively. The detector is a 6000 element CCD based linear array with a pixel dimension of 10μm by 7 μm. The detector is placed at the focus of a refractive type optical system consisting of eight lens elements, which provides a focal length of 360 mm. The processing of the analogue output video signal is similar to that of PAN. For this camera, a 7-bit digitization is used which gives an intensity variation of 128 levels.
  • 27. Linear Imaging Self-Scanning Camera-4 (LISS-4) LISS-4 camera serves the dual purpose of acquiring 70 km swath, mono images giving continuity to the PAN camera of 1C/ 1D. In its normal mode it acquires 23 km swath 3 band multispectral imagery, which can be positioned anywhere in the 70 km coverage of Mono mode. The enhanced dynamic range of 10 bits is intended to serve the worldwide requirement of radiometric ranges. The stereo capability of 1C/ 1D is retained to provide the across track stereo to the requirement of the users.
  • 28.
  • 29. Panchromatic camera (PAN) The PAN camera is configured to provide the imageries of the Earth in visible spectrum, in a panchromatic band (0.5- 0.75 m) with a geometric resolution of greater than 10 m and a swath of 70 km. The camera uses an off-axis reflective type optics system consisting of three mirrors for providing the required focal length. A 7μm pixel sized CCD is being used as the detector element. Using three linear array charge-coupled detectors covers the total swath of 70 km and each of these detectors covers aswath of about
  • 30. The central detector is offset from the other two detectors by a distance in focal plane that corresponds to 8.6 km on the ground. The other two detectors cover swath of 24 km each adjacent to the central CCD. These two detectors are aligned with an accuracy of 30 arc sec-1. The overlap of the central swath with the side swaths is 600 m on the ground. Each of the detectors provides four analogue outputs, which are independently processed by video chains, converted to digital and providing a data handling system for formatting. For a PAN data compatible with the expected signal to noise ratio, a 6-bit digitization is used which gives 64 radiometric gray levels.
  • 31. Characteristics of PAN camera Geometric resolution from altitude of 817 km 5.8 m Effective focal length for optics 980 mm Swath 70 km Field-of-view for optics ±2.5o (across track) ±0.3o (along track) Spectral band 0.5-0.75 μm
  • 32. viii) Wide Field Sensor (WiFS) This camera operates in two bands B3: 0.62 μm to 0.68 μm (Red) and B4: 0.77 μm to 0.86 μm (NIR). Each band uses a 2048 element CCD with an element size of 13 μm by 13 μm. A wide-angle refractive optics system with 8-lens elements is used with a focal length of about 56 mm. This payload required to cover a ground swath of 770 km with a resolution of 188 m. This ground swath with the selected 817 km orbit can provide the required repetivity for the intended application.
  • 33. To cover the 770 km, two separate band assemblies are used for each band. Thus the entire swath in each band is covered by two detectors. Each of the detectors covers half of the swath. The signal processing chain in similar to LISS-3 wherein the analogue video signal is converted to 7 bits and given to data handling system for formatting. Table gives the characteristics of WiFS camera.
  • 34. Characteristics of WiFS Band 3 0.62-0.68 μm Band 4 0.77-0.86 μm Resolution 188.3 m Swath 810 km Radiometric resolution 7 bits Band-to-band registration ±0.25 pixel
  • 35. Advanced Wide Field Sensor (AWiFS) with a spatial resolution of 56 m providing a swath of 740 km. The camera operates in the Visible, Near Infra Red and Short Wave Infra Red spectral bands. AWiFS is a unique camera having the capability to take the imagery of the world repeatedly every 5 days, in the fields of agriculture, land and water resources management, and, disaster management.
  • 36.
