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NASA NTRS1993

A theoretical and numerical study of polarimetric scattering and emission from random rough surfaces with anisotropic directional spectrum

In this paper, theoretical and numerical results of the polarimetric scattering and emission from random rough surfaces with anisotropic directional spectrum are presented for the remote sensing of ocean and soil surfaces. The polarimetric scattered field for rough dielectric surfaces is derived to the second order by the small perturbation method (SPM). It is found that the second-order scattered field is coherent in nature, and its coefficients for different polarizations present the lowest-order corrections to the Fresnel reflection coefficients of the surfaces. In addition, the cross-polarized (HV and VH) components of the coherent fields are reciprocal and not zero for surfaces with anisotropic directional spectrum when the azimuth angle of the incident direction is not aligned with the symmetry directions of surfaces. In order to verify the energy conservation condition of the theoretical results, which is important if the theory is to be applied to the passive polarimetry of rough surfaces, a Monte Carlo simulation is performed to numerically calculate the polarimetric reflectivities of one-dimensional random rough surfaces which are generated with a prescribed power-law spectrum in the spectral domain and transformed to the spatial domain by the FFT. The surfaces simulated by this approach are periodic with the period corresponding to the low-wavenumber cutoff. To calculate the scattering from periodic dielectric surfaces, the authors present a new numerical technique which applies the Floquet theorem to reduce the problem to one period and does not require the evaluation of one-dimensional periodic Green's function used in the conventional method of moment formulation. Once the scattering coefficients are obtained, the polarimetric Stokes vectors for the emission from the random surfaces are then calculated according to the Kirchhoff's law and are illustrated as functions of relative azimuth observation and row directions. The second-order SPM is also reduced to this one-dimensional case, and theoretical results for all four Stokes parameters are in excellent agreement with the numerical results obtained from the Monte Carlo simulation. Moreover, the second order coherent fields are found to be necessary for the theoretical evaluation of the third and fourth Stokes parameters. Without that, the reflectivities of random rough surfaces are significantly over-estimated, and the signs of the third and the fourth Stokes parameters are found to be incorrect, if calculated by using the first-order incoherent fields alone.

Yueh, S. H.↗

NASA NTRS2012

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, 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 will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed 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 l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗

NASA NTRS1982

Effects of varying soil moisture contents and vegetation canopies on microwave emissions

Results of NASA airborne passive microwave scans of bare and vegetated fields for comparison with ground truth tests are discussed and a model for atmospheric scattering of radiation by vegetation is detailed. On-board radiometers obtained data at 21, 2.8, and 1.67 cm during three passes over each of 46 fields, 28 of which were bare and the others having wheat or alfalfa. Ground-based sampling included moisture in five layers down to 15 cm in addition to soil temperature. The relationships among the brightness temperature and soil moisture, as well as the surface roughness and the vegetation canopy were examined. A model was developed for the dielectric coefficient and volume scattering for a vegetation medium. L- to C-band data were found useful for retrieving soil information directly. A surface moisture content of 5-35% yielded an emissivity of 0.9-0.7. The data agreed well with a combined multilayer radiative transfer model with simple roughness correction.

Burke, H.-H. K.↗

NASA NTRS2004

Estimating Surface Soil Moisture in Simulated AVIRIS Spectra

Soil albedo is influenced by many physical and chemical constituents, with moisture being the most influential on the spectra general shape and albedo (Stoner and Baumgardner, 1981). Without moisture, the intrinsic or matrix reflectance of dissimilar soils varies widely due to differences in surface roughness, particle and aggregate sizes, mineral types, including salts, and organic matter contents. The influence of moisture on soil reflectance can be isolated by comparing similar soils in a study of the effects that small differences in moisture content have on reflectance. However, without prior knowledge of the soil physical and chemical constituents within every pixel, it is nearly impossible to accurately attribute the reflectance variability in an image to moisture or to differences in the physical and chemical constituents in the soil. The effect of moisture on the spectra must be eliminated to use hyperspectral imagery for determining minerals and organic matter abundances of bare agricultural soils. Accurate soil mineral and organic matter abundance maps from air- and space-borne imagery can improve GIS models for precision farming prescription, and managing irrigation and salinity. Better models of soil moisture and reflectance will also improve the selection of soil endmembers for spectral mixture analysis.

