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At least 19 records

A Performance Analysis on Soil Dielectric Models Over Organic Soils in Alaska for Passive Microwave Remote Sensing of Soil Moisture

Passive microwave remote sensing of soil moisture (SM) requires a physically based dielectric model that quantitatively converts the volumetric SM into the soil bulk dielectric constant. Mironov 2009 is the dielectric model used in the operational SM retrieval algorithms of the NASA Soil Moisture Active Passive (SMAP) and the ESA Soil Moisture and Ocean Salinity (SMOS) missions. However, Mironov 2009 suffers a challenge in deriving SM over organic soils, as it does not account for the impact of soil organic matter (SOM) on the soil bulk dielectric constant. To this end, we presented a comparative performance analysis of nine advanced soil dielectric models over organic soil in Alaska, four of which incorporate SOM. In the framework of the SMAP single-channel algorithm at vertical polarization (SCA-V), SM retrievals from different dielectric models were derived using an iterative optimization scheme. The skills of the different dielectric models over organic soils were reflected by the performance of their respective SM retrievals, which was measured by four conventional statistical metrics, calculated by comparing satellite-based SM time series with in-situ benchmarks. Overall, SM retrievals of organic-soil-based dielectric models tended to overestimate, while those from mineral-soil-based models displayed dry biases. All the models showed comparable values of unbiased root-mean-square error (ubRMSE) and Pearson Correlation (R), but Mironov 2019 exhibited a slight but consistent edge over the others. An integrated consideration of the model inputs, the physical basis, and the validated accuracy indicated that the separate use of Mironov 2009 and Mironov 2019 in the SMAP SCA-V for mineral soils (SOM < 15%) and organic soils (SOM ≥ 15%) would be the preferred option.

Soil Moisture↗

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Tsang, Leung↗

Systems for passive microwave remote sensing and their calibration methods

A system for passive microwave remote sensing using at least one microwave radiometer includes a fixed body portion and a mobile body portion. The mobile body portion is configured for rotatably coupling with the fixed body portion for rotation about a rotation axis. The mobile body portion is configured for supporting the microwave radiometer therein such that the microwave radiometer rotates about the rotation axis when the mobile body portion is rotated about the rotation axis such that a polarization axis of the radiometer is aligned with an earth axis. The fixed body portion includes a motor mechanism for effecting rotation of the mobile body portion. In an embodiment, the mobile body portion includes a plurality of body section, each body section being configured for supporting a microwave radiometer therein. In another embodiment, each one of the plurality of body sections is configured to be interchangeably coupled with each other.

47 OTHER INSTRUMENTATION↗

Systems for passive microwave remote sensing and their calibration methods

A system for passive microwave remote sensing using at least one microwave radiometer includes a fixed body portion, the fixed body portion being configured to attach to a mobile platform, and a mobile body portion, the mobile body portion being configured for rotatably coupling with the fixed body portion for rotation about a rotation axis. The mobile body portion is configured for supporting the at least one microwave radiometer therein such that the at least one microwave radiometer rotates about the rotation axis when the mobile body portion is rotated about the rotation axis such that a polarization axis of the at least one radiometer is aligned with an earth axis. The fixed body portion includes a motor mechanism for effecting rotation of the mobile body portion such that the at least one microwave radiometer provides a vertical scanning below and above the mobile platform.

Klein, Marian↗

Modeling the Effect of Vegetation on Passive Microwave Remote Sensing of Soil Moisture

The effect of vegetation on passive microwave remote sensing of soil moisture is studied. The radiative transfer modeling work of Njoku and Kong is applied to a stratified medium of which the upper layer is treated as a layer of vegetation. An effective dielectric constant for this vegetation layer is computed using estimates of the dielectric constant of individual components of the vegetation layer. The horizontally-polarized brightness temperature is then computed as a function of the incidence angle. Model predictions are used to compare with the data obtained in the Huntsville '96, remote sensing of soil moisture experiment, and with predictions obtained using a correction procedure of Jackson and Schmugge.

Liu, Y. P.↗

Passive microwave remote sensing of the ocean - A review

This paper reviews the current status of passive microwave remote sensing of the ocean. The physics of emission and instrumentation are highlighted in order to establish a relationship between the thermal emission and retrieved geophysical parameters. A discussion then follows on measurements of temperature, salinity, windspeed, etc. using passive microwave systems. These measurements are related to the accuracy and spatial resolution required by the users. The status of passive microwave remote sensing is summarized and recommendations for future research are presented.

Swift, C. T.↗

Implications of RFI at L-Band on Passive Microwave Remote Sensing of Soil Moisture from Space: Experience with ESTAR During SGP97

Passive microwave remote sensing in the protected band at 1.413 GHz (L-band) is important for monitoring parameters of the ocean and land surface such as soil moisture and sea surface salinity. These parameters are needed for understanding energy exchange between the surface and atmosphere and therefore are important for improving our understanding of weather and climate change. Although the band at 1.413 GHz is protected for passive use, airborne radiometers experience problems with RFI. For example, during the Southern Great Plains Experiment (1997) the ESTAR radiometer experienced significant RFI associated with airports, presumably air traffic control radar. This is a potential problem for future sensors in space planned for remote sensing of the earth surface in this frequency band.

LeVine, David M.↗

Inversion of passive microwave remote sensing data from satellites

Global passive microwave observations from earth-orbiting satellites have mapped humidity and liquid water over ocean, temperature profiles, ice and snow, and other geophysical parameters. In most applications, the inversion problem is adequately approximated as linear with jointly Gaussian statistics, and, thus, a linear retrieval performs well. In some cases, the problem is typically factored into a decision process followed by appropriate linear or quasilinear processes. Certain problems, however, require more powerful nonlinear or nonstationary procedures, such as Kalman filtering.

