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      Permanent link:
      https://www.ias.ac.in/article/fulltext/jbsc/020/03/0427-0438

    • Keywords

       

      Remote sensing; community analysis; vegetation mapping

    • 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.

    • Author Affiliations

       

      Shirish A Ravan1 2 P S Roy1 C M Sharma1 3

      1. Forestry and Ecology Division, Indian Institute of Remote Sensing, 4, Kalidas Road, Dehradun - 248 001, India
      2. IGCMC, WWF-India, 172B, Lodi Estate, New Delhi - 110 003, India
      3. Department of Forestry, HNB Garhwal University, Srinagar Garhwal - 246 174, India
    • Dates

       
  • Journal of Biosciences | News

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