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Microwave remote sensing of soil moisture, volume 1

Multifrequency sensor data from NASA's C-130 aircraft were used to determine which of the all weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. The perpendicular vegetation index (PVI) as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture. A linear equation was developed to estimate percent field capacity as a function of L-band emissivity and the vegetation index. The prediction algorithm improves the estimation of moisture significantly over predictions from L-band emissivity alone.

Mcfarland, M. J.↗

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA's Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has as its key measurement objective the frequent, global mapping of near-surface soil moisture and its freeze-thaw state. SMAP soil moisture and freeze/thaw measurements at 10 km and 3 km resolutions respectively, would enable significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture control of these fluxes is a key factor in the performance of atmospheric models used for weather forecasts and climate projections Soil moisture measurements are also of great importance in assessing floods and for monitoring drought. In addition, observations of soil moisture and freeze/thaw timing over the boreal latitudes can help reduce uncertainties in quantifying the global carbon balance. The SMAP measurement concept utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The SMAP radiometer and radar flight hardware and ground processing designs are incorporating approaches to identify and mitigate potential terrestrial radio frequency interference (RFI). The radar and radiometer instruments are planned to operate in a 680 km polar orbit, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments would yield global maps of soil moisture and freeze/thaw state to be provided at 10 km and 3 km resolutions respectively, every two to three days. Plans are to provide also a radiometer-only soil moisture product at 40-km spatial resolution. This product and the underlying brightness temperatures have characteristics similar to those provided by the Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are unique opportunities for common data product development and continuity between the two missions. SMAP also has commonalities with other satellite missions having L-band radiometer and/or radar sensors applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Njoku, Eni↗

An L-Band Brightness Temperature Disaggregation Method Using S-Band Radiometer Data for the Water Cycle Observation Mission (WCOM)

The Water Cycle Observation Mission (WCOM) will build upon previous L and C band passive microwave soil moisture satellite missions. WCOM will consist of a passive microwave synthetic aperture radiometer operating at L, S, and C bands. The WCOM requirements for passive soil moisture are to estimate soil moisture in the top 5 cm of soil layer with an error less than 0.04 cu m/cu m, at 15 km resolution and with a 3-day revisit. A new set of algorithms for these multi-frequency platforms will need to be developed for estimating the data products at the desired resolution. To accomplish this, a brightness temperature (TB) downscaling methodology is developed that uses passive S-band TB (30 km) to downscale L-band TB (50 km) and to estimate soil moisture at a 30 km resolution, based on the linear relationships between the passive signals of L-band and S-band. To test this downscaling method, analysis was performed using PALS data from the Soil Moisture Experiments in 2002 (SMEX02). For this study, 4 km L-band observations were downscaled to 800 m. The root mean square errors (RMSE) between the downscaled TBL at 800m with the observed TBL at 800m are 2.63 K and 1.60 K for H and V polarizations respectively. The results also showed that it was possible to use these disaggregated TB to estimate soil moisture to meet the mission requirement of 0.04 cu m/cu m. These results showed that we can obtain higher resolution soil moisture from L band passive TB with a high accuracy (<0.04 cu m/cu m) by using S-band information.

Disaggregation↗

L-Band Brightness Temperature Variations at Dome C and Snow Metamorphism at the Surface

The Antarctic Plateau is a promising site to monitor microwave radiometers' drift, and to inter-calibrate microwave radiometers, especially 1.4 GigaHertz (L-band) radiometers on board the Soil Moisture and Ocean Salinity (SMOS), and AquariusSAC-D missions. The Plateau is a thick ice cover, thermally stable in depth, with large dimensions, and relatively low heterogeneities. In addition, its high latitude location in the Southern Hemisphere enables frequent observations by polar-orbiting satellites, and no contaminations by radio frequency interference. At Dome C (75S, 123E), on the Antarctic Plateau, the substantial amount of in-situ snow measurements available allows us to interpret variations in space-borne microwave brightness temperature (TB) (e.g. Macelloni et al., 2007, 2013, Brucker et al., 2011, Champollion et al., 2013). However, to analyze the observations from the Aquarius radiometers, whose sensitivity is 0.15 K, the stability of the snow layers near the surface that are most susceptible to rapidly change needs to be precisely assessed. This study focuses on the spatial and temporal variations of the Aquarius TB over the Antarctic Plateau, and at Dome C in particular, to highlight the impact of snow surface metamorphism on the TB observations at L-band.

