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CHARACTERISTICS OF LANDSAT MISSIONSensor
SystemSpectral
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 918L1-72
L2-75
L3-78
L-4-82
TM B1 .45-.52B2 .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
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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 spectralbands 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 0.90m 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).
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Characteristics of spectral bands of Aster
subsystem Band
no.
Spectral range Spatial
resolution
VNIR 12
3
4
.52-.60
.63-.69
.78-.86
.86-.92
15M
SWIR 56
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 1112
13
14
15
8.125-8.475
8.475-8.825
8.925-9.275
10.25-10.95
10.95-11.65
90M
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SPOT SATELLITE
name launch sensors bands Spectral
range
resolution swath revisit
Spot-5 May 2005 Ms/vmi4
.43-1.75 1 600x120km 1
spot
4
98 hrv 4
1
10
20
60 26
Spot2-3
1990
1998 31
1020
60 26
spot
1
1986 3
1
10
20
60 26
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SPOT Series of Satellite
French Government in joint programme with Sweden and Belgiumundertook 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 firstsystem 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,
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SPOT-4 includes the additional20m-resolutionband in the mid-infrared portion of the spectrum (between 1.58 and 1.75m).
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 m) with red band from these systems
(0.61 to 0.68 m). This band will be used to produce both 10m black and
white images and 20m multispectral data. Another change in SPOT-4 is theaddition 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.
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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 importantmilestones 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 inthe 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.
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Detatils of IRS Series SatellitesName 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
7422
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 SEPT97
774 24
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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
SWIRGRNIR
56
23
5.8
740
141
23MX70PAN
5
24
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Detatils of IRS Series SatellitesName 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
23MX70PAN
5
24
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Detatils of IRS Series SatellitesName 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
23MX70PAN
5
24
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Details of IRS Series of SatellitesCartosat - 1
IRS-P6 (Resource -sat)
IRS-P4 (Oceansat)
IRS-1DIRS-1C
IRS-1B
IRS-1A
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Cartosat-may2005
irs-p6-oct2003irs-p4may1999
irs-1d-sep1997irs-1c-dec-1995
irs-1b-1991
irs-1a-1988
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IRS-P4 (Oceansat-1)IRS-P4 carries an Ocean Colour Monitor (OCM) and a Multi-frequencyScanning 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 contemporarysatellites 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 sensoras 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.
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RESOURCESAT-1RESOURCESAT-1 was launched by ISRO's Polar SatelliteLaunch 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 141km. It operates in the Visible, Near Infra Red and Short
Wave Infra Red spectral bands.
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FCC Car Nicobar
IRS-P6-LISS-III BANDS 4
DATE OF PASS-
FEB.16,2005
R 24 Meter
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IKONOSThe 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. Thismeans 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 perpixel (2048 gray tones). Timings of collecting / receiving
IKONOS data and satellite orbit characteristics vary
considerably depending on accuracy of product, extent
and area.
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Advantages and Limitations of
Remote SensingThe major advantages of remote sensing over the ground - basedmethods 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 andphenomenon.
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.
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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 thewidth 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 areashaving 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
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Appropriate season for aerial/satellite data acquisition in forestry1. Humid/moist evergreen and semi-evergreen
forests of western ghats and eastern ghats
January-February
2. Humid and moist evergreen and semi-evergreen
Andaman andNicobar Islands
February-March
forests of north-east India and
3.
Tropical moist deciduous forests of northern andcentral 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-
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BASIC COMPONENTS OF AN IDEAL REMOTE SENSINGSYSTEM
1. Uniform energy source
2. A non interfering atmosphere3. A series of unique energy- matter interactions at the
earths surface
4 A super sensor
5. A real-time data processing and supply system
6. Multiple data users
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1.This source would provide energy over allwavelength at a constant, known ,high level of output
irrespective of time and place.
2This would be an atmosphere that would not modifythe energy from the source in any manner, whether
that energy were on its way to the earths surface or
coming from it. Again, ideally, this would irrespective
of wavelength, time, place and sensing altitude
involved.
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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.
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4. This would be a sensor, highlysensitive to all wavelengths, yielding
spatially detailed data on the absolute
brightness form a scene as a function ofwavelength throughout the spectrum.
This super sensor would be simple and
reliable. Require virtually no power or
space and be accurate and economical
to operate.
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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.
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6.These people would have knowledge of great depth bothof 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 knowledgeabout 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 andtheses management decisions would be implemented.
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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).
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RESOLUTIN TYPES AND DEFINITIONS
TYPES:-
1. Spatial resolution
2. Spectral Resolution
3. Radiometric Resolution
4. Temporal Resolution
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original image
1m pixel 2m pixel 5m pixel
10m pixel
30m pixel
Object identification depending upon pixel size
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Spatial resolutionthe area on the earths surface thatcan 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 theground. 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 effectsthe ability to
identify various features and quantify their extent
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Spectral Resolutionthe range of wavelength that satelliteimaging 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.
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Short wavelengthVisible 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---58---14
Microwaves 1 mm ---1 m
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Radiometric Resolutionis 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 ofquantization 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.
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Temporal Resolutionis obtaining spatial and spectral data at certain time intervals. Temporal
resolution is the capability of the satellite to image the exact same areaat 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.
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Suggested books
1) Lillesand Thomas M. & Kiefer Ralph 2003 : Remote
Sensing and Image Interpretation Third Edition John Villey2) 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.