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At least 415 records · Page 23

Microwave Mixing and if Bandwidth in Sub-Micron Long High -T(sub c) Hot - Electron Bolometers

The hot-electron bolometer (HEB) mixer made from a high-T(sub c) superconductor (HTS) was introduced recently as a competing alternative to a Schottky mixer. The HEB mixer would require 100-times less LO power and thus would be a desirable candidate for long-term observational missions such as atmospheric remote-sensing and planetary science. The required cooling temperatures between 65 K and 75 K can be achieved with available space-qualified coolers or even with passive radiative coolers.

Harnack, Oliver↗

Theoretical models for microwave snow response and applications to remote sensing

Two theoretical models were developed to characterize snowpacks: (1) a random medium with a variance, a horizontal correlation length, and a vertical correlation length; and (2) a homogeneous dielectric containing discrete scatters. Theoretical results were matched with experimental data collected from snow ice fields. For snow ice fields the horizontal correlation length is no less than the vertical correlation length signifying a more laminar structure. The correspondence between the continuum random medium and the discrete spherical scatter model can be verified when the vertical correlation length is equal to the horizontal correlation length. The vertically polarized backscattering cross section sigma (sub vv) is always greater than the horizontally polarized backscattering cross section sigma (sub hh) for half space scattering media and may become smaller for a two layer model. In order to account for diurnal change exhibited by snow fields in both the active and passive remote sensing cases, a three layer model with a thin top layer caused by solar illumination must be used.

Kong, J. A.↗

Passive microwave sensing of soil moisture content - The effects of soil bulk density and surface roughness

Microwave radiometric measurements over bare fields of different surface roughness were made at frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz to study the frequency dependence, as well as the possible time variation, of surface roughness. An increase in surface roughness was found to increase the brightness temperature of soils and reduce the slope of regression between brightness temperature and soil moisture content. The frequency dependence of the surface roughness effect was relatively weak when compared with that of the vegetation effect. Radiometric time-series observations over a given field indicate that field surface roughness might gradually diminish with time, especially after a rainfall or irrigation. The variation of surface roughness increases the uncertainty of remote soil moisture estimates by microwave radiometry. Three years of radiometric measurements over a test site revealed a possible inconsistency in the soil bulk density determination, which is an important factor in the interpretation of radiometric data.

Wang, J. R.↗

Passive microwave sensing of soil moisture content: Soil bulk density and surface roughness

Microwave radiometric measurements over bare fields of different surface roughnesses were made at the frequencies of 1.4 GHz, 5 GHz, and 10.7 GHz to study the frequency dependence as well as the possible time variation of surface roughness. The presence of surface roughness was found to increase the brightness temperature of soils and reduce the slope of regression between brightness temperature and soil moisture content. The frequency dependence of the surface roughness effect was relatively weak when compared with that of the vegetation effect. Radiometric time series observation over a given field indicated that field surface roughness might gradually diminish with time, especially after a rainfall or irrigation. This time variation of surface roughness served to enhance the uncertainty in remote soil moisture estimate by microwave radiometry. Three years of radiometric measurements over a test site revealed a possible inconsistency in the soil bulk density determination, which turned out to be an important factor in the interpretation of radiometric data.

Wang, J. R.↗

User requirements and user acceptance of current and next-generation satellite mission and sensor complement, oriented toward the monitoring of water resources

Principal water resources users were surveyed to determine the applicability of remotely sensed data to their present and future requirements. Analysis of responses was used to assess the levels of adequacy of LANDSAT 1 and 2 in fulfilling hydrological functions, and to derive systems specifications for future water resources-oriented remote sensing satellite systems. The analysis indicates that water resources applications for all but the very large users require: (1) resolutions on the order of 15 meters, (2) a number of radiometric levels of the same order as currently used in LANDSAT 1 (64), (3) a number of spectral bands not in excess of those used in LANDSAT 1, and (4) a repetition frequency on the order of 2 weeks. The users had little feel for the value of new sensors (thermal IR, passive and active microwaves). What is needed in this area is to achieve specific demonstrations of the utility of these sensors and submit the results to the users to evince their judgement.

