A method for retrieving high-resolution surface soil moisture from hydros L-band radiometer and Radar observations

NASA's Earth System Science Pathfinder Hydrospheric States (Hydros) mission will provide the first global scale space-borne observations of Earth's soil moisture using both L-band microwave radiometer and radar technologies. In preparation for the Hydros mission, an observation system simulation experiment (OSSE) has been conducted. As a part of this OSSE, the potential for retrieving useful surface soil moisture at spatial resolutions of 9 and 3 km was explored. The approach involved optimally merging relatively accurate 36-km radiometer brightness temperature and relatively noisy 3-km radar backscatter cross section observations using a Bayesian method. Based on the Hydros OSSE data sets with low and high noises added to the simulated observations or model parameters, the Bayesian method performed better than direct inversion of either the brightness temperature or radar backscatter observations alone. The root-mean-square errors of 9-km soil moisture retrievals from the Bayesian merging method were reduced by 0.5 %vol/vol and 1.4 %vol/vol from the errors of direct radar inversions for the entire OSSE domain of all 34 consecutive days for the low and high noise data sets, respectively. Improvement in soil moisture estimates using the Bayesian merging method over the direct inversions of radar or radiometer data were even more significant for soil moisture retrieval at 3-km resolution. However, to address the representativeness of these results at the global and multiyear scales, further performance comparison studies are needed, particularly with actual field data.     

Soil moisture retrieval from space: the Soil Moisture and OceanSalinity (SMOS) mission

Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility of using antenna synthesis methods has been investigated. Such a system, relying on a deployable structure, has now proved to be feasible and has led to the Soil Moisture and Ocean Salinity (SMOS) mission, which is described. The main objective of the SMOS mission is to deliver key variables of the land surfaces (soil moisture fields), and of ocean surfaces (sea surface salinity fields). The SMOS mission is based on a dual polarized L-band radiometer using aperture synthesis (two-dimensional [2D] interferometer) so as to achieve a ground resolution of 50 km at the swath edges coupled with multiangular acquisitions. The radiometer will enable frequent and global coverage of the globe and deliver surface soil moisture fields over land and sea surface salinity over the oceans. The SMOS mission was proposed to the European Space Agency (ESA) in the framework of the Earth Explorer Opportunity Missions. It was selected for a tentative launch in 2005. The goal of this paper is to present the main aspects of the baseline mission and describe how soil moisture will be retrieved from SMOS data     

ESTAR measurements during the Southern Great Plains experiment(SGP99)

During the Southern Great Plains experiment (SGP99), the electronically scanned thinned array radiometer (ESTAR) mapped L-band brightness temperature over a swath about 50-km wide and 300 km long, extending west from Oklahoma City, OK, to El Reno, OK, and north from the Little Washita River watershed to the Kansas border. ESTAR flew on the NASA P-3B Orion aircraft at an altitude of 7.6 km, and maps were made on seven days between July 8-20, 1999. The brightness temperature maps reflect the patterns of soil moisture expected from rainfall and are consistent with values of soil moisture observed at the research sites within the SGP99 study area and with previous measurements in this area. The data add to the resources for hydrologic modeling in this area and are further validation of the technology represented by ESTAR as a potential path to a future mission to map soil moisture globally from space     

RADARSAT [SAR imaging]

RADARSAT, the first Canadian remote-sensing spacecraft, is designed to provide Earth observation information for five years. The satellite is scheduled for launch in 1994. The only payload instrument is a 5.6-cm-wavelength (C-band) synthetic aperture imaging radar (SAR). RADARSAT will gather data on command for up to 28 min during each cycle of its 800-km (nominal) near-polar orbit. Image resolutions from 10 to 100 m at swath widths of 45 to 500 km will be available. The RADARSAT mission is reviewed, and the design, characteristics, and implementation of the radar are introduced. Technical problems addressed include calibration, rapid data processing, the phased array antenna that provides controlled beam steering, and the first satellite implementation of a special radar technique known as ScanSAR     

