Quantification of the effect of wind driven wheat motion on SAR interferometric coherence

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2000-10

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Cranfield University

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School of Engineering, College of Aeronautics

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Thesis or dissertation

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Abstract

This report quantifies the motion of wheat subject to wind and assesses the effect of this motion on the coherence obtained from Synthetic Aperture Radar (SAR) interferometry. Over vegetation, the loss of coherence due to the change in backscatter between two SAR images taken at a different time (temporal decorrelation) is related to the wind induced motion of vegetation elements. The research aims to provide simultaneous in situ measurements of crop motion and wind velocity at canopy height and to use these measurements in a coherence model to determine the quantitatively the parameters which infer temporal decorrelation. The potential of coherence for agricultural applications is assessed. The three-dimensional motion of wheat is measured by a photogrammetry method using two commercially available video cameras. Simultaneously, wind velocity at canopy height is measured by anemometers at a high sampling frequency. Wheat motion and wind velocity data were collected in a field local to Cranfield University in summer 2000. The CD attached to this report contains the wheat motion and wind velocity data. They show that the motion of wheat is correlated with the wind speed, and that wheat plants adjacent to each other move coherently. The coherence model is based on a statistical approach, which represents the total backscatter from vegetation as the phasor addition of a fixed component and one or more components which are weather dependent. The relative contributions of the total backscatter are estimated with the RT2 backscatter intensity model. The motion measurements are used to define the variability of the phase of the weather dependent components in the model. Outputs of the model show that a C-band SAR with an incidence angle of 23° (typical configuration of the ERS satellites) yields coherence values highly variable with the wind conditions at the time of the radar passes. The potential use of coherence for agricultural applications is limited by this variability, which infers the need for an accurate coherent backscatter model.

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