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Biomass estimation of Shorea robusta with principal component analysis.of satellite data

Journal of Forestry Research 2010年第4期21卷 469-474,524页

作者： Nilanchal Patel Arnab Majumdar Birla Institute of Technology Mesra

Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis.was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis.between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis.be- tween the AGB and all the variables in each category of data. From the linear regression analysis. it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis.revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.

关键词： above ground biomass spectral response modeling vegetation indices principal component analysis linear and multiple regression analysis.

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