Whiting, Michael L.↗

NASA NTRS2007

RadSTAR L-Band Imaging Scatterometer: Performance Assessment

RadSTAR is an instrument development program aimed at combining a radiometer and a scatterometer system into a highly compact configuration that uses a single, electronically scanned antenna to provide co-located and simultaneous measurements of emission and backscatter for airborne and spaceborne applications [I]. The program was designed to map soil moisture and ocean salinity, both important components of the water cycle, and to map sea ice density and thickness, an important factor in ocean-atmosphere heat exchange in Polar Regions. The accuracy in estimation of these and a number of other Earth science parameters can be greatly enhanced by providing the co-aligned radar/radiometer microwave measurements. For instance, radiometer estimates of soil moisture from soil emission are affected by emission from vegetation, and from the roughness of the surface. Complementary measurements using the scatterometer can be used to evaluate the vegetation and surface roughness effects. Hence, the combined observations can provide an improved estimate. As with soil moisture, the ocean salinity is a function of the microwave emission from the sea surface temperature (SST) and sea roughness. There, the addition of radar backscatter measurements of sea roughness enables the correction of the emissivity and provide more accurate estimates of ocean salinity. Similar arguments can be made for other important Earth science parameters. This paper discusses the RadSTAR program, the radar system design, calibration, and digital beamforming techniques, and presents preliminary analysis of the data collected during the test flights. The data sets obtained during the flights and during the radar calibration in the anechoic chamber are also employed to asses the performance of the radar. The paper also discusses the Digital Beamforming Synthetic Aperture Radar (DBSAR) processor, a real-time processor recently developed for the LIS instrument which enables beam synthesis, fine resolutions, and large swaths.

Rincon, Rafael↗

NASA NTRS1982

Multifrequency remote sensing of soil moisture

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using 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. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index 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.

Theis, S. W.↗

NASA NTRS2009

Orion Landing Simulation Eight Soil Model Comparison

LS-DYNA finite element simulations of a rigid Orion Crew Module (CM) were used to investigate the CM impact behavior on eight different soil models. Ten different landing conditions, characterized by the combination of CM vertical and horizontal velocity, hang angle, and roll angle were simulated on the eight different soils. The CM center of gravity accelerations, pitch angle, kinetic energy, and soil contact forces were the outputs of interest. The simulation results are presented, with comparisons of the CM behavior on the different soils. The soils analyzed in this study can be roughly categorized as soft, medium, or hard, according to the CM accelerations that occur when landing on them. The soft group is comprised of the Carson Sink Wet soil and the Kennedy Space Center (KSC) Low Density Dry Sand. The medium group includes Carson Sink Dry, the KSC High Density In-Situ Moisture Sand and High Density Flooded Sand, and Cuddeback B. The hard soils are Cuddeback A and the Gantry Unwashed Sand. The softer soils were found to produce lower peak accelerations, have more stable pitch behavior, and to be less sensitive to the landing conditions. This investigation found that the Cuddeback A soil produced the highest peak accelerations and worst stability conditions, and that the best landing performance was achieved on the KSC Low Density Dry Sand.

Mark, Stephen D.↗

NASA NTRS1980

Remote sensing of soil moisture content over bare fields at 1.4 GHz frequency

A simple method of estimating moisture content (W) of a bare soil from the observed brightness temperature (T sub B) at 1.4 GHz is discussed. The method is based on a radiative transfer model calculation, which has been successfully used in the past to account for many observational results, with some modifications to take into account the effect of surface roughness. Besides the measured T sub B's, the three additional inputs required by the method are the effective soil thermodynamic temperature, the precise relation between W and the smooth field brightness temperature T sub B and a parameter specifying the surface roughness characteristics. The soil effective temperature can be readily measured and the procedures of estimating surface roughness parameter and obtaining the relation between W and smooth field brightness temperature are discussed in detail. Dual polarized radiometric measurements at an off-nadir incident angle are sufficient to estimate both surface roughness parameter and W, provided that the relation between W and smooth field brightness temperature at the same angle is known. The method of W estimate is demonstrated with two sets of experimental data, one from a controlled field experiment by a mobile tower and the other, from aircraft overflight. The results from both data sets are encouraging when the estimated W's are compared with the acquired ground truth of W's in the top 2 cm layer. An offset between the estimated and the measured W's exists in the results of the analyses, but that can be accounted for by the presently poor knowledge of the relationship between W and smooth field brightness temperature for various types of soils. An approach to quantify this relationship for different soils and thus improve the method of W estimate is suggested.

