Retrieving surface soil moisture over a wheat field: Comparison of different methods

Pardé, Mickaël; Wigneron, Jean‐Pierre; Chanzy, André; Waldteufel, Philippe; Kerr, Yann H.; Huet, Sylvie

doi:10.1016/j.rse.2003.08.002

Cited by 22 publications

(16 citation statements)

References 30 publications

(44 reference statements)

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“…Despite our simulation parameters are very stringent, our analysis [ Fig. 6(a)-(f)] confirm previously reported results [20], and retrievals with experimental L-band radiometric data [21], that have formulated the retrieval process in terms of and over the earth's surface. From this analysis, the following conclusions can be summarized.…”

Section: B Soil Moisture Retrievalssupporting

confidence: 86%

See 1 more Smart Citation

Performance of sea surface salinity and soil moisture retrieval algorithms with different auxiliary datasets in 2-D L-band aperture synthesis interferometric radiometers

Camps

Vall-llossera

Duffo

et al. 2005

IEEE Trans. Geosci. Remote Sensing

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Abstract-The Soil Moisture and Ocean Salinity (SMOS) EarthExplorer Opportunity Mission was selected in May 1999 by the European Space Agency Earth Observation Programme Board to provide global and frequent soil moisture (SM) and sea surface salinity (SSS) maps. SMOS' single payload is the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS) sensor, an L-band two-dimensional aperture synthesis interferometric radiometer with multiangular and polarimetric imaging capabilities. The definition of the SMOS Level 2 Processor requires the selection of the optimum operation mode (dual-polarization or full-polarimetric) for each application, the specification of the required auxiliary data, and the optimum retrieval algorithms. Using the SMOS simulator and based on the experience gained in previous works, this paper presents a study of the SM and SSS retrieval capabilities over homogeneous pixels, in the two modes of operation with different auxiliary data. It is found that SSS retrievals using the first Stokes parameter measured in the dual-polarization mode perform somewhat worse than using the vertical ( vv ) and horizontal ( hh ) brightness temperatures measured in the full-polarimetric mode, and the performance degrades for cold waters due to the lower sensitivity of the brightness temperature to SSS at low sea surface temperature (SST). Due to the larger angular variation of hh and vv , SM retrievals using hh and vv measured in the full-polarimetric mode exhibit a significant better performance over bare soils than over vegetation-covered soils. Over vegetation-covered soils vegetation parameters (opacity and albedo) can be inferred over a 550-km swath width in the full-polarimetric mode. However, since the first Stokes parameter is independent of both geometric and Faraday rotations, it is very robust in the presence of instrumental and geophysical errors. In the SSS retrieval problem and in the SM retrieval problem (with hh and vv measured in the full-polarimetric mode), the performance of the retrieval algorithms tested is not significantly altered if the model parameters are not exactly known, but are left as adjustable parameters in the optimization process.

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Section: B Soil Moisture Retrievalssupporting

confidence: 86%

“…4, for different soil moisture conditions), and additionally, the SM required accuracy is not as critical as in the SSS retrieval problem. The brightness temperature model used in the simulations is the model, as used in the multiangular and dual-polarization soil moisture retrievals presented in [20] and [21] …”

Section: B Soil Moisture Retrievalsmentioning

confidence: 99%

Performance of sea surface salinity and soil moisture retrieval algorithms with different auxiliary datasets in 2-D L-band aperture synthesis interferometric radiometers

Camps

Vall-llossera

Duffo

et al. 2005

IEEE Trans. Geosci. Remote Sensing

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“…The contribution of the albedo is considered directly in the brightness temperature model (4) where is the reflection coefficient defined in (1), is the vegetation temperature, is the soil temperature (an effective temperature has been computed from the soil temperature registered at different depths, see Section II-B), stands for the polarization (horizontal or vertical), and is the reflection coefficient due to the canopy layer, which is usually very small and can be neglected, so (4) can be written as (5) Some studies demonstrate that crops with vertical architecture (such as wheat) have an optical depth dependent on the polarization [12], but no study was found about vineyards. In this study, various dependences for albedo and opacity have been analyzed, obtaining the best results when the albedo and the opacity are assumed to be independent on the polarization.…”

Section: A Direct Modelmentioning

confidence: 99%

SMOS REFLEX 2003: L-band emissivity characterization of vineyards

Vall-llossera

Camps

Corbella

et al. 2005

IEEE Trans. Geosci. Remote Sensing

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Abstract-The goal of the Soil Moisture and Ocean Salinity mission over land is to infer surface soil moisture from multiangular L-band radiometric measurements. As the canopy affects the microwave emission of land, it is necessary to characterize different vegetation layers. This paper presents the Reference Pixel L-Band Experiment (REFLEX), carried out in June-July 2003 at the València Anchor Station, Spain, to study the effects of grapevines on the soil emission and on the soil moisture retrieval. A wide range of soil moisture (SM), from saturated to completely dry soil, was measured with the Universitat Politècnica de Catalunya's L-band Automatic Radiometer (LAURA). Concurrently with the radiometric measurements, the gravimetric soil moisture, temperature, and roughness were measured, and the vines were fully characterized. The opacity and albedo of the vineyard have been estimated and found to be independent on the polarization. The -model has been used to retrieve the SM and the vegetation parameters, obtaining a good accuracy for incidence angles up to 55 . Algorithms with a three-parameter optimization (SM, albedo albedo, and opacity) exhibit a better performance than those with one-parameter optimization (SM).Index Terms-L-band microwave radiometry, soil moisture, vineyards.

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“…Comparing the brightness temperature differences () to soil moisture (93 K), relative sensitivities were obtained. The range of maximum and minimum values and the base values of parameters (Table 3) were adopted from different publications [11,14,[20][21][22][23]. According to the investigation of other researchers the base values for vegetation water content (0.7), b-factor (0.1), and soil roughness (0.1) are not close to the arithmetic mean of the range because they are not normally distributed [2,11].…”

Section: Relative Sensitivity Analysismentioning

confidence: 99%

Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

2010

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Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS) and measured field soil moisture from Southern Great Plains experiment (SGP99). The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP) mission.

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Retrieving surface soil moisture over a wheat field: Comparison of different methods

Cited by 22 publications

References 30 publications

Performance of sea surface salinity and soil moisture retrieval algorithms with different auxiliary datasets in 2-D L-band aperture synthesis interferometric radiometers

Performance of sea surface salinity and soil moisture retrieval algorithms with different auxiliary datasets in 2-D L-band aperture synthesis interferometric radiometers

SMOS REFLEX 2003: L-band emissivity characterization of vineyards

Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

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