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respectively from SPOT series of satellite in later
half of eighties have supplemented with the effort of
generating information on natural resources.
The indigenous effort on design and development
of satellites and sensors led initially to the launch of
Indian Remote Sensing Satellite (IRS-1A and B),
carrying Linear Imaging Self-scanning Sensors
(LISS-I and Il with the spatial resolution comparable
with those of Landsat MSS and TM, respectively in
late eighties and early nineties. Further
development in the sensor technology had resulted
in the launch of the state-of-the-art satellite (IRS-IC)
in December, 1995 with the following three unique
Sensors:
(i) Wide Field sensor (WiFS) with 188 m spatial, two
spectral bands - red and near infrared, 810 km
swath and a repetivity of 5 days.
(ii) Linear Imaging Self-scanning Sensor (LISS-III)
with 23.5m spatial resolution in the green red and
near infrared region, and 70.5 m in the middle
infrared region, and 140 km swath,
(iii) Panchromatic (PAN) camera with 5.8 m spatial
resolution, 70 km swath and stereo capability.
While WiFS with 5-day repetivity and large swath to
provide regional level monitoring of crop condition
assessment, LISS - Ill multispectral sensor with
140 km. swath provides detailed level crop acreage
estimation and crop condition assessment. PAN
data with 5.8m spatial resolution and stereo
capability enables appreciation of terrain's relief.
Merging LISS-II data with PAN offers additional
advantage of exploiting both spectral information
from LISS-II and high spatial information from
LISS-II! and high spatial resolution from PAN for
such applications as geomorphological mapping,
soil resources mapping and terrain analyses. The
uniqueness of these sensors lies in the fact that all
the sensors with regional and local level coverage
are mounted on the same platform and collect data
under similar illumination conditions. Hence
avoiding the need for radiometric normalization.
Further, the development of launch vehicles
especially Polar Satellite Launch Vehicle (PSLV)
has enabled India, launching three experimental
satellites, namely IRS-P1 in September, 1993, IRS-
P2 in October 1994 and IRS-P3 in March, 1996.
The IRS-P3 has two payloads namely Wide Field
Sensors (WiFS) which is also aboard IRS-1C/1D,
and Modular Electro-optical Scanner (MOS) with 13
channels spanning from blue to middle infrared
region of the electromagnetic spectrum.
For visual interpretation the standard false colour
composite (FCC) prints generated from green, red
and near infrared bands have been used.
However, special products with varying combination
of spectral bands have also been tried out for
certain specific applications. For instance, red, near
infrared and shortwave infrared combination has
been found to help improved delineation of
lithological boundaries - an important element in soil
resources mapping.
Apart from supervised classification of digital
multispectral data, new classification algorithms like
fuzzy logic, artificial neural network, etc have been
developed which help refining the information
generated on natural resources using per-pixel
classifier. Further, using advanced image fusion
techniques like Intensity, Hue and Saturation (IHS)
transformation, further refinement in the
information on natural resources could be made.
Similarly, for monitoring changes that have taken
place either due to developmental programmes or
land degradation, image differencing and principal
component analysis provide more objective
assessment of such changes.
Hitherto, only optical sensor data with a few broad
spectral bands have been used to generate base
line information on natural resources. The
hyperspectral remote sensing with a potential to
provide diagnostic capability of some natural
features like minerals, vegetation, etc will help
refining the information generated on natural
resources.
Imaging the terrain in the presence of smoke, haze
and cloud cover has been the major limitation of the
optical sensor data. The microwave data with day-
and-night observation; and cloud/haze/smoke
penetration capability hold very good promise for
generating information on crop coverage, floods,
etc. during monsoon season. The polarimetric
images generated from microwave energy with
different polarization provide further insight into
structure and flouristics of vegetation, soil
properties and parent material (Skidmore, 1996).
Further, radar interferometry is yet another tool that
enables generating DEM which allows monitoring
glaciers, volcanic eruption, mine subsidence,
mudslips, etc.
Integration of information on natural resources,
socio-economic and climatic conditions and other
related ancillary information in a holistic manner for
prescribing locale-specific intervention for a given
area is very crucial. Geographic Information
System (GIS) offers the capability of integrating
spatial and attribute data and subsequent
generation of action plan/developmental plan for
sustainable development.
Intemational Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998 159
