Space remote sensing for spatial vegetation characterization.
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Date
1995-06
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Abstract
The study area, Madhav National Park (MP) represents northern tropical dry
deciduous forest. The national park, due to its unique location (nearest to township), is
under tremendous biotic pressure. In order to understand vegetation structure and dynamics,
vegetation mapping at community level was considered important. Prolonged leafless period
and background reflection due to open canopy poses challenge in interpretation of satellite
data. The vegetation of Madhav National Park was mapped using Landsat TM data. The
ground data collected from sample points were subjected to TWINSPAN analysis to cluster
sample point data into six communities. The vegetation classification obtained by interpretation
(visual and digital) of remote sensing data and TWINSPAN were compared to validate the
vegetation classification at community level. The phytosociological data collected from
sample points were analysed to characterize communities. The results indicate that structural
variations in the communities modulate spectral signatures of vegetation and form basis to
describe community structure subjectively and at spatial level.
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Keywords
Remote sensing, community analysis, vegetation mapping
Citation
Ravan Shirish A, Roy P S, Sharma C M. Space remote sensing for spatial vegetation characterization. Journal of Biosciences. 1995 Jun; 20(3): 427-438.