l-band↗

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Kim, Edward↗

Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations

Several L-band microwave radiometer and radar missions have been, or will be, operating in space for land and ocean observations. These include the NASA Aquarius mission and the Soil Moisture Active Passive (SMAP) mission, both of which use combined passive/ active L-band instruments. Aquarius s passive/active L-band microwave sensor has been designed to map the salinity field at the surface of the ocean from space. SMAP s primary objectives are for soil moisture and freeze/thaw detection, but it will operate continuously over the ocean, and hence will have significant potential for ocean surface research. In this innovation, an algorithm has been developed to retrieve simultaneously ocean surface salinity and wind from combined passive/active L-band microwave observations of sea surfaces. The algorithm takes advantage of the differing response of brightness temperatures and radar backscatter to salinity, wind speed, and direction, thus minimizing the least squares error (LSE) measure, which signifies the difference between measurements and model functions of brightness temperatures and radar backscatter. The algorithm uses the conjugate gradient method to search for the local minima of the LSE. Three LSE measures with different measurement combinations have been tested. The first LSE measure uses passive microwave data only with retrieval errors reaching 1 to 2 psu (practical salinity units) for salinity, and 1 to 2 m/s for wind speed. The second LSE measure uses both passive and active microwave data for vertical and horizontal polarizations. The addition of active microwave data significantly improves the retrieval accuracy by about a factor of five. To mitigate the impact of Faraday rotation on satellite observations, the third LSE measure uses measurement combinations invariant under the Faraday rotation. For Aquarius, the expected RMS SSS (sea surface salinity) error will be less than about 0.2 psu for low winds, and increases to 0.3 psu at 25 m/s wind speed for warm waters (25 C). To achieve the required 0.2 psu accuracy, the impact of sea surface roughness (e.g. wind-generated ripples) on the observed brightness temperature has to be corrected to better than one tenth of a degree Kelvin. With this algorithm, the accuracy of retrieved wind speed will be high, varying from a few tenths to 0.6 m/s. The expected direction accuracy is also excellent (less than 10 ) for mid to high winds, but degrades for lower speeds (less than 7 m/s).

Yueh, Simon H.↗

SMAP science recovery efforts

The Soil Moisture Active Passive (SMAP) spacecraft launched in January 2015, with a mission to produce global soil moisture maps every 1.5 days using a combination of active (radar) and passive (radiometer) L-band measurements. In July 2015, after 2.5 months in operation, the radar failed and was not able to transmit. While the radiometer was still producing excellent science measurements, the need to recover key active-passive soil moisture requirements was paramount. To that end, the science team found that the European Space Agency (ESA) had recently launched a C-band SAR spacecraft called Sentinel-1A (launched April 2014) in a similar orbit, which was seen as a potential replacement to the “active” part of the SMAP measurements. An analysis was performed to see what the resulting spatial and temporal coverage could be. The promising results of that coupled with the ramp up in global coverage from Sentinel-1A and 1B (launched April 2016) allowed SMAP to create a new joint science data product that strives to meet the original mission objectives. The joint product is now part of the routine release of SMAP data to the science community as of June 2018.

Ballard, Christopher G.↗

ESTAR: The Electronically Scanned Thinned Array Radiometer for remote sensing measurement of soil moisture and ocean salinity

The product of a working group assembled to help define the science objectives and measurement requirements of a spaceborne L-band microwave radiometer devoted to remote sensing of surface soil moisture and sea surface salinity is presented. Remote sensing in this long-wavelength portion of the microwave spectrum requires large antennas in low-Earth orbit to achieve acceptable spatial resolution. The proposed radiometer, ESTAR, is unique in that it employs aperture synthesis to reduce the antenna area requirements for a space system.

Swift, C. T.↗

Seasonal Dependence of SMAP Radiometer-Based Soil Moisture Performance as Observed over Core Validation Sites

The NASA SMAP (Soil Moisture Active Passive) mission provides a global coverage of soil moisture measurements based on its L-band microwave radiometer every 2-3 days at about 40 km resolution. The soil moisture retrieval algorithms model the brightness temperature as a function of soil moisture, surface conditions and vegetation. External data sources inform the algorithms about the surface conditions and vegetation, which enable the retrieval of soil moisture. The inversion process contains uncertainties related to radiometer measurements, forward model assumptions and ancillary data sources. This study focuses on the uncertainties that depend on the seasonal evolution of the surface conditions and vegetation. This study compares the SMAP and core validation site (CVS) soil moisture values over a period of three years to extract the evolution of performance metrics over time. The analysis showed that most CVS that include managed agriculture exhibit significant time-dependent seasonal bias. This bias was linked to seasonal temperature cycle, which is a proxy to several features that can cause seasonally dependent errors in the SMAP product.

core validation site↗

L-band RFI Detected by SMOS and Aquarius

Ocean salinity and soil moisture are key parameters for understanding the global water cycle, weather, and climate. These parameters are being measured with spaceborne radiometers operating in the L-band window at 14001427 MHz. Although man-made activity in this band is prohibited, radio frequency interference (RFI) is still a problem over significant portions of the earth. This paper reports a comparison of the RFI environment in this window as observed by two L-band radiometer systems, Aquarius and Soil Moisture and Ocean Salinity. The observed RFI environment depends on the sources and also on the characteristics of the instrument. Comparing the observations provides insight into the extent of the problem (actual sources), the influence of the instrument on the observation of RFI, and on potential ways of mitigating the effects. As this report shows, the global distribution of RFI is largely consistent between the two instruments, but the details, especially at low levels of RFI, depend on the characteristics of the instrument.

