clearly depends on maintaining the global greenhouse 
equilibrium, an important component of which is 
conservation of forests (Rao, 1996). To define 
conservation on forest ecosysteiti, understanding of the 
biospherical processes, their spatial inter linkages and 
continuous monitoring of the human interventions are 
necessary. Satellite remote sensing plays an important 
role in determining the above needs, alongwith 
enhancing and monitoring through repetitive coverage 
over different spatio-temporal scales. The integrated 
information derived from the satellite data set assists in 
evolving of appropriate action plans for initiating 
sustainable development. Hence, to redefine effective 
forest management and environmental protection, an 
integrated approach using biophysical and socio 
economic information need to be developed at national 
level. Geoinformatic would play an important role in 
ensuing millennium, the geospatial data will provide 
valuable information through process modelling and 
monitoring. 
1.1 Forest Management 
Forests are known to be the most important 
renewable natural resources. However due to socio 
economic and socio-political reasons, India has faced 
one serious problem of forest degradation in the tropical 
world. Present world average of forest per person is 
7000 sq. mt as against Indian average of 700 sq. mt. As 
stated the forest resources and forestlands need to be 
managed in such a way that they meet the socio 
economic and forest produce needs, not only of this 
generation but for future too. In this context, forest 
management strategy in India should be based on very 
reliable database on forest area, their productive 
potential and ameliorating sites. The detailed forest 
cover type maps which are often required for laying of 
individual felling coupes, planning of roads, fire lines, 
wildlife habitat management for day to day management 
are not available today. Hence a quick repetitive and 
accurate information about forest cover is required at the 
local, regional (state) and national levels for various 
purposes. Satellite remote sensing and Geographic 
Information System (GIS) have demonstrated that 
together with the ground data they have potential to 
provide comprehensive information on various facets of 
forest management in India (Fig. 1). The present paper 
attempts to analyse the experiences of two decades of 
the application of Satellite Remote Sensing in India with 
particular reference to forestry. The spatial modelling 
approaches that provide the ability to support decisions 
in forest management are also highlighted. 
2. DEFORESTATION ‘HOT SPOT’ MAPPING 
National Remote Sensing Agency (NRSA) for the 
first time used 1:1 million images for the periods 1972- 
75 and 1980-82 and forest cover have been classified 
into three categories viz., Closed, Mangrove & 
Open/Degraded (NRSA, 1983). Based on Satellite 
Remote Sensing, national database is available to 
analyse the national forest cover. This data has been 
compiled in the form of Forest Information System 
(FRIS) at the Indian Institute of Remote Sensing (IIRS). 
Generation of Information on forest cover in India at 
national level has been done on 1:1 million and 
1:250,000 scale using visual interpretation of false 
colour images. 
Forest Survey of India (FSI) uses satellite images 
to map forests on 1:250,000 scale. This experience has 
been extended in evolving the national programme to 
monitor national vegetation regularly. This data has been 
compiled at district level alongwith socio-economic 
information in the form of FRIS at IIRS. Based on the 
trends of deforestation, population growth, cattle 
population, grazing pressure, forest fire incidence, 
‘Hotspots’ have been mapped in different districts. 
3. FOREST STOCK MAPPING 
Stock maps depict forest types, density, 
encroachments, cultivation patches, regeneration status 
and reveal information about available resources. 
Conventional ground surveys are time consuming and 
strenuous. Visual or digital classification and 
interpretation methodology for updating stock maps 
from high resolution satellite data like IRS-1C PAN 
have shown possibility of achieving more informative 
stock maps than conventional ones. 
The state Forest departments like, Karnataka, 
Maharastra, Rajasthan, Andhra Pradesh and Madhya 
Pradesh have started using satellite remote sensing data 
for mapping on 1:50,000 scale and overlaying 
compartment boundaries to obtain stock information. 
This approach needs further consolidation by 
incorporating digital approaches in data enhancements 
or classification. For intensive forest management, this 
mapping should be done on 1:25 000 scale using IRS 
LISS III and PAN hybrid images. Though the strategies 
have shifted from commercial forestry to conservation 
forestry, people oriented productivity in terms of non 
wood forest products have to be estimated for their yield 
regulation. Hence, estimating growing stock in terms of 
wood and non-wood forest produce is a priority. 
Multistage sampling approach using remote sensing 
provides most reliable estimate of forest resource 
stockings (Chacko, 1964). Ultimately, stratified 
populations (at different levels) are sampled to estimate 
total stock. This approach with multi-resolution sensor 
systems can provide higher accuracy estimation.