Soil Moisture Active Passive Radar Research Articles

The first polarimetric GNSS-Reflectometer instrument in space improves the SMAP mission’s sensitivity over densely vegetated areas

The Soil Moisture Active Passive (SMAP) mission has dramatically benefited our knowledge of the Earth’s surface processes. The SMAP mission was initially designed to provide complementary L-band measurements from a radiometer and a radar, producing geophysical measurements at a finer spatial resolution than the radiometer alone. Both instruments, sensitive to the geophysical parameters in the swath, provided independent measurements at different spatial resolutions. A few months after SMAP’s launch, the radar transmitter’s high-power amplifier suffered an anomaly, and the instrument could no longer return data. During recovery activities, the SMAP mission switched the radar receiver frequency facilitating the reception of Global Positioning System (GPS) signals scattered off the Earth’s surface, and enabling the radar to become the first spaceborne polarimetric Global Navigation Satellite System – Reflectometry (GNSS-R) instrument. With more than 7 years of continued measurements, SMAP GNSS-R data are the most extensive existing GNSS-R dataset and the only one providing GNSS-R polarimetric measurements. We demonstrate that the SMAP polarimetric GNSS-R reflectivity, derived from Stokes parameters mathematical formulation, can enhance the radiometer data over dense vegetation areas, recovering some of the original SMAP radar capability to contribute to the science products and pioneering the first polarimetric GNSS-R mission.

Validation of the Effective Resolution of SMAP Enhanced Resolution Backscatter Products

NASA's Soil Moisture Active Passive (SMAP) mission originally included both passive and active L-band measurement capability. It was the first satellite instrument to provide global L-band radar observations of normalized radar cross section ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sigma ^{o}$</tex-math></inline-formula> ) at multiple resolutions. The SMAP radar collected high resolution ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 1–3 km) synthetic aperture radar (SAR) measurements over most of the Earth's land mass. It simultaneously collected low resolution 6×30 km “slice” and full-footprint 29×35 km measurements. The SMAP radar operated for 83 days from day of the year 103 to 186 in 2015, before the transmitter failed. The SMAP radar was designed to make vegetation roughness measurements in support of the SMAP primary mission to measure soil moisture, but the radar data is useful for a variety of applications, particularly in the polar regions. Unfortunately, limitations in the data download volume precluded downlink of high resolution data over Antarctica, sea ice in the polar regions, and various islands. Nonetheless, low resolution slice and footprint data were collected and downlinked over these areas. To better exploit this low resolution data, this paper employs image reconstruction techniques to create twice-daily enhanced resolution SMAP radar images from the slice and footprint measurements. To validate the resolution enhancement, the enhanced resolution data are compared to SAR results over Greenland and South America. The new data set is provided to the science community to support cryosphere and climate studies.

Application of a Change Detection Soil Moisture Retrieval Algorithm to Combined, Semiconcurrent Radiometer, and Radar Observations

This paper extends the application of an existing change-detection-based, time-series soil moisture retrieval algorithm to non-concurrent active and passive measurements from WindSat/AMSR2 and the Soil Moisture Active Passive radar, which was active from late April until mid-July on 2015. A time-series of L-band radar backscatter observations was used to populate an under-determined matrix equation whose optimal solution was derived via a bounded linear least squares estimator, and whose bounds were derived from a time-series of radiometer-derived soil moisture estimates (taken by either WindSat or AMSR2). Surface soil moisture estimates are compared with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-situ</i> measurement probes, which were treated as ground truth. Error statistics and time-series results for the validation sites are presented here and conclusions derived therefrom. The overall RMSE and un-biased RMSE for the retrieval algorithm, taken across all reference pixels considered in the study, were 0.070 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf{m}^{3}/\mathbf{m}^{3}$</tex-math></inline-formula> and 0.067 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf{m}^{3}/\mathbf{m}^{3}$</tex-math></inline-formula> respectively, when using WindSat to constrain the algorithm. When using AMSR2 to constrain the algorithm, the RMSE and un-biased RMSE were 0.093 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf{m}^{3}/\mathbf{m}^{3}$</tex-math></inline-formula> and 0.090 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbf{m}^{3}/\mathbf{m}^{3}$</tex-math></inline-formula> respectively.