  • 37. SATELLITE TYPES 1 LANDSAT Series 2. MODIS ,ASTER 3 SPOT Series 4. IRS SERIES 5. IKONOS 6. LIDAR 7. RADAR 8. SRTM
  • 38. LANDSAT Series of Satellites NASA, with the co-operation of the U.S. Department of Interior, began a conceptual study of the feasibility of a series of Earth Resources Technology Satellites (ERTS). ERTS-1 was launched on July 23, 1972. It represented the first unmanned satellite specifically designed to acquire data about earth resources on a systematic, repetitive, medium resolution, multispectral basis. It was primarily designed as an experimental system to test that feasibility of collecting earth resources data from unmanned satellites. Just prior to the launch of ERTS-B on January 22nd 1975, NASA officially renamed the ERTS programme as "LANDSAT" programme. All subsequent satellites in the series carried the Landsat designation. So far five Landsat satellites have been launched successfully, Table highlights the characteristics of the Landsat series satellites mission. There have been four different types of sensors included in various combinations on these missions.
  • 39. CHARACTERISTICS OF LANDSAT MISSION Sensor System Spectral resolution Spatial resolution Scan width Revisit Orbital Altitude IN KM Launch MSS B4 .5-.6 B5 .6-.7 B6 .7-.8 B7 .8-1.1 79X79 185 18 918 L1-72 L2-75 L3-78 L-4-82 TM B1 .45-.52 B2 .52-60 B3 .63-.69 B4 .76-.90 B5 1.55-1.75 B6 10.4-12.5 B7 2.08-2.35 30X30 120X120 185 16 710 L-5-1984
  • 40. Multispectral Scanner (MSS) systems, Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM). After more than two decades of success, the LANDSAT program realized its first unsuccessful mission with the launch failure of Landsat-6 on October 5, 1993. The sensor included on-board was the Enhanced Thematic Mapper (ETM). To provide continuity with Landsat -4 and -5 the ETM incorporated the same seven spectral bands and the same spatialresolutions as the TM. The ETM's major improvement over the TM was addition of an eighth panchromatic band operating in 0.50 to 0.90μm ranges a spatial resolution of 15m. Landsat-7 includes two sensors: the Enhanced Thematic Mapper plus (ETM+) and the High Resolution Multispectral Stereo Imager (HRMSI).
  • 41.
  • 42. Characteristics of spectral bands of Aster subsystem Band no. Spectral range Spatial resolution VNIR 1 2 3 4 .52-.60 .63-.69 .78-.86 .86-.92 15M SWIR 5 6 7 8 9 10 1.600-1.700 2.145-2.185 2.185-2.225 2.235-2.285 2.295-2.365 2.360-2.430 30M TIR 11 12 13 14 15 8.125-8.475 8.475-8.825 8.925-9.275 10.25-10.95 10.95-11.65 90M
  • 43. SPOT SATELLITE name launch sensors bands Spectral range resolution swath revisit Spot-5 May 2005 Ms/vmi 4 .43-1.75 1 600x120km 1 spot 4 98 hrv 4 1 10 20 60 26 Spot 2-3 1990 1998 3 1 10 20 60 26 spot 1 1986 3 1 10 20 60 26
  • 44. SPOT Series of Satellite French Government in joint programme with Sweden and Belgium undertook the development of Systeme Pour l'Observation de la Terre (SPOT) program. Conceived and designed by the French Centre National d'Etudes Spatiales (CNES), SPOT has developed into a large- scale international programme with ground receiving stations and data distribution outlets located in more than 30 countries. It is also the first system to have pointable optics. This enables side-to-side off-nadir viewing capabilities, and it affords full scene stereoscopic imaging from two different satellite tracks permitting coverage of the same area. SPOT- 1 was retired from full-time services on December 31, 1990. The SPOT-2 satellite was launched on January 21, 1990, and SPOT-3 was launched on September 25, 1993 Spot 4 was launched on 26 March 1998. SPOT- 1, -2 and -3 have identical orbits and sensor systems,
  • 45. SPOT-4 includes the additional 20m-resolution band in the mid-infrared portion of the spectrum (between 1.58 and 1.75μm). This band is intended to improve vegetation monitoring and mineral discriminating capabilities of the data. Furthermore, mixed 20m and 10m data sets will be co-registered on-board instead of during ground processing. This will be accomplished by replacing the panchromatic band of SPOT-1, -2 and -3 (0.49 to 0.73 μm) with red band from these systems (0.61 to 0.68 μm). This band will be used to produce both 10m black and white images and 20m multispectral data. Another change in SPOT-4 is the addition of a separate wide-field-of-view, sensor called the Vegetation SPOT-5 is the latest in France's series of Earth observing satellites, all of which were sent into orbit by Arianespace. Since the first SPOT satellite was launched in 1986, the SPOT system has sought to provide continuity of service and constantly improved quality of products for users. Spot 5 is the fifth satellite in the SPOT series, placed into orbit by an Ariane5 launcher in May 2002.
