ELBARA II, an L-Band Radiometer System for Soil Moisture Research

L-band (1–2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

The objective of this study was to compare several approaches to soil moisture (SM) retrieval using L-band microwave radiometry. The comparison was based on a brightness temperature (TB) data set acquired since 2010 by the L-band radiometer ELBARA-II over a vineyard field at the Valencia Anchor Station (VAS) site. ELBARA-II, provided by the European Space Agency (ESA) within the scientific program of the SMOS (Soil Moisture and Ocean Salinity) mission, measures multiangular TB data at horizontal and vertical polarization for a range of incidence angles (30-60). Based on a three year data set (2010-2012), several SM retrieval approaches developed for spaceborne missions including AMSR-E (Advanced Microwave Scanning Radiometer for EOS), SMAP (Soil Moisture Active Passive) and SMOS were compared. The approaches include: the Single Channel Algorithm (SCA) for horizontal (SCA-H) and vertical (SCA-V) polarizations, the Dual Channel Algorithm (DCA), the Land Parameter Retrieval Model (LPRM) and two simplified approaches based on statistical regressions (referred to as 'Mattar' and 'Saleh'). Time series of vegetation indices required for three of the algorithms (SCA-H, SCA-V and Mattar) were obtained from MODIS observations. The SM retrievals were evaluated against reference SM values estimated from a multiangular 2-Parameter inversion approach. The results obtained with the current base line algorithms developed for SMAP (SCA-H and -V) are in very good agreement with the reference SM data set derived from the multi-angular observations (R2 around 0.90, RMSE varying between 0.035 and 0.056 m3m3 for several retrieval configurations). This result showed that, provided the relationship between vegetation optical depth and a remotely-sensed vegetation index can be calibrated, the SCA algorithms can provide results very close to those obtained from multi-angular observations in this study area. The approaches based on statistical regressions provided similar results and the best accuracy was obtained with the Saleh methods based on either bi-angular or bipolarization observations (R2 around 0.93, RMSE around 0.035 m3m3). The LPRM and DCA algorithms were found to be slightly less successful in retrieving the 'reference' SM time series (R2 around 0.75, RMSE around 0.055 m3m3). However, the two above approaches have the great advantage of not requiring any model calibrations previous to the SM retrievals

Validación a largo plazo de datos de nivel 3 de tierra de SMOS con medidas de ELBARA-II en la Valencia Anchor Station