microwave radiometry↗

A Preview of AMSR: Airborne C-band Microwave Radiometer (ACMR) Observations from SGP99

Although L-band is generally considered ideal for passive microwave sensing of soil moisture, near-future satellite observing systems such as Advanced Mechanically Scanned Radiometer (AMSR) will provide C-band data for several years before any L-band data might become available. The Southern Great Plains'99 (SGP99) Experiment was designed to generate C-band observations suitable for testing and refinement of AMSR-era soil moisture retrieval algorithms. C-band data collected using the Airborne C-band Microwave Radiometer (ACMR), a new high-accuracy NASA/GSFC instrument, clearly demonstrated a strong response to a 9-day drydown event as well as to differences between the northern (cooler & wetter) and southern (warmer & dryer) areas covered by the P-3 flights. For example, the H-polarized brightness temperatures observed during the first three days of the drydown increased up to 50 K in the northern areas. These observations represent a preview of what we can expect from AMSR, albeit at 3-km spatial resolution vs. approximately 60 km for AMSR. Initial results of soil-vegetation microwave modeling will also be presented to estimate the relative contributions of soil physical temperature, canopy physical temperature, soil moisture, and canopy moisture. Significant radio-frequency interference (RFI) was evident during the experiment, and amelioration strategies will be discussed. The net effect of RFI (an upward bias in brightnesses) when averaged over an AMSR footprint is expected to be more subtle.

Kim, Edward↗

Improved Calibration through SMAP RFI Change Detection

Anthropogenic Radio-Frequency Interference (RFI) drove both the SMAP (Soil Moisture Active Passive) microwave radiometer hardware and Level 1 science algorithm designs to use new technology and techniques for the first time on a spaceflight project. Care was taken to provide special features allowing the detection and removal of harmful interference in order to meet the error budget. Nonetheless, the project accepted a risk that RFI and its mitigation would exceed the 1.3-K error budget. Thus, RFI will likely remain a challenge afterwards due to its changing and uncertain nature. To address the challenge, we seek to answer the following questions: How does RFI evolve over the SMAP lifetime? What calibration error does the changing RFI environment cause? Can time series information be exploited to reduce these errors and improve calibration for all science products reliant upon SMAP radiometer data? In this talk, we address the first question.

Passive L-band radiometer↗

Evaluation of the Validated Soil Moisture Product from the SMAP Radiometer

NASA's Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAP's radiometer-derived soil moisture product (L2_SM_P) provides soil moisture estimates posted on a 36 km fixed Earth grid using brightness temperature observations from descending (6 am) passes and ancillary data. A beta quality version of L2_SM_P was released to the public in September, 2015, with the fully validated L2_SM_P soil moisture data expected to be released in May, 2016. Additional improvements (including optimization of retrieval algorithm parameters and upscaling approaches) and methodology expansions (including increasing the number of core sites, model-based intercomparisons, and results from several intensive field campaigns) are anticipated in moving from accuracy assessment of the beta quality data to an evaluation of the fully validated L2_SM_P data product.

Ocean Salinity↗

Soil moisture detection from Skylab

An investigation was designed for the Skylab satellite to determine the feasibility of remote sensing of the soil moisture content of the surface from various microwave sensors. Skylab data for the experiment were collected during passes 5, 10, 16, and 38 across the two test sites selected in eastern Kansas and western Texas. Pass 38 covered both test sites giving five data sets for the analysis. As Skylab data were being taken the moisture content of the soil was sampled by ground crews for each 2.5 centimeter depth from the surface to 15 centimeters at interval of about six kilometers along two different routes along the test sites. This resulted in a total of 2250 soil moisture samples corresponding to different locations and six different depths. Skylab data were collected by passive microwave radiometers at wavelengths of 2.1 and 21 centimeters by the S193 and S194 microwave sensors. An active microwave system also collected scatterometer data at a wavelength of 2.1 centimeters. The analysis of microwave data has revealed that the longer wavelength L-Band passive radiometer gives the best correlation with soil moisture content of the upper 2.5 centimeter depth of soil.

Eagleman, J. R.↗

Salinity surveys using an airborne microwave radiometer

The Barnes PRT-5 infrared radiometer and L-band channel of the multifrequency microwave radiometer are used to survey the distribution of surface water temperature and salinity. These remote sensors were flown repetitively in November 1971 over the outflow of the Mississippi River into the Gulf of Mexico. Data reduction parameters were determined through the use of flight data obtained over a known water area. With these parameters, the measured infrared and microwave radiances were analyzed in terms of the surface temperature and salinity.

Paris, J. F.↗