Remote sensing resolution

1. Sensor Resolution
Definition: Ability of a sensor to record and display fine details
4 types of sensor resolutions:
1. Spatial Resolution
 A measure of the smallest angular or linear separation between two objects that can be
resolved by the sensor.
 It is the ability of the sensor to measure the size of the smallest possible feature that can
be detected
 It is dependant of the IFOV of the sensor. IFOV is the angular cone of the sensor. Size of the
area viewed is determined by multiplying the IFOV by flying height. Area seen on the
ground is called resolution cell which is the maximum spatial resolution of the sensor
 For a feature to be detected, its size should be equal or larger than the resolution cell
 Finer the resolution, lesser the total ground area can be seen
 Finer the resolution, smaller the objects can be detected
 Military sensors have finer resolution as compared to commercial sensors

2. 2. Spectral Resolution
 Number and size of the specific wavelength intervals (bands) of the
electromagnetic spectrum to which the sensor is sensitive
 Ability of a sensor to define the fine wavelengths intervals (bands)
Finer the spectral resolution, narrower the wavelength ranges of a
particular band
Black and white films record only visible bands of the EM spectrum while
color film also does same but can detect the colors of RGB so have higher
spectral resolution compared to former one
 Multispectral and Hyperspectral sensors
 High spectral resolution helps in discrimination between different targets
based on their spectral response in each of the narrow bands

3. 3. Radiometric Resolution
Actual information content in an image.
Radiometric resolution of an imaging system describes its ability to
discriminate very slight differences in energy.
Finer the radiometric resolution, more the sensitivity to detect small
differences in reflected or emitted energy.
 imagery data are represented in positive digital numbers which depends on
the number of bits used for coding numbers in binary format e.g. 2 bits, 4
bits, 32 bits, 64 bits. Each bit records an exponent of power 2.
For example 8 bits mean 2 to the power 8 means 2x2x2x2x2x2x2x2=256
where 0 (Black) means low reflection, 255 (White) means high reflection)
 CartoSat 2 uses 10 bits coding

4. Temporal Resolution
 frequency of obtaining data over a given area
It is related with the revisit period which is often in days (e.g. CartoSat 2 has
4 days revisit time and 14 with 14 orbits per day while CartoSat 3 has

5. The Saga of Indian Remote Sensing Satellite System
• IRS-1A, the first of the series of indigenous state-of-art operating remote
sensing satellites, was successfully launched into a polar sun-synchronous
orbit on March 17, 1988 from the Soviet Cosmodrome at Baikonur.
• The successful launch of IRS-1A was one of the proudest moments for the
entire country, which depicted the maturity of satellite to address the various
requirements for managing natural resources of the nation. Its LISS-I had a
spatial resolution of 72.5 meters with a swath of 148 km on ground sensors,
LISS-II A and LISS-II B, with spatial resolution of 36.25 meters each and
mounted on the spacecraft in such a way to provide a composite swath of
146.98 km on ground. LISS-II had two separate imaging sensors
• The IRS-1A satellite, with its LISS-I and LISS-II sensors quickly enabled
India to map, monitor and manage its natural resources at coarse and
medium spatial resolutions. The operational availability of data products to
the user organisations further strengthened the operationalisation of remote
sensing applications and management in the country.

6. • Starting with IRS-1A in 1988, ISRO has launched many
operational remote sensing satellites. Today, India has one of
the largest constellations of remote sensing satellites in
operation. Currently, *thirteen* operational satellites are in Sun-
synchronous orbit – RESOURCESAT-1, 2, 2A CARTOSAT-1, 2,
2A, 2B, RISAT-1 and 2, OCEANSAT-2, Megha-Tropiques,
SARAL and SCATSAT-1, and *four* in Geostationary orbit-
INSAT-3D, Kalpana & INSAT 3A, INSAT -3DR.
• The data from these satellites are used for several applications
covering agriculture, water resources, urban planning, rural
development, mineral prospecting, environment, forestry, ocean
resources and disaster management.