Revista oficial de la Asociación Española de Teledetección[EN] The Soil Moisture and Ocean Salinity (SMOS) mission was launched on 2nd November 2009 with the objective of providing global estimations of soil moisture and sea salinity. The main activity of the Valencia Anchor Station (VAS) is currently to assist in a long-term validation of SMOS land products. This study focus on a level 3 SMOS data validation with in situ measurements carried out in the period 2010-2012 over the VAS. ELBARA-II radiometer is placed in the VAS area, observing a vineyard field considered as representative of a major proportion of an area of 50×50 km, enough to cover a SMOS footprint. Brightness temperatures (TB) acquired by ELBARA-II have been compared to those observed by SMOS at the same dates and time. They were also used for the L-MEB model inversion to retrieve soil moisture (SM), which later on have been compared to those provided by SMOS as level 3 data. A good correlation between both TB datasets was found, improving year by year, mainly due to the decrease of precipitations in the analyzed period and the mitigation of radio frequency interferences at L-band. The larger homogeneity of the radiometer footprint as compared to SMOS explains the higher variability of its TB. Periods of more intense precipitation (spring and autumn) also presented higher SM, which corroborates the consistency of SM retrieved from ELBARA-II’s observations. However, the results show that SMOS level 3 data underestimate SM as compared to ELBARA-II’s, probably due to the influence of the small soil fraction which is not cultivated in vineyards. SMOS estimations in descending orbit (6 pm) had better quality (higher correlation, lower RMSE and bias) than the ones in ascending orbit (6 am, when there is a higher soil moisture). Guardar / Salir Siguiente >[ES] La misión de SMOS (Soil Moisture and Ocean Salinity) se lanzó el 2 de Noviembre de 2009 con el objetivo de proporcionar datos de humedad del suelo y salinidad del mar. La principal actividad de la conocida como Valencia Anchor Station(VAS) es asistir en la validación a largo plazo de productos de suelo de SMOS. El presente estudio se centra en una validación de datos de nivel 3 de SMOS en la VAS con medidas in situ tomadas en el periodo 2010-2012. El radiómetro ELBARA-II está situado dentro de los confines de la VAS, observando un campo de viñedos que se con-sidera representativo de una gran proporción de un área de 50×50 km, suficiente para cubrir un footprint de SMOS. Las temperaturas de brillo (TB) adquiridas por ELBARA-II se compararon con las observadas por SMOS en las mismas fechas y horas. También se utilizó la inversión del modelo L-MEB con el fin de obtener humedades de suelo (SM) que, posteriormente, se compararon con datos de nivel 3 de SMOS. Se ha encontrado una buena correlación entre ambas series de TB, con mejoras año tras año, achacable fundamentalmente a la disminución de precipitaciones en el perio-do objeto de estudio y a la mitigación de las interferencias por radiofrecuencia en banda L. La mayor homogeneidad del footprintdel radiómetro ELBARA-II frente al de SMOS explica la mayor variabilidad de sus TB. Los periodos de preci-pitación más intensa (primavera y otoño) también son de mayor SM, lo que corrobora la consistencia de los resultados de SM simulados a través de las observaciones del radiómetro. Sin embargo, se debe resaltar una subestimación por parte de SMOS de los valores de SM respecto a los obtenidos por ELBARA-II, presumiblemente debido a la influencia que la pequeña fracción de suelo no destinado al cultivo de la vid tiene sobre SMOS. Las estimaciones por parte de SMOS en órbita descendente (6 p.m.) resultaron de mayor calidad (mayor correlación y menores RMSE y bias) que en órbita ascendente (6 a.m., momento de mayor humedad de suelo).This work is carried out within the framework of the project MIDAS-7/UVEG Productos y Aplicaciones Avanzados de SMOS y Futuras Misiones (Parte UVEG) from the Spanish Research Programme on Space, Spanish Ministry for Economy and Competitiveness.Fernandez-Moran, R.; Wigneron, JP.; López-Baeza, E.; Miernecki, M.; Salgado-Hernanz, P.; Coll, M.; Kerr, YH.... (2015). Towards a long-term dataset of ELBARA-II measurements assisting SMOS level-3 land product and algorithm validation at the Valencia Anchor Station. Revista de Teledetección. (43):55-62. doi:10.4995/raet.2015.2297.SWORD55624

Soil freezing in northern aapa mires:freeze/thaw -detection using portable L-band radiometer

Abstract. Seasonal soil freezing is one of the most significant sources of uncertainty in methane emissions from high latitude wetlands. Although soil freezing can be remotely sensed with current satellite-based instruments, the resolution is not high enough to detect small-scale variations within individual mires. In this study, a lightweight radiometer mounted on an unmanned aerial vehicle (UAV) was tested for detecting the freeze/thaw (F/T) state of the soil in aapa mires in Finnish Lapland. The three main research questions were the suitability of the radiometer for high resolution F/T detection, the existence of possible spatial patterns in the timing of soil freezing, and the effects of environmental factors on these spatial patterns. As this was the first study to use a UAV-mounted radiometer for F/T detection, there was no established method for retrieving the F/T state of the soil from the measured brightness temperature values. In previous studies using satellite-based instruments, the F/T state of the soil is determined by a threshold method where the measured values are scaled pixel-wise between known reference values of thawed and frozen soils and classified based on a fixed threshold. This method was modified for use with UAV measurements. The performance of the radiometer was evaluated by comparing the measurement results with tower-based radiometer and in-situ measurements in the study area. Spatial patterns in the timing of soil freezing were investigated using analysis of variance and measures of spatial autocorrelation. The effects of environmental factors were investigated using generalized linear models (GLM), generalized additive models (GAM), and hierarchical partitioning with environmental variables derived from readily available remote sensing materials. The F/T state of the soil was successfully determined from the UAV measurements, and the results were comparable to those of other measurements in the study area. Variation in the spatial distribution of the timing of soil freezing was detected at the local scale. The soil appeared to freeze as a result of two separate major freezing events and was therefore modeled as a binary response variable. Both GLM and GAM showed that the most significant factors contributing to the spatial patterns were the Enhanced Vegetation Index (EVI), the flark area and the standard deviation of the Topographic Wetness Index (TWI). Hierarchical partitioning highlighted the individual effects of EVI. All detected relationships were strongly correlated with the microtopographic structure of the mire, suggesting that seasonal freezing progresses differently on different surface types