Impact of Multiresolution Active and Passive Microwave Measurements on Soil Moisture Estimation Using the Ensemble Kalman Smoother

An observing system simulation experiment is developed to test tradeoffs in resolution and accuracy for soil moisture estimation using active and passive L-band remote sensing. Concepts for combined radar and radiometer missions include designs that will provide multiresolution measurements. In this paper, the scientific impacts of instrument performance are analyzed to determine the measurement requirements for the mission concept. The ensemble Kalman smoother (EnKS) is used to merge these multiresolution observations with modeled soil moisture from a land surface model to estimate surface and subsurface soil moisture at 6-km resolution. The model used for assimilation is different from that used to generate "truth." Consequently, this experiment simulates how data assimilation performs in real applications when the model is not a perfect representation of reality. The EnKS is an extension of the ensemble Kalman filter (EnKF) in which observations are used to update states at previous times. Previous work demonstrated that it provides a computationally inexpensive means to improve the results from the EnKF, and that the limited memory in soil moisture can be exploited by employing it as a fixed lag smoother. Here, it is shown that the EnKS can be used in large problems with spatially distributed state vectors and spatially distributed multiresolution observations. The EnKS-based data assimilation framework is used to study the synergy between passive and active observations that have different resolutions and measurement error distributions. The extent to which the design parameters of the EnKS vary depending on the combination of observations assimilated is investigated     

The NAFE'05/CoSMOS Data Set: Toward SMOS Soil Moisture Retrieval, Downscaling, and Assimilation

The National Airborne Field Experiment 2005 (NAFE'05) and the Campaign for validating the Operation of Soil Moisture and Ocean Salinity (CoSMOS) were undertaken in November 2005 in the Goulburn River catchment, which is located in southeastern Australia. The objective of the joint campaign was to provide simulated Soil Moisture and Ocean Salinity (SMOS) observations using airborne L-band radiometers supported by soil moisture and other relevant ground data for the following: (1) the development of SMOS soil moisture retrieval algorithms; (2) developing approaches for downscaling the low-resolution data from SMOS; and (3) testing its assimilation into land surface models for root zone soil moisture retrieval. This paper describes the NAFE'05 and CoSMOS airborne data sets together with the ground data collected in support of both aircraft campaigns. The airborne L-band acquisitions included 40 km times 40 km coverage flights at 500-m and 1-km resolution for the simulation of a SMOS pixel, multiresolution flights with ground resolution ranging from 1 km to 62.5 m, multiangle observations, and specific flights that targeted the vegetation dew and sun glint effect on L-band soil moisture retrieval. The L-band data were accompanied by airborne thermal infrared and optical measurements. The ground data consisted of continuous soil moisture profile measurements at 18 monitoring sites throughout the 40 km times 40 km study area and extensive spatial near-surface soil moisture measurements concurrent with airborne monitoring. Additionally, data were collected on rock coverage and temperature, surface roughness, skin and soil temperatures, dew amount, and vegetation water content and biomass. These data are available at www.nafe.unimelb.edu.au.     

Conceptual Performance of a Satellite Borne, Wide Swath Synthetic Aperture Radar

A satellite borne synthetic aperture radar can image a wide swath in the order of 700 km with one-look 100-m resolution. If the design meets the ambiguity constraints at the far edge of the swath, the maximum swath width is independent of both radar wavelength and shape of the physical antenna aperture. The antenna pattern can be a pencil beam scanned in the elevation plane, or a fan beam formed by a long antenna. The scanning pencil beam antenna may be a phased array or multiple-feed reflector which may be more practical than a long antenna to image a wide swath. Design performance trade computations are presented involving resolution, swath width, antenna area, average transmitter power and digital data rate.     