  • 46. IRS Satellite Series The Indian Space programme has the goal of harnessing space technology for application in the areas of communications, broadcasting, meteorology and remote sensing. The important milestones crossed so far are Bhaskara-1 and 2 (1979) the experimental satellites, which carried TV Cameras and Microwave Radiometers. The Indian Remote Sensing Satellite was the next logical step towards the National operational satellites that directly generates resources information in a variety of application areas such as forestry, geology, agriculture and hydrology. IRS -1A/1B, carried Linear Self Scanning sensors LISS-I & LISS-II. IRS-P2 launched in October 1994 on PSLV-D2 (an indigenous launch vehicle). IRS-1C, launched on December 28, 1995, which carried improved sensors like LISS-III, WiFS, PAN Camera, etc. Details of IRS series platforms are given in the following section. IRS-P3 was launched into the sun synchronous orbit by another indigenous launch vehicle PSLV - D3 on 21.3.1996 from Indian launching station Sriharikota (SHAR). IRS-1D was launched on 29 September 1997 and IRS-P4 was launched on 26 May 1999.
  • 47. Detatils of IRS Series Satellites Name Launch Sensors Types Band s Spectral range Resol ution Swath Revisit DAYS IRS 1A 1988 L-I L-II MS 4 72.5 36.25 148 74 22 1B 1991 L-I L-II MS 4 72.5 22 1C Dec95 WiFS LIII PAN MS MS PAN 2 3+1 1 R,NIR G,R,NIR SWIR1.55 -1.70 .50-.75 189 23.5 70 5.8 810 142 148 70 5 24 1D SEPT 97 774 24
  • 48. Detatils of IRS Series Satellites Nam e Launch Sensors Types Band s Spectral range Resol ution Swath Revisit DAYS Irs- p6 oct200 3 AWiFS LISS-III LISS-IV MS PAN MS MS 3 1 3+1 3 G,R,NIR SWIR1.5 5-1.70 GRNIR SWIR GRNIR 56 23 5.8 740 141 23MX 70PAN 5 24
  • 49. Detatils of IRS Series Satellites Name Launch Sensors Types Band s Spectral range Resol ution Swath Revisit DAYS Irs- p6 oct2003 AWiFS LISS-III LISS-IV MS PAN MS MS 3 1 3+1 3 G,R,NIR SWIR1.55 -1.70 GRNIR SWIR GRNIR 56 23 5.8 370, 740 141 23MX 70PAN 5 24
  • 50. Detatils of IRS Series Satellites Name Launch Sensors Types Band s Spectral range Resol ution Swath Revisit DAYS Irs- p6 oct2003 AWiFS LISS-III LISS-IV MS PAN MS MS 3 1 3+1 3 G,R,NIR SWIR1.55 -1.70 GRNIR SWIR GRNIR 56 23 5.8 370, 740 141 23MX 70PAN 5 24
  • 51. Details of IRS Series of Satellites Cartosat - 1 IRS-P6 (Resource -sat) IRS-P4 (Oceansat) IRS-1D IRS-1C IRS-1B IRS-1A
  • 53. IRS-P4 (Oceansat-1) IRS-P4 carries an Ocean Colour Monitor (OCM) and a Multi-frequency Scanning Microwave Radiometer (MSMR), launched on May 26 1999. OCM has 8 narrow spectral bands operating in visible and near-infrared bands (402-885 nm) with a spatial resolution of 350 m and swath of 1500 kms. IRS P4 OCM thus provides highest spatial resolution compared to any other contemporary satellites in the international arena during this time frame. The MSMR with its all weather capability is configured to have measurements at 4 frequencies (6.6, 10.6, 18 & 26 GHZ) with an overall swath of 1500 km. The spatial resolution is 120, 80, 40 and 40 kms for the frequency bands of 6.6, 10.6, 18 and 26 GHz. MSMR will also be in a way a unique sensor as no other passive microwave radiometer is operational in the civilian domain today and will be useful for study of both physical oceanographic and meteorological parameters.
