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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Evaluation and Application of Remotely Sensed Soil Moisture Products

Whereas in-situ measurements of soil moisture are very accurate, achieving accurate regional soil moisture estimates derived solely from point measurements is difficult because of the dependence upon the density of the gauge network and the proper upkeep of these instruments, which can be costly. Microwave remote sensing is the only technology capable of providing timely direct measurements of regional soil moisture in areas that are lacking in-situ networks. Soil moisture remote sensing technology is well established has been successfully applied in many fashions to Earth Science applications. Since the microwave emission from the soil surface has such a high dependency upon the moisture content within the soil, we can take advantage of this relationship and combined with physically-based models of the land surface, derive accurate regional estimates of the soil column water content from the microwave brightness temperature observed from satellite-based remote sensing instruments. However, there still remain many questions regarding the most efficient methodology for evaluating and applying satellite-based soil moisture estimates. As discussed below, we to use satellite-based estimates of soil moisture dynamics to improve the predictive capability of an optimized hydrologic model giving more accurate root-zone soil moisture estimates.

Bolten, J.↗
NASA NTRS2020

Toward P-Band Passive Microwave Sensing of Soil Moisture

Currently, near-surface soil moisture at a global scale is being provided using National Aeronautics and Space Administration’s (NASA’s) Soil Moisture Active Passive (SMAP) and European Space Agency’s (ESA’s) Soil Moisture and Ocean Salinity (SMOS) satellites, both of which utilize L-band (1.4 GHz; 21 cm wavelength ) passive microwave remote sensing techniques. However, a fundamental limitation of this technology is that the water content can only be measured for approximately the top 5-cm layer of soil moisture, and only over low-to-moderate vegetation covered areas in order to meet the 0.04 m3/m3 target accuracy, limiting its applicability. Consequently, a longer wavelength radiometer is being explored as a potential solution for measuring soil moisture in a deeper surface layer of soil and under denser vegetation. It is expected that P-band ( wavelength of 40 cm and frequency of 750 MHz) could potentially provide soil moisture information for the top 10-cm layer of soil, being one-tenth to one-quarter of the wavelength. In addition, P-band is expected to have higher soil moisture retrieval accuracy due to its reduced sensitivity to vegetation water content and surface roughness. To demonstrate the potential of P-band passive microwave soil moisture remote sensing, a short-term airborne field experiment was conducted over a center pivot irrigated farm at Cressy in Tasmania, Australia, in January 2017. First results showing a comparison of airborne P-band brightness temperature observations against airborne L-band brightness temperature observations and ground soil moisture measurements are presented. The P-band brightness temperature was found to have a similar but stronger response to soil moisture compared to L-band.

Nan Ye↗
NASA NTRS1985

Remote Sensing of Earth Terrain

The objective of this research is to develop theoretical models that are useful and practical in the remote sensing of the Earth environment including the Earth terrain, the lower and the upper atmospheres. Various models applicable to the microwave remote sensing of vegetation, snow-ice, and atmospheric precipitation have been developed. Such studies shall be extended to the higher frequency range to unify the optical band and the microwave theoretical foundations. The study, which had an emphasis on vegetation canopy to include all terrain media, and the whole Earth environment will be extended. A data base will be developed to generate scene radiation characteristics which will benefit the studies of global inhabitability, meteorological applications, and crop yield.

Kong, J. A.↗
NASA NTRS1981

Radiative transfer theory for active remote sensing of a homogeneous layer containing spherical scatterers

The radiative transfer theory with a Rayleigh scattering model is used to study the effect of volume scattering for active microwave remote sensing of low-loss and scattering dominant areas by obtaining backscattering cross sections through iterative and numerical approaches. The iterative approach gives closed form solutions which are valid when the effect of scattering is small. The depolarization of the backscattered power is shown to be a second-order effect. For the general cases, a numerical approach is used to solve the radiative transfer equations. The theoretical results are compared and illustrated for the various cases.

Shin, R. T.↗
NASA NTRS1986

Development of EOS-aided procedures for the determination of the water balance of hydrologic budget of a large watershed

Work focused on the acquisition of remotely sensed data for the 1985 to 1986 hydrogolic year; continuation of the field measurement program; continued acquisition and construction of passive microwave remote sensing instruments; a compilation of data necessary for an initial water balance computation; and participation with the EOS Simulataneity Team in reviewing the Feather River watershed as a possible site for a simultaneity experiment.

Congalton, Russell G.↗
NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗
NASA NTRS2004

Hydrological Application of Remote Sensing: Surface States -- Snow

Remote sensing research of snow cover has been accomplished for nearly 40 years. The use of visible, near-infrared, active and passive-microwave remote sensing for the analysis of snow cover is reviewed with an emphasis on the work on the last decade.

