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

Prévot, Laurent; Champion, Isabelle; Guyot, G.

doi:10.1016/0034-4257(93)90053-z

Cited by 202 publications

(125 citation statements)

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“…However, despite the average development of the vegetation, it will not be accounted for in this study, as the effect of the vegetation was minimised given the low incidence angles (swath modes S1 and S2) and the HH polarisation of the RADARSAT acquisitions (Biftu and Gan, 1999). This negligible effect could be verified through application of a water cloud model (Attema and Ulaby, 1978;Prévot et al, 1993), using leaf area index (LAI) and vegetation water content (VWC) as bulk canopy parameters. For LAI and VWC respectively ranging from 2.149 to 3.711 and 0.661 to 1.317 kgm −2 , the attenuation of the backscatter through the canopy was compensated to a large extent by a direct vegetation contribution, leading to insignificant vegetation corrections within the relative radiometric accuracy of the RADARSAT observations, i.e.…”

Section: Study Sites and Datamentioning

confidence: 99%

Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR

Lievens

Verhoest

Keyser

et al. 2011

Hydrol. Earth Syst. Sci.

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Abstract. Soil moisture retrieval from Synthetic Aperture Radar (SAR) using state-of-the-art backscatter models is not fully operational at present, mainly due to difficulties involved in the parameterisation of soil surface roughness. Recently, increasing interest has been drawn to the use of calibrated or effective roughness parameters, as they circumvent issues known to the parameterisation of fieldmeasured roughness. This paper analyses effective roughness parameters derived from C-and L-band SAR observations over a large number of agricultural seedbed sites in Europe. It shows that parameters may largely differ between SAR acquisitions, as they are related to the observed backscatter coefficients and variations in the local incidence angle. Therefore, a statistical model is developed that allows for estimating effective roughness parameters from microwave backscatter observations. Subsequently, these parameters can be propagated through the Integral Equation Model (IEM) for soil moisture retrieval. It is shown that fairly accurate soil moisture results are obtained both at Cand L-band, with an RMSE ranging between 4 vol% and 6.5 vol%.

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Section: Study Sites and Datamentioning

confidence: 99%

Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR

Lievens

Verhoest

Keyser

et al. 2011

Hydrol. Earth Syst. Sci.

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“…According to the model, the total backscatter at a co-polarised channel qq (σ°q q ), is the incoherent sum of the contribution from the vegetation (σ°v eg ) and the soil (σ°s oil ), and the two way attenuation of the vegetation layer (τ 2 ). For a given incidence angle, the co-polarised backscatter can be given by: The water cloud model has been modified and implemented differently by various authors [108][109][110][111] and despite its inconsistency during model implementation, it has found widespread use among the radar modelling community [112] with varying results. Dabrowska-Zielinska et al [113] found the soil moisture contribution to the backscattering coefficient to be predominant over that from the vegetation for C-band, θ = 23 o , while for L-band θ = 35 o , the backscattering coefficient was more sensitive to the vegetation contribution.…”

Section: Soil Moisture Retrieval Using Semi-empirical Scattering Modelsmentioning

confidence: 99%

Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques

2009

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Abstract:The importance of land surface-atmosphere interactions, principally the effects of soil moisture, on hydrological, meteorological, and ecological processes has gained widespread recognition over recent decades. Its high spatial and temporal variability however, makes soil moisture a difficult parameter to measure and monitor effectively using traditional methods. Microwave remote sensing technology has demonstrated the potential to map and monitor relative soil moisture changes over large areas at regular intervals in time and also the opportunity of measuring, through inverse modelling, absolute soil moisture values. This ability has been demonstrated under a variety of topographic and land cover conditions using both active and passive microwave instruments. The purpose of this paper is to review the current status of soil moisture determination from active microwave remote sensing systems and to highlight the key areas of research that will have to be addressed to achieve routine use of the proposed retrieval approaches.

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“…In copolarized power scattered, the internal soil-vegetation interactions is not a dominating factor and thus can be neglected [Dobson et al, 1986] [Prevot et al, 1993a]. Many modifications to the model have been reported [Ulaby et al, 1982] [Bindlish et al, 2001].…”

Section: The Water Cloud Model For Vegetationmentioning

confidence: 99%

“…V 1 is a description of the canopy, and V 2 is a second description of the canopy. These two parameters describe the effect of canopy geometry and water content on the backscatter coefficient, and because an important part of the scattering and attenuation is controlled by the leaves, many studies [Lievens et al, 2011] [Moran et al, 1998] [Prevot et al, 1993a] propose using the LAI (kg m−2) as the canopy descriptor.…”

Section: The Water Cloud Model For Vegetationmentioning

confidence: 99%

Estimation of Physical Parameters of a Multilayered Multi-Scale Vegetated Surface

Hosni

Farah

Naceur

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VI/4 KEY WORDS: moisture, estimating, synergistic methodology, WCM, backscattering, vegetation. ABSTRACT:Soil moisture is important to enable the growth of vegetation in the way that it also conditions the development of plant population. Additionally, its assessment is important in hydrology and agronomy, and is a warning parameter for desertification. Furthermore, the soil moisture content affects exchanges with the atmosphere via the energy balance at the soil surface; it is significant due to its impact on soil evaporation and transpiration. Therefore, it conditions the energy transfer between Earth and atmosphere.Many remote sensing methods were tested. For the soil moisture; the first methods relied on the optical domain (short wavelengths). Obviously, due to atmospheric effects and the presence of clouds and vegetation cover, this approach is doomed to fail in most cases. Therefore, the presence of vegetation canopy complicates the retrieval of soil moisture because the canopy contains moisture of its own. This paper presents a synergistic methodology of SAR and optical remote sensing data, and it's for simulation of statistical parameters of soil from C-band radar measurements. Vegetation coverage, which can be easily estimated from optical data, was combined in the backscattering model. The total backscattering was divided into the amount attributed to areas covered with vegetation and that attributed to areas of bare soil. Backscattering coefficients were simulated using the established backscattering model. A two-dimensional multiscale SPM model has been employed to investigate the problem of electromagnetic scattering from an underlying soil. The water cloud model (WCM) is used to account for the effect of vegetation water content on radar backscatter data, whereof to eliminate the impact of vegetation layer and isolate the contributions of vegetation scattering and absorption from the total backscattering coefficient.

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

Cited by 202 publications

References 22 publications

Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR

Effective roughness modelling as a tool for soil moisture retrieval from C- and L-band SAR

Soil Moisture Retrieval from Active Spaceborne Microwave Observations: An Evaluation of Current Techniques

Estimation of Physical Parameters of a Multilayered Multi-Scale Vegetated Surface

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