Relationship Between Active and Passive Microwave Signals Over Vegetated Surfaces

The NASA Soil Moisture Active Passive (SMAP) satellite mission aims to produce enhanced resolution surface soil moisture products by combining coincident but multiresolution L-band active and passive microwave measurements. Since the SMAP radar ceased operations early in the mission, Copernicus Sentinel-1 C-band radar observations are used in the combined product. The synergy is built on two basic foundations: first, active and passive signals covary in a known and systematic fashion, and second, measurements are available at multiple resolutions. In this study, we perform numerical simulations and assess global satellite observations to test the first foundation (covariation). Specific focus lies on the role of the vegetation canopy in modulating the active–passive relationship. We use a discrete radiative transfer model to simulate the slope <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\beta $ </tex-math></inline-formula> and coefficient of determination <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> of the relationship between active and passive signals, considering three vegetation types for which the model has been extensively assessed in previous experimental studies. We find that a linear relationship between backscatter and emissivity can be established over a range of vegetation conditions. The coupling between active and passive signals decreases with increasing vegetation water content, such that moderate or higher correlations (nonzero slopes) are retained up to 4 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (6.3 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for L-band/L-band and 1.5 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (2 kg/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) for the C-band/L-band configuration. We decompose the effects of different soil-vegetation scattering mechanisms, such as double-bounce, and different measurement error levels on the active–passive relationship. Comparisons with satellite data confirm that our simulations capture magnitudes and major trends found across global vegetated land masses.

On the impact of C-band in place of L-band radar for SMAP downscaling

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) mission was launched on 31st January 2015, with the aim of providing global soil moisture maps at 9 km spatial resolution by combining L-band radar and radiometer observations. However, after the SMAP radar became inoperable, NASA decided to utilize the Sentinel 1A/1B C-band SAR data in its place. The new version of baseline brightness temperature (Tb) downscaling algorithm for SMAP is tested using L-band airborne data to evaluate the capabilities of the C-band Sentinel-1A SAR relative to L-band radar data in downscaling the SMAP Tb for achieving high resolution brightness temperature. In this study, the downscaling algorithm used L-band airborne Synthetic Aperture Radar (SAR) backscatter (σ) collected from the fifth Soil Moisture Active Passive Experiment (SMAPEx-5) in south-eastern Australia to downscale 36 km L-band SMAP radiometer Tb pixels to 3 km and 9 km. The downscaling results were then compared with the published results using Sentinel-1A C-band backscatter, and evaluated against airborne 1 km resolution L-band passive microwave brightness temperature collected from SMAPEx-5. The results show that for vertical polarization the average Root Mean Square Error (RMSE) of downscaled Tb when compared with reference airborne Tb across 4 days at 9 km resolution were 4.9 K for L-band and 6.0 K for C-band, and increased to 9.3 K for L-band and 9.6 K for C-band at 3 km spatial resolution. Moreover, the correlation coefficient (R) of downscaled and reference Tb across the 4 days was 0.92 for L-band and 0.88 for C-band at 9 km, decreasing to 0.75 for L-band and 0.72 for C-band at 3 km spatial resolution. Accordingly, the RMSE increased and the correlation coefficient decreased when using C-band radar data in place of that at L-band. However, overall there is expected to be only a slight decrease in performance of the downscaling algorithm by using the Sentinel 1A data in place of the SMAP radar.

The Use of SMAP-Reflectometry in Science Applications: Calibration and Capabilities

