India produces almost enough natural rubber to meet its entire industrial requirement. Presently,
the production of NR and its consumption almost match in the country, but in future it may be not balanced.
The satellite data analysis consisted of data preparation, ortho-rectification, image fusion, data normalization,
NDVI generation, digital classification, visual interpretation, accuracy assessment and acreage estimation.
Temporal LISS-III images were acquired at different periods under variable atmospheric conditions, solar
illumination and view angles and thus, require radiometric normalization to remove radiometric distortions and make
the images comparable.
Initially the digital numbers were converted to Top of the Atmospheric radiance (TOA) and subsequently, relative
radiometric normalization was carried out using Pseudo-Invariant Features (PIF).PIF corrected images were used
for generating of NDVI. The Normalized Difference Vegetation Index (NDVI) is a numerical indicator that uses
the reflectance in red and near-infrared bands of the electromagnetic spectrum which is sensitive to vegetation
cover, vigour, biomass and condition.
Temporal NDVI generated using Resourcesat-1 LISS-III data were used in hierarchical decision rule
based classification for delineation of natural rubber plantations.
Satellite data acquisition period in relation to tree phonological stages plays a critical role in spectral
discrimination of NR plantations from other vegetation types. Similarly, natural rubber showed
typical NDVI profile was coinciding with the tree phenology.
FCC of LISS-III data along with the classified data showing spatial distribution of natural rubber in
Tripura state.