High-resolution change estimation of soil moisture using L-band radiometer and Radar observations made during the SMEX02 experiments

The soil moisture experiments held during June-July 2002 (SMEX02) at Iowa demonstrated the potential of the L-band radiometer (PALS) in estimation of near surface soil moisture under dense vegetation canopy conditions. The L-band radar was also shown to be sensitive to near surface soil moisture. However, the spatial resolution of a typical satellite L-band radiometer is of the order of tens of kilometers, which is not sufficient to serve the full range of science needs for land surface hydrology and weather modeling applications. Disaggregation schemes for deriving subpixel estimates of soil moisture from radiometer data using higher resolution radar observations may provide the means for making available global soil moisture observations at a much finer scale. This paper presents a simple approach for estimation of change in soil moisture at a higher (radar) spatial resolution by combining L-band copolarized radar backscattering coefficients and L-band radiometric brightness temperatures. Sensitivity of AIRSAR L-band copolarized channels has been demonstrated by comparison with in situ soil moisture measurements as well as PALS brightness temperatures. The change estimation algorithm has been applied to coincident PALS and AIRSAR datasets acquired during the SMEX02 campaign. Using AIRSAR data aggregated to a 100-m resolution, PALS radiometer estimates of soil moisture change at a 400-m resolution have been disaggregated to 100-m resolution. The effect of surface roughness variability on the change estimation algorithm has been explained using integral equation model (IEM) simulations. A simulation experiment using synthetic data has been performed to analyze the performance of the algorithm over a region undergoing gradual wetting and dry down.     

Microwave backscattering and emission model for grass canopies

Microwave radar and radiometer measurements of grasslands indicate a substantial reduction in sensor sensitivity to soil moisture in the presence of a thatch layer. When this layer is wet it masks changes in the underlying soil, making the canopy appear warm in the case of passive sensors (radiometer) and decreasing backscatter in the active case (scatterometer). A model for a grass canopy with thatch is presented in order to explain this behavior and for comparison with observations. The canopy model consists of three layers: grass, thatch, and the underlying soil. The grass blades are modeled by elongated elliptical discs and the thatch is modeled as a collection of disk shaped water droplets (i.e., the dry matter is neglected). The ground is homogeneous and flat. The distorted Born approximation is used to compute the radar cross section of this three layer canopy and the emissivity is computed from the radar cross section using the Peake formulation for the passive problem. Results are computed at L-band (1.4 GHz) and C-band (4.75 GHz) using canopy parameters (i.e., plant geometry, soil moisture, plant moisture, etc.) representative of Konza Prairie grasslands. The results are compared to C-band scatterometer measurements and L-band radiometer measurements at these grasslands     

Application of ERS-1 wind scatterometer data to soil frost and soilmoisture monitoring in boreal forest zone

The feasibility of the ERS-1 Wind Scatterometer (WS) for monitoring the boreal forest zone is investigated, concentrating on soil frost and soil moisture monitoring. The ERS-1 WS measures the target area with coarse spatial resolution (about 50 km) using three separate antenna beams and a wide angular range. The investigations are concerned with the boreal forest zone using data (1) from test areas located in Finland and (2) covering the whole northern European boreal forest zone. The seasonal behavior of WS data is studied and a semiempirical forest backscattering model-based inversion method for the retrieval of soil moisture and for soil frost monitoring from WS data is developed. The developed inversion method employs nearly simultaneous three-beam measurements and a varying incidence angle. Promising results were obtained in the monitoring of soil frost, and the retrieval of soil moisture also appears to be a feasible field of application. The applicability of the instrument for forest biomass retrieval using single images was found to be limited to long-term change detection     

Development of precipitation radar onboard the Tropical RainfallMeasuring Mission (TRMM) satellite

The precipitation radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite is the first spaceborne radar to measure precipitation from space. The PR, operating at 13.8 GHz, is a 128-element active phased array that allows a fast and sophisticated cross-track scanning over a swath width of 215 km with a cross-range spatial resolution of about 4.3 km. The PR has a minimum detectable rain rate of 0.5 mm/h with range resolution of 250 m. In order to achieve a reliable and accurate rain echo data for three years mission life, functions for internal and external calibrations are implemented. Through a series of PR flight-model tests on the ground and an initial checkout just after the TRMM launch, it is confirmed that the PR functions properly and meets the performance requirements to quantitatively measure three-dimensional (3D) precipitation distribution from space     

