Resolution.pptx 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.