Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS &amp; SMAP soil moisture retrieval algorithms

Wigneron, Jean‐Pierre; Jackson, Thomas J.; O'Neill, Peggy E.; Lannoy, Gabriëlle De; Rosnay, Patricia de; Walker, Jeffrey P.; Ferrazzoli, P.; Миронов, В. Л.; Bircher, Simone; Grant, Jennifer; Kurum, Mehmet; Schwank, Mike; Muñoz-Sabater, Joaquín; Das, N.; Royer, A.; Al-Yaari, Amen; Bitar, Ahmad Al; Fernandez-Morán, Roberto; Lawrence, Heather; Mialon, Arnaud; Parrens, Marie; Richaume, Philippe; Delwart, Steven; Kerr, Yann H.

doi:10.1016/j.rse.2017.01.024

Cited by 397 publications

(267 citation statements)

References 164 publications

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“…Inversion for the soil roughness parameter HR from 10 radiometer measurements above the soil-only setup (Step 2 of the layer experiment, see Figure 4) gave a value of 0.49, which corresponds to a standard deviation of the surface height σR of 0.012 m based on the formulation proposed by Choudhury et al [34] or a σR of 0.013 m if we used the formulation of Wigneron et al [12]. It should be noted that the inversion was performed in a large parameter space (0 < HR < 1), which ensured finding the global optimum.…”

Section: Soil Roughness Parametermentioning

confidence: 96%

“…To limit the number of parameters to be retrieved simultaneously as only two TB S,p data (TB S,H and TB S,V ) were available for each time step (i.e., every 15 min), a two-step inversion approach was used. Values of the parameters ω H and ω V were first assumed to be in the range 0-0.2 as proposed in [12]. For each possible combination of ω H and ω V in that range (i.e., 21 × 21 combinations considering a step of 0.01 for the ω values), only τ and ε r were derived for all time steps.…”

Section: Radiative Transfer Modelmentioning

confidence: 99%

“…Many researchers have already investigated the effect of soil surface roughness on microwave signals [11,12]. During recent years, the effect of soil organic matter on passive L-band microwave signals has also been studied in the context of the ESA SMOSHiLat project [13].…”

Section: Introductionmentioning

confidence: 99%

“…During recent years, the effect of soil organic matter on passive L-band microwave signals has also been studied in the context of the ESA SMOSHiLat project [13]. L-band radiometer algorithms for soil moisture retrieval are based on the use of a radiative transfer (RT) model [12,14,15] and a dielectric mixing model [16][17][18] to derive soil moisture information from brightness temperature observations. The listed dielectric mixing models were developed for mineral soils and no information on organic matter content can be accounted for.…”

Section: Introductionmentioning

confidence: 99%

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Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

et al. 2018

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Organic soils play a key role in global warming because they store large amount of soil carbon which might be degraded with changing soil temperatures or soil water contents. There is thus a strong need to monitor these soils and, in particular, their hydrological characteristics using, for instance, space-borne L-band brightness temperature observations. However, there are still open issues with respect to soil moisture retrieval techniques over organic soils. In view of this, organic soil blocks with their vegetation cover were collected from a heathland in the Skjern River catchment in western Denmark and then transported to a remote sensing field laboratory in Germany where their structure was reconstituted. The controlled conditions at this field laboratory made it possible to perform tower-based L-band radiometer measurements of the soils over a period of two months. Brightness temperature data were inverted using a radiative transfer (RT) model for estimating the time variations in the soil dielectric permittivity and the vegetation optical depth. In addition, the effective vegetation scattering albedo parameter of the RT model was retrieved based on a two-step inversion approach. The remote estimations of the dielectric permittivity were compared to in situ measurements. The results indicated that the radiometer-derived dielectric permittivities were significantly correlated with the in situ measurements, but their values were systematically lower compared to the in situ ones. This could be explained by the difference between the operating frequency of the L-band radiometer (1.4 GHz) and that of the in situ sensors (70 MHz). The effective vegetation scattering albedo parameter was found to be polarization dependent. While the scattering effect within the vegetation could be neglected at horizontal polarization, it was found to be important at vertical polarization. The vegetation optical depth estimated values over time oscillated between 0.10 and 0.19 with a mean value of 0.13. This study provides further insights into the characterization of the L-band brightness temperature signatures of organic soil surface layers and, in particular, into the parametrization of the RT model for these specific soils. Therefore, the results of this study are expected to improve the performance of space-borne remote sensing soil moisture products over areas dominated by organic soils.

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Section: Soil Roughness Parametermentioning

confidence: 96%

Section: Radiative Transfer Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

et al. 2018

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“…This algorithm uses a forced VOD in a single-orbit configuration. Miernecki et al (2014) and Wigneron et al (2017) presented a review and a comparison of the different retrieval approaches for L-band microwave from EO missions (SMOS, SMAP and AQUARIUS).…”

Section: Introductionmentioning

confidence: 99%

The global SMOS Level 3 daily soil moisture and brightness temperature maps

Bitar

Mialon

Kerr

et al. 2017

Earth Syst. Sci. Data

191

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Abstract. The objective of this paper is to present the multi-orbit (MO) surface soil moisture (SM) and anglebinned brightness temperature (TB) products for the SMOS (Soil Moisture and Ocean Salinity) mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS) makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD) compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD) using multi-angular dual-polarisation TB from MO. A subsidiary anglebinned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive) TB. The Level 3 SM V300 product is compared to the single-orbit (SO) retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM) are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an open licence and free of charge using a web application

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Assessment of SMAP soil moisture for global simulation of gross primary production

Chen

Liu

et al. 2017

J. Geophys. Res. Biogeosci.

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In this study, high‐quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process‐based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun‐induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment‐2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p < 0.05). Significant improvement in r appears in single‐cropping agricultural land where the irrigation is not considered in the model but well captured by SMAP (e.g., 0.09 in North America, p < 0.05). With the assimilation of SMAP, areas with weak model performances are identified in double or triple cropping cropland (e.g., part of North China Plain) and/or mountainous area (e.g., Spain and Turkey). The correlation coefficient is enhanced by 0.01 in global average for shrub, grass, and cropland. This enhancement is small and insignificant because nonwater‐stressed areas are included.

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Modelling the passive microwave signature from land surfaces: A review of recent results and application to the L-band SMOS & SMAP soil moisture retrieval algorithms

Cited by 397 publications

References 164 publications

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

The global SMOS Level 3 daily soil moisture and brightness temperature maps

Assessment of SMAP soil moisture for global simulation of gross primary production

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