New radar studies of slant-path attenuation due to rain

Approximately 40 h of data from the summer of 1976 were employed in a comparison of radar and radiometer estimates of slant-path attenuation due to rain. McGill Radar Weather Observatory is situated 20 km west of Montreal; the radiometers, separated by 18 km at two sites located about 90 km northwest of the radar, had fixed antennas pointed approximately southeast at an elevation of 18.5 deg. Values of radar reflectivity along the two radiometer paths were used to calculate the slant-path attenuation at 13 GHz as a function of time with a 1 min resolution for direct comparison with the radiometer measurements. It was found that the cumulative distribution of attenuation inferred by radar from each site could be made to agree satisfactorily with the radiometer distribution assuming that rain was present everywhere along the path with a Marshall-Palmer distribution and applying a 1 dB correction to the independently-determined radar calibration. This agreement, close to within a fraction of a decibel, gives confidence to the use of radar records in compiling attenuation statistics. An example is presented of a new application of such records, namely the assessment of rain-induced interference over adjacent earth-space paths.     

Passive active L- and S-band (PALS) microwave sensor for oceansalinity and soil moisture measurements

A passive/active WS-band (PALS) microwave aircraft instrument to measure ocean salinity and soil moisture has been built and tested. Because the L-band brightness temperatures associated with salinity changes are expected to be small, it was necessary to build a very sensitive and stable system. This new instrument has dual-frequency, dual polarization radiometer and radar sensors. The antenna is a high beam efficiency conical horn. The PALS instrument was installed on the NCAR C-130 aircraft and soil moisture measurements were made in support of the Southern Great Plains 1999 experiment in Oklahoma from July 8-14, 1999. Data taken before and after a rainstorm showed significant changes in the brightness temperatures, polarization ratios and radar backscatter, as a function of soil moisture. Salinity measurement missions were flown on July 17-19, 1999, southeast of Norfolk, VA, over the Gulf Stream. The measurements indicated a clear and repeatable salinity signal during these three days, which was in good agreement with the Cape Hatteras ship salinity data. Data were also taken in the open ocean and a small decrease of 0.2 K was measured in the brightness temperature, which corresponded to the salinity increase of 0.4 psu measured by the M/V Oleander vessel     

Flower Constellation of Millimeter-Wave Radiometers for Tropospheric Monitoring at Pseudogeostationary Scale

In this paper, the design of a minisatellite FLOwer constellation (FC), deploying millimeter-wave (MMW) scanning RADiometers, namely, FLORAD, and devoted to tropospheric observations, is analyzed and discussed. The FLORAD mission is aimed at the retrieval of thermal and hydrological properties of the troposphere, specifically temperature profile, water-vapor profile, cloud liquid content, and rainfall and snowfall rate. The goal of frequent revisit time at regional scale, coupled with quasi-global coverage and relatively high spatial resolution, is here called pseudogeostationary scale and implemented through a FC of three minisatellites in elliptical orbits. FCs are built on compatible (resonant) orbits and can offer several degrees of freedom in their design. The payload MMW channels for tropospheric retrieval were selected following the ranking based on a reduced-entropy method between 90 and 230 GHz. Various configurations of the MMW radiometer multiband channels are investigated, pointing out the tradeoff between performances and complexity within the constraint of minisatellite platform. Statistical inversion schemes are employed to quantify the overall accuracy of the selected MMW radiometer configurations.      

