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Estimation of carbon sequestration by using vegetation indices

The Global warming forces countries in the world to pay efforts reducing the amount of carbon emission. Forests play an important role in terms of absorbing and storing carbon dioxide. Many studies indicated that carbon sequestration can be efficiently estimated via a method combining with forest inventories and remote sensing. Therefore, a SPOT5 and a FORMOSAT-2 satellite image are used to extract different kinds of vegetation indices, e.g. the Normalized Difference Vegetation Index (NDVI) etc., incorporated with field data to calculate amount of carbon sequestration via four regression analysis methods. The results show that the estimation is workable with biomass indices and proposed regression methods. Moreover, the proposed regression models are better suitable to estimate the wood's volume of two forest types, e.g. pure artificial coniferous and artificial broadleaf mixed forest. However, the variants of MRA or BPNN can more accurately estimate the amount of carbon sequestration than original methods.