Studies on forest carbon pools in tropical forest ecosystems of Karnataka, India using remote sensing and GIS [geographic information system]
2003
Rjashekar, G. | Gharai, B. | Giniraj, A. | Dutt, C.B.S. | Murthy, M.S.R.
Precise characterization of carbon (C) fluxes both in spatial and temporal domain is necessary to understand the C fluxes in relation to climate change. The carbon fluxes assessment becomes further complex in the tropics due to Land use and Land cover (LULC) changes which also exert force on land surface processes and feedbacks. Limited basic data is available in the tropics which could facilitate to understand land surface processes to climate change. The study presents a multi tier approach in providing inputs for estimation of carbon pools in parts of tropical forest ecosystems in Western Ghats, Karnataka, India using multiresolution satellite data and ground measurements. Spatial land cover heterogeneity analysis was done to identify optimal grid resolution for assessing the regional land cover distribution as an input for biomass assessment. Spatial patterns of stand density and basal area were assessed using trend surfaces generated by cokriging these parameter with LAI [leaf area index] surfaces generated using remote sensing. IRS LISS III and MODIS statellite data were used to analyze the feasibility of coarse resolution LAI products in biomass assessment. The study revealed that 1 km is the optimal grid size for retaining the identity of land cover heterogeneity in the selected forest ecosystem. Cokriging between stand density, basal area and LAI showed trends of spatial correlations at a range of 60 km. Significant relationships need to be explored using high resolution time composite LAI data and well distributed ground inventory points. The LAI levels generated using coarse resolution MODIS LAI have shown positive bias in relation to high resolution IRS LISS III LAI Levels. Biases observed are further analyzed in terms of registration errors, atmospheric correction and sub-pixel heterogeneity
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