Surface soil humidity retrieval by means of a semi-empirical coupled SAR model

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Abstract

In the last years, the availability of new technologies of Earth Observation encouraged researches to use integratedapproaches for environmental monitoring. Even for agro-hydrological applications, remotely sensed data are available onwide areas allowing the retrieval of cost-effective and representative estimation of high spatial and temporal variabilityof the soil-vegetation system variables. In particular, soil water content plays an important role determining the partitionof precipitation between surface runoff and infiltration and, moreover, influences the distribution of the incomingradiation between latent and sensible heat flux. As a consequence, distributed soil water content maps are essential datafor watershed applications such as flood prediction and crop irrigation scheduling. Since cloud cover has beenhighlighted as the main limitation of SW/TIR traditional techniques, this research is focused on the applicability of soilmoisture models based on active microwave. In particular, a Semi Empirical Coupled Model (SECM) is proposed.Reliable assessments of both surface roughness and dielectric constant (thus soil moisture) are retrieved by means of twoiterative modules, without any calibration phase. The validation with in situ soil moisture, taken at a depth comparable tothe RADAR penetration, gives a good agreement for bare-sparse vegetation coverage. The research is carried out on the24 km² test-site of DEMMIN (Görmin farm, Mecklenburg Vorpommern), in the North-East of Germany. Data wereacquired within the ESA-funded AgriSAR project, between April and July 2006. The implemented model uses HH, VVand HV polarized L-bands, acquired by the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt -DLR) using an airborne platform.
Original languageEnglish
Pages1-8
Number of pages8
Publication statusPublished - 2010

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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