Coupled land surface and radiative transfer models for the analysis of passive microwave satellite observations

Soil moisture is one of the key variables controlling the water and energy exchanges between Earth’s surface and the atmosphere. Therefore, remote sensing based soil moisture information has potential applications in many disciplines. Besides numerical weather forecasting and climate research these include agriculture and hydrologic applications like flood and drought forecasting. The first satellite specifically designed to deliver operational soil moisture products, SMOS (Soil Moisture and Ocean Salinity), was launched 2009 by the European Space Agency (ESA). SMOS is a passive microwave radiometer working in the L-band of the microwave domain, corresponding to a frequency of roughly 1.4 GHz and relies on a new concept. The microwave radiation emitted by the Earth’s surface is measured as brightness temperatures in several look angles. A radiative transfer model is used in an inversion algorithm to retrieve soil moisture and vegetation optical depth, a measure for the vegetation attenuation of the soil’s microwave emission. For the application of passive microwave remote sensing products a proper validation and uncertainty assessment is essential. As these sensors have typical spatial resolutions in the order of 40 – 50 km, a validation that relies solely on ground measurements is costly and labour intensive. Here, environmental modelling can make a valuable contribution. Therefore the present thesis concentrates on the question which contribution coupled land surface and radiative transfer models can make to the validation and analysis of passive microwave remote sensing products. The objective is to study whether it is possible to explain known problems in the SMOS soil moisture products and to identify potential approaches to improve the data quality. The land surface model PROMET (PRocesses Of Mass and Energy Transfer) and the radiative transfer model L-MEB (L-band microwave emission of the Biosphere) are coupled to simulate land surface states, e.g. temperatures and soil moisture, and the resulting microwave emission. L-MEB is also used in the SMOS soil moisture processor to retrieve soil moisture and vegetation optical depth simultaneously from the measured microwave emission. The study area of this work is the Upper Danube Catchment, located mostly in Southern Germany. Since model validation is essential if model data are to be used as reference, both models are validated on different spatial scales with measurements. The uncertainties of the models are quantified. The root mean squared error between modelled and measured soil moisture at several measuring stations on the point scale is 0.065 m3/m3. On the SMOS scale it is 0.039 m3/m3. The correlation coefficient on the point scale is 0.84. As it is essential for the soil moisture retrieval from passive microwave data that the radiative transfer modelling works under local conditions, the coupled models are used to assess the radiative transfer modelling with L-MEB on the local and SMOS scales in the Upper Danube Catchment. In doing so, the emission characteristics of rape are described for the first time and the soil moisture retrieval abilities of L-MEB are assessed with a newly developed LMEB parameterization. The results show that the radiative transfer modelling works well under most conditions in the study area. The root mean squared error between modelled and airborne measured brightness temperatures on the SMOS scale is less than 6 – 9 K for the different look angles. The coupled models are used to analyse SMOS brightness temperatures and vegetation optical depth data in the Upper Danube Catchment in Southern Germany. Since the SMOS soil moisture products are degraded in Southern Germany and in different other parts of the world these analyses are used to narrow down possible reasons for this. The thorough analysis of SMOS brightness temperatures for the year 2011 reveals that the quality of the measurements is degraded like in the SMOS soil moisture product. This points towards radio frequency interference problems (RFI), that are known, but have not yet been studied thoroughly. This is consistent with the characteristics of the problems observed in the SMOS soil moisture products. In addition to that it is observed that the brightness temperatures in the lower look angles are less reliable. This finding could be used to improve the brightness temperature filtering before the soil moisture retrieval. An analysis of SMOS optical depth data in 2011 reveals that this parameter does not contain valuable information about vegetation. Instead, an unexpected correlation with SMOS soil moisture is found. This points towards problems with the SMOS soil moisture retrieval, possibly under the influence of RFI. The present thesis demonstrates that coupled land surface and radiative transfer models can make a valuable contribution to the validation and analysis of passive microwave remote sensing products. The unique approach of this work incorporates modelling with a high spatial and temporal resolution on different scales. This makes detailed process studies on the local scale as well as analyses of satellite data on the SMOS scale possible. This could be exploited for the validation of future satellite missions, e.g. SMAP (Soil Moisture Active and Passive) which is currently being prepared by NASA (National Aeronautics and Space Administration). Since RFI seems to have a considerable influence on the SMOS data due to the gained insights and the quality of the SMOS products is very good in other parts of the world, the RFI containment and mitigation efforts carried out since the launch of SMOS should be continued

