MODELING THE IMPACT OF TEMPORAL DECORRELATION ON INSAR GROUND CANCELLATION TECHNIQUES IN THE FRAME OF TROPICAL FOREST CHARACTERIZATION AT P BAND - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

MODELING THE IMPACT OF TEMPORAL DECORRELATION ON INSAR GROUND CANCELLATION TECHNIQUES IN THE FRAME OF TROPICAL FOREST CHARACTERIZATION AT P BAND

Résumé

3-D imaging using SAR tomography is a well-recognized technique for the characterization of forested areas. Studies revealed that the intensity of radar echoes originating from specific locations within the canopy of forest could be used to estimate its above ground biomass. Moreover, a recent work proposed an estimation technique using a pair of interferometric SAR images only. The images are combined in order to cancel contributions from the ground, and to roughly estimate the volume reflectivity. This paper proposes to study the influence of temporal decorrelation of this minimalist approach, which relies on the hypothesis of perfectly correlated signals. A model, based on second order statistics, is proposed and is used to predict the influence of temporal decorrelation of the relative error of the above ground biomass estimation over tropical forests measured at P band.
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Dates et versions

hal-04087003 , version 1 (02-05-2023)

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Citer

L. Ferro-Famil, M. Mariotti d'Alessandro, S. Tebaldini, Y. Huang. MODELING THE IMPACT OF TEMPORAL DECORRELATION ON INSAR GROUND CANCELLATION TECHNIQUES IN THE FRAME OF TROPICAL FOREST CHARACTERIZATION AT P BAND. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2022, Kuala Lumpur, Malaysia. ⟨10.1109/IGARSS46834.2022.9884243⟩. ⟨hal-04087003⟩
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