• Shirish A Ravan

      Articles written in Journal of Biosciences

    • Biomass estimation using satellite remote sensing data—An investigation on possible approaches for natural forest

      P S Roy Shirish A Ravan

      More Details Abstract Fulltext PDF

      Vegetation type and its biomass are considered important components affecting biosphere-atmosphere interactions. The measurements of biomass per unit area and productivity have been set as one of the goals for International Geosphere-Biosphere Programme (IGBP). Ground assessment of biomass, however, has been found insufficient to present spatial extent of the biomass. The present study suggests approaches for using satellite remote sensing data for regional biomass mapping in Madhav National Park (MP). The stratified random sampling in the homogeneous vegetation strata mapped using satellite remote sensing has been effectively utilized to extrapolate the sample point biomass observations in the first approach.

      In the second approach attempt has been to develop empirical models with satellite measured spectral response and biomass. The results indicate that there is significant relationships with spectral responses. These relationships have seasonal dependency in varying phonological conditions. The relationships are strongest in visible bands and middle infrared bands. However, spectral biomass models developed using middle infrared bands would be more reliable as compared to the visible bands as the later spectral regions are less sensitive to atmospheric changes

      It was observed that brightness and wetness parameters show very strong relationship with the biomass values. Multiple regression equations using brightness and wetness isolates have been used to predict biomass values. The model used has correlation coefficient of 0.77. Per cent error between observed and predicted biomass was 10.5%. The biomass estimated for the entire national park using stratified and spectral response modelling approaches were compared and showed similarity with the difference of only 4.69%. The results indicate that satellite remote sensing data provide capability of biomass estimation

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