The Soil Moisture Active Passive (SMAP) mission became one of the newest spaceborne Global Navigation Satellite System–Reflectometry (GNSS-R) missions collecting Global Positioning System (GPS) bistatic radar measurements when the band-pass center frequency of its radar receiver was switched to the GPS L2C band. SMAP-Reflectometry (SMAP-R) brings a set of unique capabilities, such as polarimetry and improved spatial resolution, that allow for the exploration of scientific applications that other GNSS-R missions cannot address. In order to leverage SMAP-R for scientific applications, a calibration must be performed to account for the characteristics of the SMAP radar receiver and each GPS transmitter. In this study, we analyze the unique characteristics of SMAP-R, as compared to other GNSS-R missions, and present a calibration method for the SMAP-R signals that enables the standardized use of these signals by the scientific community. There are two key calibration parameters that need to be corrected: The first is the GPS transmitted power and GPS antenna gain at the incidence angle of the measured reflections and the second is the convolution of the SMAP high gain antenna pattern and the glistening zone (Earth surface area from where GPS signals scatter). To account for the GPS transmitter variability, GPS instrument properties—transmitted power and antenna gain—are collocated with information collected from the CYclone Global Navigation Satellite System (CYGNSS) at SMAP’s range of incidence angles (37.3° to 42.7°). To account for the convolutional effect of the SMAP antenna gain, both the scattering area of the reflected GPS signal and the SMAP antenna footprint are mapped on the surface. We account for the size of the scattering area corresponding to each delay and Doppler bin of the SMAP-R measurements based off the SMAP antenna pattern, and normalize according to the size of a measurement representative to one obtained with an omnidirectional antenna. We have validated these calibration methods through an analysis of the coherency of the reflected signal over an extensive area of old sea ice having constant surface characteristics over a period of 3 months. By selecting a vicarious scattering surface with high coherency, we eliminated scene variability and complexity in order to avoid scene dependent aliases in the calibration. The calibration method reduced the dependence on the GPS transmitter power and gain from ~1.08 dB/dB to a residual error of about −0.2 dB/dB. Results also showed that the calibration method eliminates the effect of the high gain antenna filtering effect, thus reducing errors as high as 10 dB on angles furthest from SMAP’s constant 40° incidence angle.

The SMAP and Copernicus Sentinel 1A/B microwave active-passive high resolution surface soil moisture product

Soil Moisture Active Passive (SMAP) mission of NASA was launched in January 2015. Currently, SMAP has an L-band radiometer and a defunct L-band radar with a rotating 6-m mesh reflector antenna. On July 7th, 2015, the SMAP radar malfunctioned and became inoperable. Consequently, the production of high-resolution active-passive soil moisture product got hampered, and only ~2.5 months (April 15th, 2015 to July 7th, 2015) of data remain available. Therefore, during the SMAP post-radar phase, many ways were examined to restart the high-resolution soil moisture product generation of the SMAP mission. One of the feasible approaches was to substitute the SMAP radar with other available SAR data. Sentinel-1A/Sentinel-1B SAR data was found most suitable for combining with the SMAP radiometer data because of its nearly similar orbit configuration that allows overlapping of their swaths with a minimal time difference, a key feature/requirement for the SMAP active-passive algorithm. The Sentinel interferometric wide swath (IW) mode acquisition also provides the co-polarized and cross-polarized observations required for the SMAP active-passive algorithm. However, some differences do exist between the SMAP and Sentinel SAR data. They are mainly: 1) Sentinel has a C-band SAR whereas SMAP operates at L-band; 2) Sentinel has multiple incidence angles within its swath, and SMAP has one single incidence angle; and 3) Sentinel 1A/B Interferometric Wide (IW) swath width is ~250 km as compared to SMAP with 1000 km swath width. On any given day, the narrow swath width of the Sentinel observations significantly reduces the overlap spatial coverage between SMAP and Sentinel as compared to the original SMAP radar and radiometer swath coverage. Hence, the temporal resolution (revisit interval) suffers due to narrow overlapped swath width and degrades from 3 days to 12 days. One advantage of using very high-resolution resolution Sentinel-1A/Sentinel-1B data in the SMAP active-passive algorithm is the potential of obtaining the disaggregated brightness temperature and thus soil moisture at a much finer spatial resolution of 3 km and 1 km at global extent. The assessment of high-resolution product at 3 km and 1 km using the soil moisture calibration and validations sites shows reasonable accuracy of ~0.05 m3/m3. The SMAP-Sentinel1 active-passive high-resolution product is now available to the public (new version released in October 2018) through NSIDC (NASA DAAC). The duration of this product is from April 2015 to current date.