Wang, J. R.↗

NASA NTRS2018

Aiding in the Efforts of Bioregenerative Life Support for the Future Residents of Mars and Long-Duration Space Flights Plant Growth in Amended Martian Regolith Simulant

Currently, the goal of plant growth research at KSC (Kennedy Space Center) is to provide a sustainable source of healthy food on long-duration space flights so astronauts and future residents of Mars can get the nutrition they need and produce food, recycle the atmosphere, and aid in recycling water. The sustainable production of food will aid in the efforts of closed life support. Plants have a vital application for bioregenerative life support as demands for food and oxygen can be provided through photosynthesis, while the carbon dioxide from human respiration is removed. In order for a growing medium to provide for plant growth, it needs to provide support, oxygen, ions, and liquid to the plant. This summer research determines how amended Martian regolith simulant acts as a growing medium for plants through looking at the structural properties of each amendment. Mars is covered with regolith which is crushed volcanic rock that is composed of a high amount of perchlorate salts. The composition of Martian soil is such that it is roughly basaltic and consists of sulfur, nitrates, and oxychlorine species. Martian regolith simulants have been generated to further analyze plant growth and aim to replicate features of the reference sample. The JSC (Johnson Space Center) Mars-1A regolith simulant resembles Martian regolith at the Viking I landing site. The objectives of the research this summer at Kennedy Space Center are to devise a plant growth in amended JSC Mars-1A Martian regolith simulant and perform crop studies to assess the performance of full duration crop growth in amended Martian regolith simulant. This research will provide a deeper understanding of how the combination of soil amendments to Martian regolith has a synergistic effect on improving crop production The plant growth experiment will be completed with three treatments each containing inorganic and organic soil amendments.

Onsay, Daphne↗

NASA NTRS1997

Monitoring Land Surface Soil Moisture from Space with in-Situ Sensors Validation: The Huntsville Example

Based on recent advances in microwave remote sensing of soil moisture and in pursuit of research interests in areas of hydrology, soil climatology, and remote sensing, the Center for Hydrology, Soil Climatology, and Remote Sensing (HSCARS) conducted the Huntsville '96 field experiment in Huntsville, Alabama from July 1-14, 1996. We, researchers at the Global Hydrology and Climate Center's MSFC/ES41, are interested in using ground-based microwave sensors, to simulate land surface brightness signatures of those spaceborne sensors that were in operation or to be launched in the near future. The analyses of data collected by the Advanced Microwave Precipitation Radiometer (AMPR) and the C-band radiometer, which together contained five frequencies (6.925,10.7,19.35, 37.1, and 85.5 GHz), and with concurrent in-situ collection of surface cover conditions (surface temperature, surface roughness, vegetation, and surface topology) and soil moisture content, would result in a better understanding of the data acquired over land surfaces by the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer (AMSR), because these spaceborne sensors contained these five frequencies. This paper described the approach taken and the specific objective to be accomplished in the Huntsville '97 field experiment.

Wu, Steve Shih-Tseng↗

NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗

NASA NTRS1984

Microwave radiometer experiment of soil moisture sensing at BARC test site during summer 1981

Soil moisture was measured by truck mounted microwave radiometers at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz. The soil textures in the two test sites were different so that the soil type effect of microwave radiometric response could be studied. Several fields in each test site were prepared with different surface roughnesses and vegetation covers. Ground truth on the soil moisture, temperature, and the biomass of the vegetation was acquired in support of the microwave radiometric measurements. Soil bulk density for each of the fields in both test sites was sampled. The soils in both sites were measured mechanically and chemically. A tabulation of the measured data is presented and the sensors and operational problems associated with the measurements are discussed.