An observation system simulation experiment for the impact of landsurface heterogeneity on AMSR-E soil moisture retrieval

Using a high-resolution hydrologic model, a land surface microwave emission model (LSMEM), and an explicit simulation of the orbital and scanning characteristics for the advanced microwave sensing radiometer (AMSR-E), an observing system simulation experiment (OSSE) is carried out to assess the impact of land surface heterogeneity on large-scale retrieval and validation of soil moisture products over the U.S. Southern Great Plains using the 6.925 GHz channel on the AMSR-E sensor. Land surface heterogeneity impacts soil moisture products through the presence of nonlinearities in processes represented by the LSMEM, as well as the fundamental inconsistency in spatial scale between gridded soil moisture imagery derived from in situ point-scale sampling, numerical modeling, and microwave remote sensing sources. Results within the 575000 km² Red-Arkansas River basin show that, for surfaces with vegetation water contents below 0.75 kg/m², these two scale effects induce root mean squared errors (RMSEs) of 1.7% volumetric (0.017 cm_water³/cm_soil³ ) into daily 60 km AMSR-E soil moisture products and RMS differences of 3.0% (0.030 cm_water/3cm_soil³ ) into 60 km comparisons of AMSR-E soil moisture products and in situ field-scale measurements of soil moisture sampled on a fixed 25-km grid     

Soil moisture retrieval from AMSR-E

The Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System (EOS) Aqua satellite was launched on May 4, 2002. The AMSR-E instrument provides a potentially improved soil moisture sensing capability over previous spaceborne radiometers such as the Scanning Multichannel Microwave Radiometer and Special Sensor Microwave/Imager due to its combination of low frequency and higher spatial resolution (approximately 60 km at 6.9 GHz). The AMSR-E soil moisture retrieval approach and its implementation are described in this paper. A postlaunch validation program is in progress that will provide evaluations of the retrieved soil moisture and enable improved hydrologic applications of the data. Key aspects of the validation program include assessments of the effects on retrieved soil moisture of variability in vegetation water content, surface temperature, and spatial heterogeneity. Examples of AMSR-E brightness temperature observations over land are shown from the first few months of instrument operation, indicating general features of global vegetation and soil moisture variability. The AMSR-E sensor calibration and extent of radio frequency interference are currently being assessed, to be followed by quantitative assessments of the soil moisture retrievals.     

Multifrequency Microwave Radiometer Measurements of Soil Moisture

Ground-based microwave radiometer experiments were performed to investigate the effects of moisture, temperature, and roughness on microwave emission from bare soils. Measurements were made at frequencies of 0.6-0.9, 1.4, and 10.7 GHz using van-mounted radiometers to observe prepared soil sites in Kern County, CA. The sites were instrumented for monitoring soil characteristics and surface meteorological conditions. Brightness temperature variations of approximately 15 K at 1.4 GHz and 25 K at 10.7 GHz were observed as a result of diurnal changes in the soil temperature. Increasing the soil moisture content from 2 to 15 percent by volume resulted in brightness temperature decreases of approximately 70 K at 0.775 and 1.4 GHz, and 40 K at 10.7 GHz, depending, to a lesser extent, on polarization and viewing angle. The results show the significance of soil temperature in deriving soil moisture from microwave radiometer measurements. Comparisons of the microwave measurements with theoretical predictions using a smooth surface model show reasonable agreement and support previous results of this nature obtained with other soil types. Approximately equal sensitivity to soil moisture was observed at 0.775 and 1.4 GHz, although the sampling depth is greater at the lower frequency.     

Improvement of Moisture Estimation Accuracy of Vegetation-Covered Soil by Combined Active/Passive Microwave Remote Sensing

The measured effects of vegetation canopies on radar and radiometric sensitivity to soil moisture are compared to first-order emission and scattering models. The models are found to predict the measured emission and backscattering with reasonable accuracy for various crop canopies at frequencies between 1.4 and 5.0 GHz, especially at angles of incidence less than 30°. The vegetation loss factor L (?) increases with frequency and is found to be dependent upon canopy type and water content. In addition, the effective radiometric power absorption coefficient of a mature corn canopy is roughly 1.75 times that calculated for the radar at the same frequency. Comparison of an L-band radiometer with a C-band radar shows the two systems to be complementary in terms of accurate soil moisture sensing over the extreme range of naturally occurring soil-moisture conditions. The combination of both an L-band radiometer and a C-band radar is expected to yield soil-moisture estimates that are accurate to better than +/-30 percent of true soil moisture, even for a soil under a lossy crop canopy such as mature corn. This is true even without any other ancillary information.