Mr. Atef A. E. Amriche Profile

Atef A. E. Amriche

Engineer in Agronomy at INSID

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Author

Area of Expertise:

Soil science , Remote sensing , physical soil properties (structure stability) , Semiarid regions

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Proceedings Article | 23 October 2012 Paper

Soil moisture monitoring over a semiarid region using Envisat ASAR data

Atef A. Amriche, Mokhtar Guerfi

Proceedings Volume 8531, 85311N (2012) https://doi.org/10.1117/12.974526

KEYWORDS: Soil science, Agriculture, Radar, Backscatter, Synthetic aperture radar, Vegetation, Surface roughness, Climatology, Image filtering, Data modeling

Read Abstract +

Soil moisture (SM) is of fundamental importance to many agricultural, hydrological and climate studies. In this paper, a simple approach for mapping near-surface SM from Envisat ASAR data was developed. Four high-resolution images covering a semiarid region in Algeria were acquired with the same sensor configuration. We performed the pretreatment using the Basic Envisat SAR Toolbox of the European Space Agency. Then, we extracted the backscattering coefficient σ⁰ (dB) from the filtered and calibrated images. On the other hand, five training sites with different soil physical properties and vegetation cover were selected for monitoring SM. The field campaigns were conducted concurrent to satellite image acquisitions to measure soil water content in the top five centimeters using the gravimetric method. The study of linear regressions associated to the change detection approach allowed the expression of the backscattering coefficient as a function of volumetric soil moisture (σ⁰ = a*θ + b). The coefficients “a” and “b” of the equation slightly differ from one site to another and also from one season to the next. This difference is mainly due to the effects of surface roughness and vegetation biomass variations. Our study confirms a good agreement between the volumetric nearsurface SM and the radar backscattering coefficient for all the test fields. The comparison between measured and estimated SM proves the accuracy of the inversion models used here with a mean average error of less than 5%. At the end, high resolution maps of soil moisture distribution were obtained from the acquired radar images.

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