4 - Central Institute of Brackishwater Aquaculture

Natlonal Workshop-cum-Tralnlng on Bioinforrnatia and Information Management in A ~U~CU~~UN
about 3 times. To pass from identification to analysis a further improvement in
spatial resolution of 10 or more times may be needed.
A "High Resolution" image refers to one with a small resolution size. Fine
details can be seen in a high resolution image. On the other hand, a "Low
Resolution" image is one with a large resolution size, i.e, only coarse features
can be observed in the image.
Spectral resolution is determined by the band widths of the channels used in
the imaging system. High spectral resolution is achieved by band widths which
collectively are likely to provide more accurate spectral signature for discrete
objects than by broad bandwidths. Spectral resolution varies from a single band
panchromatic system, four or seven multispectral band system in IRS SPOT and
many satellite systems to many hyper-spectral bands of TERRA or AQUA MODIS
satellite system.
Radiometric Resolution refers to the smallest change in intensity level that
can be detected by the sensing system. The intrinsic radiometric resolution of a
sensing system depends on the signal to noise ratio of the detector. In a digital
image, the radiometric resolution is limited by the number of discrete
quantization levels used to digitize the continuous intensity value. With a given
spectral resolution, increasing the number of quantizing levels or improving the
radiometric resolution will improve discrimination between scene objects.
Interdependency between spatial, spectral and radiometric resolutions for each
remote sensing system affect the various compromises and trade offs.
Temporal resolution is an important consideration when determining the
resolution characteristics of a sensor system. It is defined by the repetitive
period of the sensors. This is very important to monitor any temporal dynamics
of the features. For example, temporal growth profile of a crop monitored
through remote sensing derived parameters helps in identifying and
discriminating it.
2.1.3 Remote Sensing as a Data Source
As Remote sensing is the noninvasive and non destructive gathering of
information about the features, it has become a valuable source of input for GIs
databases because remote sensing data (in particular satellite-borne) provides
synoptic viewing, data comparability, repeat coverage, the capability for
historical record, as well as the provision of data in the non-visible part of the
spectrum.
Again satellite systems such as SPOT, NOAA -AVHRR and IRS -WiFS acquire
data for large areas in a short time period, there by providing essentially uniform
coverage with respect to data and level of detail. Such data are already in digital
form and are provided more or less standard formats. These data products are
available for almost all the earth's land areas and are inexpensive relative to
alternate sources. Although imageries are not planimetrically correct, pre
processing can often bring data to acceptable levels of geometric accuracy with
only modest effort.