SAR imagery to estimate roughness parameters when modelling runoff risk - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue International Journal of Remote Sensing Année : 1999

SAR imagery to estimate roughness parameters when modelling runoff risk

Résumé

The influence of the roughness of agricultural soil on runoff and erosion is a proven fact. Synthetic aperture radar (SAR) sensors should enable discrimination between plots with different cropping patterns. A study of Mediterranean vineyards in southern France was made, with the aim of obtaining a better understanding of the potential for using radar satellite data from ERS-1 when estimating roughness parameters. Roughness measurements enabled modelling of the backscattering coefficient (s°) of known surfaces, using the electromagnetic Integral Equation Model (IEM). The good correlation between ERS-1 and IEM data indicated the feasability of extracting roughness parameters by means of remote sensing methods. Seven ERS-1 images were examined, corresponding to different stages in the development of vegetation and roughness. Two images were finally selected as they offered the possibility of discriminating between two factors : (1) the orientation of mechanical labour, which can be related to a periodic and stable roughness over time, and (2) cropping practices, corresponding to a random roughness pattern that changes with season. Both roughness parameters derived from SAR satellite data contribute additional data to runoff models - a preferred runoff direction as defined by furrow direction, as well as the intensity of this runoff under the influence of random roughness. A rule for the behaviour of s° in terms of furrow orientation is presented.

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Dates et versions

hal-02578618 , version 1 (14-05-2020)

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Citer

A. Rémond, Amélie Beaudoin, Christine King. SAR imagery to estimate roughness parameters when modelling runoff risk. International Journal of Remote Sensing, 1999, 20 (13), pp.2613-2625. ⟨hal-02578618⟩
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