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Analysis of SAR interferometry for tree height estimation over hilly forested area
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Edité par CCSD -
International audience. Evaluation of current and future Synthetic Aperture Radar (SAR) data to extract forest attributes over various sites is needed. This study focuses on hilly forested man-managed pine plantation for which the estimation of height is of primary importance. Indeed this parameter is a good indicator of the forest productivity i.e. rate of growth. Furthermore it may be used to observe how forests react to their changing environment. ERS (European Remote Sensing Satellite) differential interferogram offers a great potentiality for the retrieval of such parameters. However these data may be affected by different sources of errors. In this study a simple additive model to analyze the error on the estimation of forest height is first proposed. Next, the measured and interferometric-derived height are compared. The results show a low correlation associated with high error. The error analysis shows a good agreement between predicted and observed value especially for the residual relative height. From there, it appears that the main source of error comes from the Digital Elevation Model (DEM) uncertainty and particularly for area under forest cover. A numerical study based on the model of error shows that a low level of coherence – deccorelation effect – may be considerable. Moreover, a systematic error is related to the fact that the scattering center of the layer is not the top of the canopy. Finally, the results indicate that 1) to date, differential interferometry is far from an operational use for forest height retrieval over hilly terrain, 2) even if the total error is a mixture of various sources deccorelation as well as penetration depth effects may be strongly reduced and 3) toward application purpose, a decrease on the DEM uncertainty is needed.
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