Staelin, D. H.↗

Progress in passive microwave remote sensing - Nonlinear retrieval techniques

A variety of nonlinear retrieval methods have been applied to passive microwave remote sensing problems. These problems can be characterized in part by the degree to which their underlying physics and statistics can be understood and characterized in a simple way. Four examples of varying complexity are considered here; the simplest problem requires only analytic expressions for retrievals, whereas the most complex problem has been handled only with pattern classification techniques. The four examples are: (1) Doppler measurements of winds at 70 to 100 km, (2) retrieval of atmospheric water vapor profiles using the opaque 183-GHz water vapor resonance, (3) retrieval of snow accumulation rate by means of combined theoretical and empirical procedures, and (4) classification of diverse polar terrain by means of pattern recognition techniques.

Staelin, D. H.↗

Passive microwave remote sensing for meteorology

The use of passive microwave techniques for the systematic geophysical monitoring of earth from aircraft and space is briefly reviewed. These techniques employ frequencies from approximately 1-300 GHz and have yielded information about atmospheric temperature, composition, and wind profiles. In particular, the application of passive microwave technology to temperature profile determination using the Nimbus 5 and 6 satellites, as well as the Tiros-N operational satellites and the Block 5D satellites, is presented.

Staelin, D. H.↗

Synergic inversion technique for active and passive microwave remote sensing of the ocean

A unified approach for combining active and passive microwave measurements for remote sensing applications is described. A synergic inversion technique has been developed and applied to the retrieval of geophysical parameters of the ocean surface and of the atmosphere. It is based on the combination of radiometric and radar measurements at the electromagnetic and cell level and not only on the correction of radar measurements by radiometric measurements, or conversely. Such a combination is performed through a common quantity: the bistatic scattering coefficient of the observed surface. This is used in a direct model to simulate combined measurements from active and passive sensors. It requires a rather complete and accurate calculation of the scattering of microwaves by the rough sea surface. Comparisons with experimental models derived for scatterometers and radar altimeters or with data derived from radiometric measurements show that the results of this unified approach are consistent with those from separate microwave sensors, at least for a foam-free sea surface.

Sobieski, Piotr↗

Passive microwave remote sensing of an anisotropic random-medium layer

The principle of reciprocity is invoked to calculate the brightness temperatures for passive microwave remote sensing of a two-layer anisotropic random medium. The bistatic scattering coefficients are first computed with the Born approximation and then integrated over the upper hemisphere to be subtracted from unity, in order to obtain the emissivity for the random-medium layer. The theoretical results are illustrated by plotting the emissivities as functions of viewing angles and polarizations. They are used to interpret remote sgnsing data obtained from vegetation canopy where the anisotropic random-medium model applies. Field measurements with corn stalks arranged in various configurations with preferred azimuthal directions are successfully interpreted with this model.

Lee, J. K.↗

Theory and experiment for passive microwave remote sensing of snowpacks

Both the theory and experiment for the passive remote sensing of snow with microwave radiometers have been studied. The volume scattering effects of snow are accounted for by incorporating Mie scattering theory into a radiative transfer model. The theory is applied to the interpretation of experimental data obtained from various snow measurements. The spectral and angular dependences of the brightness temperatures are illustrated and show good agreement between the theory and experiment. Brightness temperatures as a function of snow depths are also interpreted and discussed. It is observed that as the snow depth increases, the brightness temperature increases when the subsurface is an aluminum plate due to the fact that the plate is cold and snow absorption induces a brightening effect and the brightness temperature decreases when the subsurface is soil due to the fact that snow scattering induces darkening effects.

Kong, J. A.↗

The Fourth Stokes Parameter for Geolocation in Passive Microwave Remote Sensing from Space

Polarimetric microwave radiometers such as SMAP are capable of measuring the fourth Stokes parameter in brightness temperature over the Earth surface. The value of this parameter is normally small but exhibits sharp spikes when the scene includes large differences in emission from the surface, such occur at land/water boundaries. In this manuscript, it is shown that these spikes can be used to accurately locate coastlines with potential application to geolocation in passive microwave remote sensing from space. Examples are presented using the L-band radiometer on SMAP, first with theory using calculations with the SMAP antenna pattern and orbit and then with SMAP measurements of the fourth Stokes parameter over Madagascar. Using the SMAP data, the coastline is located with a standard deviation less than 2 km. The results are consistent with the conventional approach used for geolocation of the SMAP radiometer footprint.

Passive Microwave Remote Sensing↗

Ground-Based Passive Microwave Remote Sensing Observations of Soil Moisture at S and L Band with Insight into Measurement Accuracy

Accurate estimates of spatially heterogeneous algorithm variables and parameters are required in determining the spatial distribution of soil moisture using radiometer data from aircraft and satellites. A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, Alabama from July 1-14, 1996 to study retrieval algorithms and their sensitivity to variable and parameter specification. With high temporal frequency observations at S and L band, we were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cubic centimeter/cubic centimeter with an indication of a shallower emitting depth at higher moisture values. Surface moisture behavior was less apparent on the vegetated plots than it was on the bare plot because there was less moisture gradient and because of difficulty in determining vegetation water content and estimating the vegetation b parameter. Discrepancies between remotely sensed and gravimetric, soil moisture estimates on the vegetated plots point to an incomplete understanding of the requirements needed to correct for the effects of vegetation attenuation. Quantifying the uncertainty in moisture estimates is vital if applications are to utilize remotely-sensed soil moisture data. Computations based only on the real part of the complex dielectric constant and/or an alternative dielectric mixing model contribute a relatively insignificant amount of uncertainty to estimates of soil moisture. Rather, the retrieval algorithm is much more sensitive to soil properties, surface roughness and biomass.

Laymon, Charles A.↗