  • 54. RESOURCESAT-1 RESOURCESAT-1 was launched by ISRO's Polar Satellite Launch Vehicle, PSLV-C5, from Satish Dhawan Space Centre-SHAR on October 17, 2003. RESOURCESAT-1 carries three cameras on board: A multi-spectral high spatial resolution camera, namely, Linear Imaging Self Scanner-4 (LISS-4) providing a spatial resolution of 5.8 m and a swath of 23 km. It operates in the Visible and Near Infra Red spectral bands. (ii) A multi-spectral Linear Imaging Self Scanner-3 (LISS-3), which has a spatial resolution of 23 m and a swath of 141 km. It operates in the Visible, Near Infra Red and Short Wave Infra Red spectral bands.
  • 55.
  • 56. FCC Car Nicobar IRS-P6-LISS-III BANDS 4 DATE OF PASS- FEB.16,2005 R 24 Meter
  • 57. IKONOS The IKONOS-2 satellite was launched in September 1999 and has been delivering commercial data since early 2000. IKONOS is the first of the next generation of high spatial resolution satellites. IKONOS data records 4 channels of multispectral data at 4-meter resolution and one panchromatic channel with 1-meter resolution. This means that IKONOS is first commercial satellite to deliver near photographic quality imagery of anywhere in the world from space. Radiometric Resolution: Data is collected as 11 bits per pixel (2048 gray tones). Timings of collecting / receiving IKONOS data and satellite orbit characteristics vary considerably depending on accuracy of product, extent and area.
  • 58.
  • 59. Advantages and Limitations of Remote Sensing The major advantages of remote sensing over the ground - based methods are: 1.Synoptic view: Remote sensing process facilitates the study of various features of earth's surface in their spatial relation to each other and helps to delineate the required features and phenomenon. 2.Accessibility: Remote sensing process makes it possible to gather information about the inaccessible area when it is not possible to do ground survey like in mountainous areas or foreign lands. 3.Time: Since information about a large area can be gathered quickly, the techniques save time and efforts of human beings/ or mass. 4.Multi-disciplinary applications: The data gathered by remote sensing process can be used by the users of different disciplines like, geology, forestry land use etc.
  • 60. Limitations of Remote Sensing Technology 1. Since resolution of the data from LISS-III is 23.5 M the linear forest cover along roads, canals, bunds, rail of the width less than the resolution are generally not be recorded. 2. young plantations and species having less chlorophyll contents in their crown do not give proper reflectance and as a result are difficult to be interpreted correctly. 3. considerable details on ground may be obscured in areas having clouds and shadows. It is difficult to interpret such areas without the help of collateral data. 4. variation in spectral reflectance during leaf less period poses problems in interpretation. 5. gregarious occurrence of bushy vegetation, such as lantana, sugarcane etc, often poses problems in delineation of forest cover, as their reflectance is similar to that of tree canopy.
  • 61. Appropriate season for aerial/satellite data acquisition in forestry 1. Humid/moist evergreen and semi-evergreen forests of western ghats and eastern ghats January-February 2. Humid and moist evergreen and semi-evergreen Andaman and Nicobar Islands February-March forests of north-east India and 3. Tropical moist deciduous forests of northern and central India December-January 4. Temperate evergreen forests of western Himalayas March-May Temperate, sub-alpine, alpine evergreen, deciduous forests of Jammu 6. Arid and semi-arid dry deciduous and scrub forest October-December Mangrove for period 5. Jammu and Kashmir
  • 62. BASIC COMPONENTS OF AN IDEAL REMOTE SENSING SYSTEM 1. Uniform energy source 2. A non interfering atmosphere 3. A series of unique energy- matter interactions at the earth’s surface 4 A super sensor 5. A real-time data processing and supply system 6. Multiple data users
  • 63. 1.This source would provide energy over all wavelength at a constant, known ,high level of output irrespective of time and place. 2’This would be an atmosphere that would not modify the energy from the source in any manner, whether that energy were on its way to the earth’s surface or coming from it. Again, ideally, this would irrespective of wavelength, time, place and sensing altitude involved.
