Details

Autor(en) / Beteiligte

• Prévot, L.
• Champion, I.
• Guyot, G.

Titel

Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer

Ist Teil von

• Remote sensing of environment, 1993, Vol.46 (3), p.331-339

Ort / Verlag

Elsevier Inc

Erscheinungsjahr

1993

Quelle

Elsevier Journal Backfiles on ScienceDirect (DFG Nationallizenzen)

Beschreibungen/Notizen

• Since microwave remote sensing techniques are insensitive to cloud cover, they can overcome this strong limitation of optical remote sensing. As in the optical domain, their use for monitoring vegetation canopies requires the development of suitable inversion algorithms. These would allow the estimation of variables such as LAI from radar data. This article investigates the possible use of a semiempirical water-cloud model in an inversion scheme. Using radar data obtained with a ground-based dual-frequency (C and X bands, 5.7 and 3.3 cm wavelength, respectively) scatterometer on experimental winter wheat fields, it is first verified that a semiempirical water-cloud model can adequately simulate the backscattering coefficients obtained over the growing season, as a function of LAI and surface soil moisture. Then it is shown that the model can be numerically inverted. This yields simultaneous estimation of LAI and surface soil moisture, the standard deviations of the residuals being respectively 0.64 m 2 m −2 and 0.065 cm 3 cm −3. Finally, the influence of radar measurement errors on the inversion scheme is quantified by means of a simulation study. This shows that a 1 dB accuracy of the radar is required for a 1 m 2 m −2 precision of the estimated LAI.