Hall, Dorothy K.↗
NASA NTRS2004

Comparison of Local Scale Measured and Modeled Brightness Temperatures and Snow Parameters from the CLPX 2003 by Means of a Dense Medium Radiative Transfer Theory Model

Microwave remote sensing offers distinct advantages for observing the cryosphere. Solar illumination is not required, and spatial and temporal coverage are excellent from polar-orbiting satellites. Passive microwave measurements are sensitive to the two most useful physical quantities for many hydrological applications: physical temperature and water content/state. Sensitivity to the latter is a direct result of the microwave sensitivity to the dielectric properties of natural media, including snow, ice, soil (frozen or thawed), and vegetation. These considerations are factors motivating the development of future cryospheric satellite remote sensing missions, continuing and improving on a 26-year microwave measurement legacy. Perhaps the biggest issues regarding the use of such satellite measurements involve how to relate parameter values at spatial scales as small as a hectare to observations with sensor footprints that may be up to 25 x 25 km. The NASA Cold-land Processes Field Experiment (CLPX) generated a dataset designed to enhance understanding of such scaling issues. CLPX observations were made in February (dry snow) and March (wet snow), 2003 in Colorado, USA, at scales ranging from plot scale to 25 x 25 km satellite footprints. Of interest here are passive microwave observations from ground-based, airborne, and satellite sensors, as well as meteorological and snowpack measurements that will enable studies of the effects of spatial heterogeneity of surface conditions on the observations. Prior to performing such scaling studies, an evaluation of snowpack forward modelling at the plot scale (least heterogeneous scale) is in order. This is the focus of this paper. Many forward models of snow signatures (brightness temperatures) have been developed over the years. It is now recognized that a dense medium radiative transfer (DMRT) treatment represents a high degree of physical fidelity for snow modeling, yet dense medium models are particularly sensitive to snowpack structural parameters such as grain size, density, and depth---parameters that may vary substantially within a snowpack. Microwave radiometric data and snow pit measurements collected at the Local-Scale Observation Site (LSOS) during the third Intensive Observation Period (IOP3) of the CLPX have been used to test the capabilities of a DMRT model using the Quasi Crystalline Approximation with Coherent Potential (QCA-CP). The radiometric measurements were made by the University of Tokyo s Ground Based Microwave Radiometer-7 (GBMR-7) system. We evaluate the degree to which a DMRT-based model can accurately reproduce the GBMR-7 brightness temperatures at different frequencies and incidence angles.

Tedescol, Marco↗
NASA NTRS1987

Radar scene generation for tactical decision aids

The Mueller matrix and polarization covariance matrix for polarimetric radar systems was studied. The clutter is modeled by a layer of random permittivity, described by a three-dimensional correlation function, with variance, and horizontal and vertical correlation lengths. A general mixing formula was derived for discrete scatters immersed in a host medium. The results are applicable to general multiphase mixtures. The strong fluctuation theory was used to derive the backscattering cross sections, and was further extended to include higher order co-polarized and cross-polarized moments. A two-layer anisotropic random medium model was developed for the active and passive remote sensing of ice fields. A three-layer random medium model was adopted to study the volume scattering effects for the active and passive microwave remote sensing of snow-covered ice fields. The snow layer was simulated by an isotropic random medium and the ice layer by an anisotropic random medium. The vegetation canopy and snow-covered ice field were studied with a three-layer model, an isotropic random medium layer overlying an anisotropic random medium. The dyadic Green's function of the three-layer medium and the scattered electromagnetic intensities with Born approximation were calculated.

Kong, J. A.↗
NASA NTRS1990

Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Kong, Jin AU↗
NASA NTRS1994

Integration of remote sensing and hydrologic modeling through multi-disciplinary semiarid field campaigns: Moonsoon 1990, Walnut Gulch 1992, and SALSA-MEX

A research and modeling strategy is presented for development of distributed hydrologic models given by a combination of remotely sensed and ground based data. In support of this strategy, two experiments Moonsoon'90 and Walnut Gulch'92 were conducted in a semiarid rangeland southeast of Tucson, Arizona, (U.S.) and a third experiment, the SALSA-MEX (Semi Arid Land Surface Atmospheric Mountain Experiment) was proposed. Results from the Moonsoon'90 experiment substantially advanced the understanding of the hydrologic and atmospheric fluxes in an arid environment and provided insight into the use of remote sensing data for hydrologic modeling. The Walnut Gulch'92 experiment addressed the seasonal hydrologic dynamics of the region and the potential of combined optical microwave remote sensing for hydrologic applications. SALSA-MEX will combine measurements and modeling to study hydrologic processes influenced by surrounding mountains, such as enhanced precipitation, snowmelt and recharge to ground water aquifers. The results from these experiments, along with the extensive experimental data bases, should aid the research community in large scale modeling of mass and energy exchanges across the soil-plant-atmosphere interface.

