Improved Understanding of Soil Surface Roughness Parameterization for L-Band Passive Microwave Soil Moisture Retrieval

Passive microwave remote sensing is one of the most effective methods for inversing soil moisture. Under the condition of laboratory, firstly, C band microwave radiation was used to achieve the trial of ground-based remote sensing soil moisture, and then regression analysis was carried out according to the data measured, finally, got the C band experience regression model of soil moisture inversion. The results showed that: in the level-off state of soil surface, soil humidity and soil microwave emission rate is linear negative correlation, in the other words, soil microwave emission rate decreased while the soil moisture increased. Besides, with the increasing of soil surface roughness, both the value of microwave polarization index (MPDI) and microwave emission rate polarization difference Δe have the same trend of quick drop, stabilization and slow raise, and it presented the relationship of quadratic curve with the change of roughness.

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

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-4995-2010 ◽

2010 ◽

Vol 7 (4) ◽

pp. 4995-5031 ◽

Cited By ~ 4

Author(s):

H. Lievens ◽

N. E. C. Verhoest ◽

E. De Keyser ◽

H. Vernieuwe ◽

P. Matgen ◽

...

Keyword(s):

Soil Moisture ◽

State Of The Art ◽

Incidence Angle ◽

Soil Surface ◽

Equation Model ◽

Roughness Parameters ◽

Effective Roughness ◽

Soil Surface Roughness ◽

L Band ◽

Microwave Backscatter

Abstract. Soil moisture retrieval from Synthetic Aperture Radar (SAR) using state-of-the-art backscatter models is not yet 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 field-measured 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 and furthermore 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 the estimation of 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 C- and L-band, with an RMSE ranging between 4 vol% and 6.5 vol%.

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Retrieval of soil surface roughness from active and passive microwave observations

Piantadosi, J., Anderssen, R.S. and Boland J. (eds) MODSIM2013, 20th International Congress on Modelling and Simulation ◽

10.36334/modsim.2013.l19.gao ◽

2013 ◽

Keyword(s):

Surface Roughness ◽

Soil Surface ◽

Passive Microwave ◽

Soil Surface Roughness

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

Hydrology and Earth System Sciences ◽

10.5194/hess-15-151-2011 ◽

2011 ◽

Vol 15 (1) ◽

pp. 151-162 ◽

Cited By ~ 54

Author(s):

H. Lievens ◽

N. E. C. Verhoest ◽

E. De Keyser ◽

H. Vernieuwe ◽

P. Matgen ◽

...

Keyword(s):

Soil Moisture ◽

Incidence Angle ◽

Soil Surface ◽

Equation Model ◽

Roughness Parameters ◽

Effective Roughness ◽

Soil Surface Roughness ◽

L Band ◽

Microwave Backscatter ◽

Param Eters

Abstract. Soil moisture retrieval from Synthetic Aperture Radar (SAR) using state-of-the-art back\\-scatter 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 field-measured 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 param\\-eters 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 C- and L-band, with an RMSE ranging between 4 vol% and 6.5 vol%.

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An inversion method based on multi-angular approaches for estimating bare soil surface parameters from RADARSAT-1

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-6-207-2009 ◽

2009 ◽

Vol 6 (1) ◽

pp. 207-241 ◽

Cited By ~ 2

Author(s):

M. R. Sahebi ◽

J. Angles

Keyword(s):

Surface Roughness ◽

Dielectric Constant ◽

Soil Moisture ◽

Soil Surface ◽

Bare Soil ◽

Earth Observation ◽

Radar Signal ◽

Inversion Method ◽

Inversion Algorithm ◽

Soil Surface Roughness

Abstract. The radar signal recorded by earth observation (EO) satellites is known to be sensitive to soil moisture and soil surface roughness, which influence the onset of runoff. This paper focuses on the inversion of these parameters using a multi-angular approach based on RADARSAT-1 data with incidence angles of 35° and 47° (in mode S3 and S7). This inversion was done based on three backscatter models: Geometrical Optics Model (GOM), Oh Model (OM) and Modified Dubois Model (MDM), which are compared in order to obtain the best configuration. For roughness expressed in rms of heights, mean absolute errors of 1.23 cm, 1.12 cm and 2.08 cm, and for dielectric constant, mean absolute errors of 2.46, 4.95 and 3.31 were obtained for the MDM, GOM and the OM simulation, respectively. This means that the MDM provided the best results with minimum errors. Based on these results, the latter inversion algorithm was applied on the images and the final results are presented in two different maps showing pixel and homogeneous zones for surface roughness and soil moisture.

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Modelling of Microwave Multi-Frequency Emission and Backscatter by a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP)

10.5194/egusphere-egu21-6659 ◽

2021 ◽

Author(s):

Hong Zhao ◽

Yijian Zeng ◽

Bob Su ◽

Jan Hofste

Keyword(s):

Soil Moisture ◽

Radiative Transfer ◽

Microwave Radiometer ◽

Soil Surface ◽

Equation Model ◽

Passive Microwave ◽

The Tibetan Plateau ◽

Microwave Sensor ◽

L Band ◽

Transfer Modelling

Emission and backscattering at different frequencies have varied responses to soil physical processes (e.g., moisture redistribution, freeze-thaw) and vegetation growing/senescencing. Combing the use of active and passive microwave multi-frequency signals may provide complementary information, which can be used to better retrieve soil moisture, and vegetation biomass and water content for ecological applications. To this purpose, a Community Land Active Passive Microwave Radiative Transfer Modelling Platform (CLAP) was adopted in this study to simulate both emission (TB) and backscatter (&#963;0), in which the CLAP is backboned by the TorVergata model for modelling vegetation scattering, and an air-to-soil transition model (ATS) (accounting for surface dielectric roughness) integrated with the Advanced Integral Equation Model (AIEM) for modelling soil surface scattering. The accuracy of CLAP was assessed by both ground-based and spaceborne measurements, and the former was from the deployed microwave radiometer/scatterometer observatory at Maqu site on an alpine meadow over the Tibetan plateau. Specifically, for the passive case, simulated TB&#160;(emissivity multiplied by effective temperature) were compared to the ground-based ELBARA-III L-band observations, as well as C-band Advanced Microwave Scanning Radiometer 2 (AMSR2) and L-band Soil Moisture Active Passive (SMAP) observations. For the active case, simulated &#963;0 were compared to the ground-based scatterometer C- and L-bands observations, and C-band Sentinel and L-band Phased Array type L-band Synthetic Aperture Radar 2 (PALSAR-2) observations. This study is expected to contribute to improving the soil moisture retrieval accuracy for dedicated microwave sensor configurations.

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