Coupled land surface and radiative transfer models for the analysis of passive microwave satellite observations

Soil moisture is one of the key variables controlling the water and energy exchanges between Earth’s surface and the atmosphere. Therefore, remote sensing based soil moisture information has potential applications in many disciplines. Besides numerical weather forecasting and climate research these include agriculture and hydrologic applications like flood and drought forecasting. The first satellite specifically designed to deliver operational soil moisture products, SMOS (Soil Moisture and Ocean Salinity), was launched 2009 by the European Space Agency (ESA). SMOS is a passive microwave radiometer working in the L-band of the microwave domain, corresponding to a frequency of roughly 1.4 GHz and relies on a new concept. The microwave radiation emitted by the Earth’s surface is measured as brightness temperatures in several look angles. A radiative transfer model is used in an inversion algorithm to retrieve soil moisture and vegetation optical depth, a measure for the vegetation attenuation of the soil’s microwave emission. For the application of passive microwave remote sensing products a proper validation and uncertainty assessment is essential. As these sensors have typical spatial resolutions in the order of 40 – 50 km, a validation that relies solely on ground measurements is costly and labour intensive. Here, environmental modelling can make a valuable contribution. Therefore the present thesis concentrates on the question which contribution coupled land surface and radiative transfer models can make to the validation and analysis of passive microwave remote sensing products. The objective is to study whether it is possible to explain known problems in the SMOS soil moisture products and to identify potential approaches to improve the data quality. The land surface model PROMET (PRocesses Of Mass and Energy Transfer) and the radiative transfer model L-MEB (L-band microwave emission of the Biosphere) are coupled to simulate land surface states, e.g. temperatures and soil moisture, and the resulting microwave emission. L-MEB is also used in the SMOS soil moisture processor to retrieve soil moisture and vegetation optical depth simultaneously from the measured microwave emission. The study area of this work is the Upper Danube Catchment, located mostly in Southern Germany. Since model validation is essential if model data are to be used as reference, both models are validated on different spatial scales with measurements. The uncertainties of the models are quantified. The root mean squared error between modelled and measured soil moisture at several measuring stations on the point scale is 0.065 m3/m3. On the SMOS scale it is 0.039 m3/m3. The correlation coefficient on the point scale is 0.84. As it is essential for the soil moisture retrieval from passive microwave data that the radiative transfer modelling works under local conditions, the coupled models are used to assess the radiative transfer modelling with L-MEB on the local and SMOS scales in the Upper Danube Catchment. In doing so, the emission characteristics of rape are described for the first time and the soil moisture retrieval abilities of L-MEB are assessed with a newly developed LMEB parameterization. The results show that the radiative transfer modelling works well under most conditions in the study area. The root mean squared error between modelled and airborne measured brightness temperatures on the SMOS scale is less than 6 – 9 K for the different look angles. The coupled models are used to analyse SMOS brightness temperatures and vegetation optical depth data in the Upper Danube Catchment in Southern Germany. Since the SMOS soil moisture products are degraded in Southern Germany and in different other parts of the world these analyses are used to narrow down possible reasons for this. The thorough analysis of SMOS brightness temperatures for the year 2011 reveals that the quality of the measurements is degraded like in the SMOS soil moisture product. This points towards radio frequency interference problems (RFI), that are known, but have not yet been studied thoroughly. This is consistent with the characteristics of the problems observed in the SMOS soil moisture products. In addition to that it is observed that the brightness temperatures in the lower look angles are less reliable. This finding could be used to improve the brightness temperature filtering before the soil moisture retrieval. An analysis of SMOS optical depth data in 2011 reveals that this parameter does not contain valuable information about vegetation. Instead, an unexpected correlation with SMOS soil moisture is found. This points towards problems with the SMOS soil moisture retrieval, possibly under the influence of RFI. The present thesis demonstrates that coupled land surface and radiative transfer models can make a valuable contribution to the validation and analysis of passive microwave remote sensing products. The unique approach of this work incorporates modelling with a high spatial and temporal resolution on different scales. This makes detailed process studies on the local scale as well as analyses of satellite data on the SMOS scale possible. This could be exploited for the validation of future satellite missions, e.g. SMAP (Soil Moisture Active and Passive) which is currently being prepared by NASA (National Aeronautics and Space Administration). Since RFI seems to have a considerable influence on the SMOS data due to the gained insights and the quality of the SMOS products is very good in other parts of the world, the RFI containment and mitigation efforts carried out since the launch of SMOS should be continued