Moran, M. S.↗
NASA NTRS1995

Observations of polar ice using enhanced resolution microwave scatterometer data

Increasing interest in the role of ice sheets in regulating global climate has created a need for synoptic interannual recording and monitoring of the earth's major ice sheets. Based on their ability to 'see' into ice, microwave remote sensing instruments are well-suited for monitoring the polar regions. Although microwave radar has increased capabilities over some aspects of visible wavelength systems, there are tradeoffs between spatial and temporal resolution. Synthetic aperture radar (SAR) can make high resolution images, but is limited in ground coverage over polar regions because of high data rates and a lack of receiving stations. Microwave scatterometers, originally designed for measuring winds over the ocean, are capable of greater ground coverage in polar regions, but are inherently low resolution instruments. However, a recently developed resolution enhancement technique can generate enhanced resolution scatterometer images. In this paper the algorithm is applied to create enhanced resolution images from Seasat and ERS-1 scatterometer data over. Time series of medium-scale radar images for Greenland and Antarctica and the surrounding seas are presented. The growth and shrinkage of the southern polar sea-ice throughout a full annual cycle is illustrated with the seasonal cycle of patterns on the Antarctic and Greenland Ice Sheets clearly evident. Using the time series and simple scattering models, the locations of key ice facies in Greenland are determined.

Long, David G.↗
NASA NTRS2001

Passive Microwave Measurements of Salinity: The Gulf Stream Experiment

Passive microwave sensors at L-band (1.4 GHz) operating from aircraft have demonstrated that salinity can be measured with sufficient accuracy (I psu) to be scientifically meaningful in coastal waters. However, measuring salinity in the open ocean presents unresolved issues largely because of the much greater accuracy (approximately 0.2 psu) required of global maps to be scientifically viable. The development of a satellite microwave instrument to make global measurements of SSS (Sea Surface Salinity) is the focus of a joint JPL/GSFC/NASA ocean research program called Aquarius. In the summer of 1999 a series of measurements called, The Gulf Stream Experiment, were conducted as part of research at the Goddard Space Flight Center to test the potential for passive microwave remote sensing of salinity in the open ocean. The measurements consisted of airborne microwave instruments together with ships and drifters for surface truth. The study area was a 200 km by 100 km rectangle about 250 km east of Delaware Bay between the continental shelf waters and north wall of the Gulf Stream. The primary passive instruments were the ESTAR radiometer (L-band, H-pol) and the SLFMR radiometer (L-band, V-pol). In addition, the instruments on the aircraft included a C-band radiometer (ACMR), an ocean wave scatterometer (ROWS) and an infrared radiometer (for surface temperature). These instruments were mounted on the NASA P-3 Orion aircraft. Sea surface measurements consisted of thermosalinograph data provided by the R/V Cape Henlopen and the MN Oleander, and data from salinity and temperature sensors on three surface drifters deployed from the R/V Cape Henlopen. The primary experiment period was August 26-September 2, 1999. During this period the salinity field within the study area consisted of a gradient on the order of 2-3 psu in the vicinity of the shelf break and a warm core ring with a gradient of 1-2 psu. Detailed maps were made with the airborne sensors on August 28 and 29 and on September 2 flights were made over the surface drifters to look for effects due to a change in surface roughness resulting from the passage of Hurricane Dennis. Results show a good agreement between the microwave measurements and ship measurements of salinity. The features of the brightness temperature maps correspond well with the features of the salinity field measured by the ship and drifters and a preliminary retrieval of salinity compares well with the ship data.

LeVine, D. M.↗
NASA NTRS1982

The NASA Radar Remote Sensing Program

The NASA radar remote sensing program is structured to conduct scientific research for earth and planetary exploration using the microwave spectrum. The program began in 1966 and has since developed a complement of radar sensors for satellite, aircraft and ground-based platforms which have been used in both land and oceanic research. Basic measurements of radar scattering coefficient signatures are carried out with airborne and ground-based scatterometers. SAR imagery is being used for geological, hydrological, geographical, and agricultural microwave remote sensing research. For oceanic investigations, altimeters are used for ocean topography experiments and scatterometers for ocean wind and current research. Future satellite radar instruments being proposed include SIR-B, SAMEX, FIREX, TOPEX and a Scatterometer Experiment.