Wang, J.↗

NASA NTRS2022

Analysis of the Smap Roughness Parameter and the Smap Vegetation Optical Depth

The SMAP product provides the soil moisture (SM) computed using three different retrieval algorithms: the single channel H and V algorithms (SCA-H and SCA-V), and the dual-channel algorithm (DCA) which in addition provides the vegetation optical depth (VOD). The roughness model and the roughness parameters play an important role in the determination of the soil moisture and the VOD. In this regard, the SMAP SCA and DCA utilize different approaches to incorporate the effect of roughness. In this work we will summarize those approaches and we will evaluate the effect of the DCA approach on the retrieval of VOD. We will compare the SMAP DCA roughness parameter h with topographic parameters such as DEM height, DEM slope, DEM height standard deviation and DEM slope standard deviation.

Mousavi, M.↗

NASA NTRS1980

System calibration of the 1.4 GHz and 5 GHz radiometers for soil moisture remote sensing

Two microwave radiometers at the frequencies of 1.4 GHz and 5 GHz were mounted on a mobile tower and used for a remote sensing of soil moisture experiment at a Beltsville Agriculture Research Center test site. The experiment was performed in October 1979 over both bare field and fields covered with grass, soybean, and corn. The calibration procedure for the radiometer systems which forms the basis of obtaining the final radiometric data product is described. It is estimated from the calibration results that the accuracy of the 1.4 GHz radiometric measurements is about + or - 3 K. The measured 5 GHz brightness temperatures over bare fields with moisture content greater than 10 percent by dry weight are about 8 K lower than those taken simultaneously at 1.4 GHz. This could be due to either (1) a 5 GHz antenna side lobe seeing the cold brightness of the sky, or (2) the thermal microwave emission from a soil being less sensitive to surface roughness at 5 GHz than at 1.4 GHz.

Wang, J.↗

NASA NTRS1981

A study of model parameters associated with the urban climate using HCMM data

The use of infrared and visible data from the Heat Capacity Mapping Mission (HCMM) and in situ data to study the intensity of the urban heat island of Saint Louis is described. Analysis of HCMM data shows that an urban heat island exists day and night in all seasons when clear skies prevail. The lower albedo value of the urban region during the day suggests that the higher temperatures are due to more absorption of solar radiation. Preliminary analysis of in situ meteorological data was performed after merging with HCMM data, and surface roughness, the exchange coefficient, and the soil moisture were calculated.

Source record↗

NASA NTRS1982

Radiometer mission requirements for large space antenna systems

Requirements are defined for Earth observational microwave radiometry using large space antenna systems with apertures in the 50 to 200 meter range. General Earth observational needs, specific measurement requirements, orbital mission guidelines and constraints, and general radiometric requirements are defined. Specific measurements include soil moisture, water surface temperature, water roughness, ice boundaries, salinity, and water pollutants. Measurements with 10 to 1 km spatial resolution and 3 to 1 day temporal resolution are required.

Keafer, L. S., Jr.↗

NASA NTRS1992

An empirical model and an inversion technique for radar scattering from bare soil surfaces

Polarimetric radar measurements were conducted for bare soil surfaces under a variety of roughness and moisture conditions at L-, C-, and X-band frequencies at incidence angles ranging from 10 to 70 deg. Using a laser profiler and dielectric probes, a complete and accurate set of ground truth data were collected for each surface condition, from which accurate measurements were made of the rms height, correlation length, and dielectric constant. Based on knowledge of the scattering behavior in limiting cases and the experimental observations, an empirical model was developed which was found to yield very good agreement with the backscattering measurements of this study, as well as with measurements reported in other investigations. An inversion technique for predicting the rms height of the surface and its moisture content from multipolarized radar observations is developed on the basis of the model.

Oh, Yisok↗

NASA NTRS2004

Estimation of Soil Moisture with L-band Multi-polarization Radar

Through analyses of the model simulated data-base, we developed a technique to estimate surface soil moisture under HYDROS radar sensor (L-band multi-polarizations and 40deg incidence) configuration. This technique includes two steps. First, it decomposes the total backscattering signals into two components - the surface scattering components (the bare surface backscattering signals attenuated by the overlaying vegetation layer) and the sum of the direct volume scattering components and surface-volume interaction components at different polarizations. From the model simulated data-base, our decomposition technique works quit well in estimation of the surface scattering components with RMSEs of 0.12,0.25, and 0.55 dB for VV, HH, and VH polarizations, respectively. Then, we use the decomposed surface backscattering signals to estimate the soil moisture and the combined surface roughness and vegetation attenuation correction factors with all three polarizations.

Shi, J.↗