Monitoring Water and Energy Cycles at Climate Scale in the Third Pole Environment (CLIMATE-TPE)

A better understanding of the water and energy cycles at climate scale in the Third Pole Environment is essential for assessing and understanding the causes of changes in the cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and for predicting the possible changes in water resources in South and East Asia. This paper reports the following results: (1) A platform of in situ observation stations is briefly described for quantifying the interactions in hydrosphere-pedosphere-atmosphere-cryosphere-biosphere over the Tibetan Plateau. (2) A multiyear in situ L-Band microwave radiometry of land surface processes is used to develop a new microwave radiative transfer modeling system. This new system improves the modeling of brightness temperature in both horizontal and vertical polarization. (3) A multiyear (2001–2018) monthly terrestrial actual evapotranspiration and its spatial distribution on the Tibetan Plateau is generated using the surface energy balance system (SEBS) forced by a combination of meteorological and satellite data. (4) A comparison of four large scale soil moisture products to in situ measurements is presented. (5) The trajectory of water vapor transport in the canyon area of Southeast Tibet in different seasons is analyzed, and (6) the vertical water vapor exchange between the upper troposphere and the lower stratosphere in different seasons is presented

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

Emission and backscattering signals of land surfaces at different frequencies have distinctive responses to soil and vegetation physical states. The use of multi-frequency combined active and passive microwave signals provides complementary information to better understand and interpret the observed signals in relation to surface states and the underlying physical processes. Such a capability also improves our ability to retrieve surface parameters and states such as soil moisture, freeze-thaw dynamics and vegetation biomass and vegetation water content (VWC) for ecosystem monitoring. We present here a prototype Community Land Active Passive Microwave Radiative Transfer Modelling platform (CLAP) for simulating both backscatter (&sigma;0) and emission (TB) signals of land surfaces, in which the CLAP is backboned by 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, and the Tor Vergata model for modelling vegetation scattering and the interaction between vegetation and soil parts. The CLAP was used to simulate both ground-based and space-borne multi-frequency microwave measurements collected at the Maqu observatory on the eastern Tibetan plateau. The ground-based systems include a scatterometer system (1&ndash;10 GHz) and an L-band microwave radiometer. The space-borne measurements are obtained from the X-band and C-band Advanced Microwave Scanning Radiometer 2 (AMSR2) radiation observations. The impacts of different vegetation properties (i.e., structure, water and temperature dynamics) and soil conditions (i.e., different moisture and temperature profiles) on the microwave signals were investigated by CLAP simulation for understanding factors that can account for diurnal variations of the observed signals. The results show that the dynamic VWC partially accounts for the diurnal variation of the observed signal at the low frequencies (i.e., S- and L-bands), while the diurnal variation of the observed signals at high frequencies (i.e., X- and C-bands) is more due to vegetation temperature changing, which implies the necessity to first disentangle the impact of vegetation temperature for the use of high frequency microwave signals. The model derived vegetation optical depth &tau; differs in terms of frequencies and different model parameterizations, while its diurnal variation depends on the diurnal variation of VWC regardless of frequency. After normalizing &tau; at multi-frequency by wavenumber, difference is still observed among different frequencies. This indicates that &tau; is indeed frequency-dependent, and &tau; for each frequency is suggested to be applied in the retrieval of soil and vegetation parameters. Moreover, &tau; at different frequencies (e.g., X-band and L-band) cannot be simply combined for constructing accurate long time series microwave-based vegetation product. To this purpose, it is suggested to investigate the role of the leaf water potential in regulating plant water use and its impact on the normalized &tau; at multi-frequency. Overall, the CLAP is expected to improve our capability for understanding and applying current and future multi-frequency space-borne microwave systems (e.g. those from ROSE-L and CIMR) for vegetation monitoring.</p