Carver, K. R.↗
NASA NTRS2020

Evaluation of long-term Northern Hemisphere snow water equivalent products

Nine gridded Northern Hemisphere snow water equivalent (SWE) products were evaluated as part of the European Space Agency (ESA) Satellite Snow Product Intercomparison and Evaluation Exercise (SnowPEx). Three categories of datasets were assessed: (1) those utilizing some form of reanalysis (the NASA Global Land Data Assimilation System version 2 – GLDAS-2; the European Centre for Medium-Range Weather Forecasts (ECMWF) interim land surface reanalysis – ERA-Interim/Land and ERA5; the NASA Modern-Era Retrospective Analysis for Research and Applications version 1 (MERRA) and version 2 (MERRA-2); the Crocus snow model driven by ERA-Interim meteorology – Crocus); (2) passive microwave remote sensing combined with daily surface snow depth observations (ESA GlobSnow v2.0); and (3) stand-alone passive microwave retrievals (NASA AMSR-E SWE versions 1.0 and 2.0) which do not utilize surface snow observations. Evaluation included validation against independent snow course measurements from Russia, Finland, and Canada and product intercomparison through the calculation of spatial and temporal correlations in SWE anomalies. The stand-alone passive microwave SWE products (AMSR-E v1.0 and v2.0 SWE) exhibit low spatial and temporal correlations to other products and RMSE nearly double the best performing product. Constraining passive microwave retrievals with surface observations (GlobSnow) provides performance comparable to the reanalysis-based products; RMSE over Finland and Russia for all but the AMSR-E products is ∼50 mm or less, with the exception of ERA-Interim/Land over Russia. Using a seven-dataset ensemble that excluded the stand-alone passive microwave products reduced the RMSE by 10 mm (20 %) and increased the correlation from 0.67 to 0.78 compared to any individual product. The overall performance of the best multiproduct combinations is still at the margins of acceptable uncertainty for scientific and operational requirements; only through combined and integrated improvements in remote sensing, modeling, and observations will real progress in SWE product development be achieved.

Northern Hemisphere snow water equivalent (SWE) pr↗
NASA NTRS1982

Global maps of oceanographic and atmospheric parameters from the Seasat SMMR

The Seasat satellite was launched by the U.S. in June 1978, to demonstrate techniques for, and the utility of, microwave remote sensing of the ocean surface. One of the instruments on board was a scanning multichannel microwave radiometer (SMMR), designed to measure primarily ocean surface temperature, ocean surface wind speed, atmospheric water vapor and cloud liquid water. Global maps of these parameters have been produced, representing 10-day, monthly and mission (90-day) averages of the radiometer measurements. These maps are compared with those derived from conventional surface measurements, and demonstrate the day and night, nearly all-weather capabilities of the microwave measurements.

Njoku, E. G.↗
NASA NTRS2000

Salinity Measurements During the Gulf Stream Experiment

The salinity of the open ocean is important for understanding ocean circulation, for understanding energy exchange with the atmosphere and for improving models to predict weather and climate. Passive microwave sensors at L-band (1.4 GHz) operating from aircraft have demonstrated that salinity can be measured with sufficient accuracy (1 psu) to be scientifically meaningful in coastal waters. However, measuring salinity in the open ocean presents unresolved issues largely because of the much greater accuracy (approx. 0.1 psu) required to be scientifically viable. In the summer of 1999 a series of measurements called, The Gulf Stream Experiment, were conducted as part of research at the Goddard Space Flight Center to test the potential for passive microwave remote sensing of salinity in the open ocean. The measurements consisted of a compliment of airborne microwave instruments (radiometers and scatterometer) and ships and drifters for surface truth. The study area was a 200 km by 100 km rectangle about 250 km east of Delaware Bay between the continental shelf waters and north wall of the Gulf Stream. The primary passive instruments were the ESTAR radiometer (L-band, H-pol) and the SLFMR radiometer (L-band, V-pol). In addition, the compliment of instruments on the aircraft included a C-band radiometer (ACMR), an ocean wave scatterometer (ROWS) and an infrared radiometer. A GPS backscatter experiment was also part of the package. These instruments were mounted on the NASA P-3 Orion aircraft. Surface salinity measurements were provided by the RN Cape Henlopen and MN Oleander (thermosalinographs) plus salinity and temperature sensors on three surface drifters deployed from the RN Cape Henopen. The primary experiment period was August 26-September 2, 1999. During this period the salinity field within the study area consisted of a gradient on the order of 2-3 psu in the vicinity of the shelf break and a warm core ring with a gradient of 1-2 psu. Detailed maps were made with the airborne sensors on August 28 and 29 and on September 2 flights were made over the surface drifters to look for effects due to a change in surface roughness resulting from the passage of Hurricane Dennis. Preliminary results show a good agreement between the microwave measurements and ship measurements of salinity. The features of the brightness temperature maps correspond well with the features of the salinity field measured by the ship and drifters and a preliminary retrieval of salinity compares well with the ship data.

LeVine, D. M.↗