Soil moisture estimation using multi linear regression with terraSAR-X data


  • G. García Universidad Nacional del Litoral; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
  • M. Brogioni Consiglio Nazionale delle Ricerche (CNR)
  • V. Venturini Universidad Nacional del Litoral
  • L. Rodriguez Universidad Nacional del Litoral
  • G. Fontanelli Consiglio Nazionale delle Ricerche (CNR)
  • E. Walker Universidad Nacional del Litoral
  • S. Graciani Universidad Nacional del Litoral
  • G. Macelloni Consiglio Nazionale delle Ricerche (CNR)



soil moisture, multiple regression, TerraSAR-X


The first five centimeters of soil form an interface where the main heat fluxes exchanges between the land surface and the atmosphere occur. Besides ground measurements, remote sensing has proven to be an excellent tool for the monitoring of spatial and temporal distributed data of the most relevant Earth surface parameters including soil’s parameters. Indeed, active microwave sensors (Synthetic Aperture Radar - SAR) offer the opportunity to monitor soil moisture (HS) at global, regional and local scales by monitoring involved processes. Several inversion algorithms, that derive geophysical information as HS from SAR data, were developed. Many of them use electromagnetic models for simulating the backscattering coefficient and are based on statistical techniques, such as neural networks, inversion methods and regression models. Recent studies have shown that simple multiple regression techniques yield satisfactory results. The involved geophysical variables in these methodologies are descriptive of the soil structure, microwave characteristics and land use. Therefore, in this paper we aim at developing a multiple linear regression model to estimate HS on flat agricultural regions using TerraSAR-X satellite data and data from a ground weather station. The results show that the backscatter, the precipitation and the relative humidity are the explanatory variables of HS. The results obtained presented a RMSE of 5.4 and a R2  of about 0.6


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Author Biographies

G. García, Universidad Nacional del Litoral; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)

Centro de Estudios Hidro-Ambientales

Facultad de Ingeniería y Ciencias Hídricas

M. Brogioni, Consiglio Nazionale delle Ricerche (CNR)

Consiglio Nazionale delle Ricerche (CNR) – Istituto di Fisica Applicata “N. Carrara” (IFAC)

V. Venturini, Universidad Nacional del Litoral

Centro de Estudios Hidro-Ambientales

Facultad de Ingeniería y Ciencias Hídricas (FICH)

L. Rodriguez, Universidad Nacional del Litoral

Centro de Estudios Hidro-Ambientales

Facultad de Ingeniería y Ciencias Hídricas (FICH)

G. Fontanelli, Consiglio Nazionale delle Ricerche (CNR)

Consiglio Nazionale delle Ricerche (CNR) – Istituto di Fisica Applicata “N. Carrara” (IFAC)

E. Walker, Universidad Nacional del Litoral

Centro de Estudios Hidro-Ambientales

Facultad de Ingeniería y Ciencias Hídricas (FICH)

S. Graciani, Universidad Nacional del Litoral

Facultad de Ingeniería y Ciencias Hídricas (FICH)

G. Macelloni, Consiglio Nazionale delle Ricerche (CNR)

Consiglio Nazionale delle Ricerche (CNR) – Istituto di Fisica Applicata “N. Carrara” (IFAC)


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