integrated assessment of natural resources. Integrated 
assessment can be defined as an interdisciplinary process 
of combining, interpreting and communicating 
knowledge from diverse scientific disciplines. The aim 
is to describe the entire cause-effect chain of a problem 
so that it can be evaluated from a synoptic perspective. 
Integrated assessment has two characteristics: (i) it 
should provide added value compared to single 
disciplinary assessment; and (ii) it should offer decision 
makers useful information (Rotmans and Dowlatabadi 
(1996). Integrated assessment is an iterative, continuing 
process, whereby on the one hand comprehensive 
insights from the scientific community are communi 
cated to the decision making community, and on the 
other, lessons learned by decision-makers contribute to 
the input for scientific investigations. 
6. ROLE OF SPACE TECHNOLOGY 
The information on nature, extent, spatial 
distribution, and potential and limitations of natural 
resources is a pre-requisite for planning the strategy for 
sustainable development. In addition, socio-economic 
and meteorological, and other related ancillary 
information is also required while recommending locale- 
specific prescriptions for taking up curative or 
preventive measures. By virtue of synoptic view of a 
fairly large area at regular interval, spaceborne 
multispectral data have been used at operational level for 
generating base line information on mineral resources, 
soils, ground water and surface water, land use/iand 
cover, forests, etc. at scales ranging from regional to 
micro level i.e. 1:250,000 to 1:12,500 scale and 
monitoring the changes, if any, over a period of time. 
Beginning with the Landsat-MSS data with a 60x80 m 
spatial resolution and four spectral bands spanning from 
green to near infrared in early seventies, the natural 
resources scientists had access to Landsat-TM data with 
a 30m spatial resolution and seven spectral bands spread 
over between blue and thermal infrared region of the 
electromagnetic spectrum in early eighties which helped 
further refinement and generation of thematic 
information at further larger scale. Further, high spatial 
resolution HRV-MLA and PLA data with 20m and 10m 
spatial resolution, respectively from SPOT series of 
satellite in later half of eighties have supplemented 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 (1RS-1A and B), 
carrying Linear Imaging Self-scanning Sensors (LISS-I 
and II) 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 
resolution, 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 23.5 m 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-I 11 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-III data 
with PAN offers additional advantage of exploiting both 
spectral information from LISS-III 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-IE 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) same as 
the one 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 infra-red bands have been used. Flowever, special 
products with varying combination of spectral bands 
have also been tried out for certain specific applications. 
For instance, red, near infrared and short wave 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 Gaussian maximum 
likelihood per-pixel classifier. Further, using advanced 
image fusion techniques like Intensity, Hue and