  • 64. 3;These interactions would generate reflected or emitted signals that not only are selective with respect to wavelength, but also are known, invariant and unique to each and every earth surface feature type and subtype of interest.
  • 65. 4. This would be a sensor, highly sensitive to all wavelengths, yielding spatially detailed data on the absolute brightness form a scene as a function of wavelength throughout the spectrum. This super sensor would be simple and reliable. Require virtually no power or space and be accurate and economical to operate.
  • 66. 5.In this system, the instant the radiance wavelength response over a terrain element was generated, it would be transmitted to the ground, geometrically and radio metrically corrected as necessary and processed in to a readily interpretable format. Each data observation would be recognized as being unique to the particular terrain element form which came. This processing would be performed nearly instantaneously(real time) providing timely information.
  • 67. 6.These people would have knowledge of great depth both of their respective disciplines and of remote sensing data acquisition and analysis techniques. The same set of data would become various forms of information for different users, because of their wealth of knowledge about the particular earth resources being sensed. This information would be available to them faster, at less expense and over larger areas than information collected in any other manner, wise decision about how best to manage the earth resources under scrutiny and theses management decisions would be implemented.
  • 68. Resolution Resolution is defined as the ability of the system to render the information at the smallest discretely separable quantity in terms of distance (spatial), wavelength band of EMR (spectral), time (temporal) and/or radiation quantity (radiometric).
  • 69. RESOLUTIN TYPES AND DEFINITIONS TYPES:- 1. Spatial resolution 2. Spectral Resolution 3. Radiometric Resolution 4. Temporal Resolution
  • 70. original image 1m pixel 2m pixel 5m pixel 10m pixel 30m pixel  Object identification depending upon pixel size
  • 71. Spatial resolution— the area on the earth’s surface that can be seen by a sensor as being separate from its surroundings and is represented by a pixel. is the projection of a detector element or a slit onto the ground. In other words scanners spatial resolution is the ground segment sensed at any instant. It is also called ground resolution element (GRE). The spatial resolution at which data are acquired has two effects –the ability to identify various features and quantify their extent
  • 72. Spectral Resolution – the range of wavelength that satellite imaging system can detect , it refers to the width and number of spectral bands. the narrow band the greater spectral resolution. describes the ability of the sensor to define fine wavelength intervals i.e. sampling the spatially segmented image in different spectral intervals, thereby allowing the spectral irradiance of the image to be determined.
  • 73. Short wavelength Visible range blue band 0.45---0.52 Green band 0.52---0.60 Red band 0.60---0.70 IR 0.70---3.0 Thermal 3---5 8---14 Microwaves 1 mm ---1 m
  • 74. Radiometric Resolution is a measure of the sensor to differentiate the smallest change in the spectral reflectance/remittance between various targets. The radiometric resolution depends on the saturation radiance and the number of quantization levels. Thus, a sensor whose saturation is set at 100%, reflectance with an 8 bit resolution will have a poor radiometric sensitivity compared to a sensor whose saturation radiance is set at 20% reflectance and 7 bit digitization.
  • 75. Temporal Resolution is obtaining spatial and spectral data at certain time intervals. Temporal resolution is the capability of the satellite to image the exact same area at the same viewing angle at different periods of time. The temporal resolution of a sensor depends on a variety of factors, including the satellite/sensor capabilities, the swath overlap and latitude.
  • 76. Suggested books 1) Lillesand Thomas M. & Kiefer Ralph 2003 : Remote Sensing and Image Interpretation Third Edition John Villey 2) Campbell John B. 1996 : Introduction to Remote Sensing, Taylor & Francis 3) Floyd F. Sabins : Remote Sensing and Principles and Image Interpretation(1987) 4) Manual of Remote Sensing IIIrd Edition : American Society of Photogrammtery and Remote Sensing 210, Little Falls Street, Falls Church, Virginia-22046 USA. 5) George Joseph. 1996: Imaging Sensors ; Remote Sensing Reviews, vol 13,Number 3-4. 6) P.J. Curran, 1985. Physical aspects of Remote Sensing Longman Group UR Ltd, England.