The SMAP mission combined active-passive soil moisture product at 9 km and 3 km spatial resolutions

The NASA Soil Moisture Active Passive (SMAP) mission was launched on January 31st, 2015. The spacecraft was to provide high-resolution (3 km and 9 km) global soil moisture estimates at regular intervals by combining for the first time L-band radiometer and radar observations. On July 7th, 2015, a component of the SMAP radar failed and the radar ceased operation. However, before this occurred the mission was able to collect and process ~2.5 months of the SMAP high-resolution active-passive soil moisture data (L2SMAP) that coincided with the Northern Hemisphere's vegetation green-up and crop growth season. In this study, we evaluate the SMAP high-resolution soil moisture product derived from several alternative algorithms against in situ data from core calibration and validation sites (CVS), and sparse networks. The baseline algorithm had the best comparison statistics against the CVS and sparse networks. The overall unbiased root-mean-square-difference is close to the 0.04 m3/m3 the SMAP mission requirement. A 3 km spatial resolution soil moisture product was also examined. This product had an unbiased root-mean-square-difference of ~0.053 m3/m3. The SMAP L2SMAP product for ~2.5 months is now validated for use in geophysical applications and research and available to the public through the NASA Distributed Active Archive Center (DAAC) at the National Snow and Ice Data Center (NSIDC). The L2SMAP product is packaged with the geo-coordinates, acquisition times, and all requisite ancillary information. Although limited in duration, SMAP has clearly demonstrated the potential of using a combined L-band radar-radiometer for proving high spatial resolution and accurate global soil moisture.

A Polarimetric Active Transponder With Extremely Large RCS for Absolute Radiometric Calibration of SMAP Radar

This paper presents a new single-antenna polarimetric active radar calibrator (PARC) intended for the polarimetric and absolute radiometric calibration of the NASA’s soil moisture active passive (SMAP) radar. The PARC receives and retransmits the SMAP signal through a dual-polarized horn antenna with 17-dB gain at the center frequency of 1.26 GHz with 100 MHz of bandwidth. The transmit and receive polarizations are perpendicular and are isolated from each other using a precision orthomode transducer (OMT) specially designed for this application. The antenna is rotated 45° in the plane perpendicular to the direction of incidence, so that the scattering matrix of the PARC with respect to SMAP polarization coordinates has equal entries that enable radiometric calibration of all four channels simultaneously. As SMAP radar resolution is coarse (1 km), a point target with a very large radar cross section (RCS) is required to provide a high signal-to-clutter ratio. The proposed PARC can provide RCS values as high as 80 dBsm to achieve a 30-dB signal-to-clutter ratio. The PARC is controlled by a microcontroller to autonomously start minutes before the SMAP radar is expected to scan the area, stabilize the amplifier gain, record the magnitude of the pulses transmitted from the radar, and transmit these data to a base station. The design procedures of the OMT and the antenna, as well as control and RF circuits, are discussed, a number of leakage cancelation techniques are introduced to increase the isolation between the ports, the RCS of the fabricated PARC is fully characterized, and the image of the PARC as seen by SMAP is presented.

Multi-Scale Validation of SMAP Soil Moisture Products over Cold and Arid Regions in Northwestern China Using Distributed Ground Observation Data

The Soil Moisture Active Passive (SMAP) mission was designed to provide global mapping of soil moisture (SM) on nested 3, 9, and 36 km earth grids measured by L-band passive and active microwave sensors. The validation of SMAP SM products is crucial for the application of the products and improvement of the retrieval algorithm. Since the SMAP SM products were released, much effort has been invested in the evaluation of the SMAP radiometer SM product (SMAP_P). However, there has been little validation of SMAP radar (SMAP_A) and active/passive combined (SMAP_AP) SM products. This paper presents an evaluation of SMAP_P, SMAP_A and SMAP_AP SM products by using distributed ground observations networks in different landscapes in the Heihe River Basin of northwestern China. The standard error metrics of SMAP products and relative error are applied to measure the products’ performances. The results show that the SMAP SM products exhibit consistent spatial-temporal variation with the ground measurements and typical precipitation events. Three products show various types of performance capability (e.g., active, passive and combined), surface coverage (e.g., bare, vegetated) and climatic region (e.g., cold, arid). Relatively, the SMAP_P shows the best performance, while the SMAP_A performs the worst. The best performances are observed over bare soils but with overestimation and the largest relative error, and unsatisfactory accuracies are observed over cold regions and woody vegetated surfaces with underestimation. The vegetation effect and the freezing-thawing cycle may be major factors that led to an unsatisfactory performance. Efforts on resolving the influence of these factors are expected to improve the accuracy and to promote the application of SMAP SM products over these regions. Overall, this evaluation provides an understanding of SMAP SM products over cold and arid regions, and suggestions for the further refinement of the SMAP SM retrieval algorithms.