Toward estimation of seasonal water dynamics of winter wheat from ground-based L-band radiometry: a concept study

peer reviewedThe vegetation optical depth (VOD) variable contains information on plant water content and biomass. It can be estimated alongside soil moisture from currently operating satellite radiometer missions, such as SMOS (ESA) and SMAP (NASA). The estimation of water fluxes, such as plant water uptake (PWU) and transpiration rate (TR), from these earth system parameters (VOD, soil moisture) requires assessing water potential gradients and flow resistances in the soil, the vegetation and the atmosphere. Yet water flux estimation remains an elusive challenge especially on a global scale. In this concept study, we conduct a field-scale experiment to test mechanistic models for the estimation of seasonal water fluxes (PWU and TR) of a winter wheat stand using measurements of soil moisture, VOD, and relative air humidity (RH) in a controlled environment. We utilize microwave L-band observations from a tower-based radiometer to estimate VOD of a wheat stand during the 2017 growing season at the Selhausen test site in Germany. From VOD, we first extract the gravimetric moisture of vegetation and then determine the relative water content (RWC) and vegetation water potential (VWP) of the wheat field. Although the relative water content could be directly estimated from VOD, our results indicate this may be challenging for the phenological phases, when rapid biomass and plant structure development take place within the wheat canopy. We estimate water uptake from the soil to the wheat plants from the difference between the soil and vegetation potentials divided by the flow resistance from soil into wheat plants. The TR from the wheat plants into the atmosphere was obtained from the difference between the vegetation and atmosphere water potentials divided by the flow resistances from plants to the atmosphere. For this, the required soil matric potential (SMP), the vapor pressure deficit (VPD), and the flow resistances were obtained from on-site observations of soil, plant, and atmosphere together with simple mechanistic models. This pathfinder study shows that the L-band microwave radiation contains valuable information on vegetation water status that enables the estimation of water dynamics (up to fluxes) from the soil via wheat plants into the atmosphere, when combined with additional information of soil and atmosphere water content. Still, assumptions have to be made when estimating the vegetation water potential from relative water content as well as the water flow resistances between soil, wheat plants, and atmosphere. Moreover, direct validation of water flux estimates for the assessment of their absolute accuracy could not be performed due to a lack of in situ PWU and TR measurements. Nonetheless, our estimates of water status, potentials, and fluxes show the expected temporal dynamics, known from the literature, and intercompare reasonably well in absolute terms with independent TR estimates of the NASA ECOSTRESS mission, which relies on a Priestly-Taylor type of retrieval model. Our findings support that passive microwave remote-sensing techniques qualify for the estimation of vegetation water dynamics next to traditionally measured stand-scale or plot-scale techniques. They might shed light on future capabilities of monitoring water dynamics in the soil-plant-atmosphere system including wide-area, remote-sensing-based earth observation data