Retrieving landscape freeze/thaw state from Soil Moisture Active Passive (SMAP) radar and radiometer measurements

Over one-third of the global land area undergoes a seasonal transition between predominantly frozen and non-frozen conditions each year, with the land surface freeze/thaw (FT) state a significant control on hydrological and biospheric processes over northern land areas and at high elevations. The NASA Soil Moisture Active Passive (SMAP) mission produced a daily landscape FT product at 3-km spatial resolution derived from ascending and descending orbits of SMAP high-resolution L-band (1.4GHz) radar measurements. Following the failure of the SMAP radar in July 2015, coarser (36-km) footprint SMAP radiometer inputs were used to develop an alternative daily passive microwave freeze/thaw product. In this study, in situ observations are used to examine differences in the sensitivity of the 3-km radar versus the 36-km radiometer measurements to the landscape freeze/thaw state during the period of overlapping instrument operation. Assessment of the retrievals at high-latitude SMAP core validation sites showed excellent agreement with in situ flags, exceeding the 80% SMAP mission accuracy requirement. Similar performance was found for the radar and radiometer products using both air temperature and soil temperature derived FT reference flags. There was a tendency for SMAP thaw retrievals to lead the surface flags due to the influence of wet snow cover conditions on both the radar and radiometer signal. Comparison with other satellite derived FT products showed those derived from passive measurements (SMAP radiometer; Aquarius radiometer; Advanced Microwave Scanning Radiometer - 2) retrieved less frozen area than the active products (SMAP radar; Aquarius radar).

Frequency-Agile Radar Electronics for the Soil Moisture Active\/Passive (SMAP) Mission

The radar aboard the Soil Moisture Active/Passive (SMAP) instrument is an L-band scatterometer/synthetic aperture radar (SAR) with uniquely designed capabilities for global retrieval of surface soil moisture. Several key science requirements have shaped the radar architecture, including requirements on terrestrial radio frequency interference (RFI) mitigation, calibration stability, and on silencing radiated emissions from the electronics in the presence of the sensitive radiometer aboard SMAP. The design uses an unconventional conical scan sequence to collect SAR data over a wide swath while the radar frequency-hops over 1217-1298 MHz in order to avoid RFI from ground sources. In this paper, we discuss: 1) the design trades that led to the choice of a frequencyhopping, "tunable LO" receiver scheme that significantly reduces the SMAP radar susceptibility to RFI; 2) loopback calibration to minimize bias errors in the transmit-power × receiver-gain product; 3) hardware design techniques for decreasing radiated emissions levels in the 1.41-GHz radiometer band; and 4) pre-launch performance results from flight radar environmental testing.

RFI Characterization and Mitigation for the SMAP Radar

The Soil Moisture Active-Passive (SMAP) mission will launch in late 2014 and will carry a combined L-band radiometer/radar instrument for the retrieval of global soil moisture and surface freeze-thaw state. Radio frequency interference (RFI) is a known challenge for Earth remote sensing in the L-band portion of the spectrum. This paper addresses efforts to characterize and mitigate RFI for the SMAP radar. A model for the RFI environment due to surface-based emitters is developed, and is shown to agree well with the observations of currently operating L-band radar systems. An analysis of the environment due to space-based emitters is also presented. Techniques to mitigate RFI in the radar band are described, and are shown to perform sufficiently well to meet the stringent SMAP measurement requirements. A companion paper addresses the different issues encountered with RFI in the radiometer band.