Castruccio, P. A.↗

Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.

Steffen, K.↗

Effects of vegetation on passive microwave estimates of soil moisture

Data collected over plots using a microwave radiometer with a wavelength of 21 cm were used to evaluate a theoretical model of the effect of vegetative cover on the emission of soils. The theoretical model was used as a basis of a simplified model which predicts the emissivity of a soil-vegetation complex with a full canopy cover. This model, when transformed to predict soil moisture, requires measurements of the microwave brightness temperature, surface temperature and vegetation biomass. Since surface temperature can be determined using thermal infrared measurements and vegetation biomass could be estimated with visible and near infrared measurements, the simplified model could be applied using only remotely sensed data.

Jackson, T. J.↗

Development Of VHF (240-270 MHz) Antennas For SoOp (Signal Of Opportunity) Receiver For 6u Cubesat Platforms

The main goal of this research is to design, fabricate, and test deployable VHF antennas for 6U Cubesat platforms to enable validation of root zone soil moisture (RZSM) estimation algorithms for signal of opportunity (SoOp) remote sensing over the 240-270 MHz frequency band. The proposed work provides a strong foundation for establishing a technology development path for maturing a truly global direct surface soil moisture (SM) and RZSM measurement system (Figure 1) over a variety of land covers with limited density restrictions. In SoOp methodology, signals transmitted by already existing transmitters (known as transmitters of opportunity, in this case the Military Satellite Communication (MilSatCom) System's UHF Follow-On program) are utilized to measure properties of reflecting targets by recording reflected signals using a simple passive microwave receiver.

Cubesat↗

Sea Ice Identification Using Dual-Polarized Ku-Band Scatterometer Data

Maps of sea ice have been based on a combination of observations from aircraft and ships, and infrared and passive microwave data from various spaceborne sensors. Described here is the potential of using dual-polarized scatterometer returns from the polar oceans to identify the edge of the ice cover. This ice edge could be used to compute the ice extent, which may be a useful indicator of climatic changes.

Ocean↗

Advanced sensors for spaceborne measurements of the earth's atmosphere

Concepts involved in remote sensing from space are reviewed, together with performance requirements of proposed and planned equipment. Attention is focused on measurements of the troposphere, particularly meteorological variables and chemical species. The principles of absorption, using either passive or active sensors, emission detection, fluorescence measurements, and EM radiation scattering are outlined. The proposed NASA Windsat, using a CO2 laser from the Orbiter or from an 800 km orbit spacecraft to measure low-level wind speeds is described, as are the uses of the AMTS atmospheric sounder instrument for IR atmospheric temperature sensing and a 20-channel microwave radiometer to detect moisture profiles in the water vapor bands. Additionally, a microwave pressure sounder to detect backscattered signals at 60 GHz is outlined, along with lidar pressure and wind speed measurement methods.

Hinkley, E. D.↗

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

land data↗

Analysis of RFI Statistics for Aquarius RFI Detection and Mitigation Improvements

Aquarius is an L-band active/passive sensor designed to globally map sea surface salinity from space. Two instruments, a radar scatterometer and a radiometer, observe the same surface footprint almost simultaneously. The radiometer is the primary instrument for sensing sea surface salinity (SSS), while the scatterometer is included to provide a correction for sea surface roughness, which is a primary source of error in the salinity retrieval. Although the primary objective is the measurement of SSS, the instrument combination operates continuously, acquiring data over land and sea ice as well. An important feature of the data processing includes detection and mitigation of Radio Frequency Interference (RFI) which is done separately for both active and passive instruments. Correcting for RFI is particularly critical over ocean because of the high accuracy required in the brightness temperature measurements for SSS retrieval. It is also necessary for applications of the Aquarius data over land, where man-made interference is widespread, even though less accuracy is required in this case. This paper will provide an overview of the current status of the Aquarius RFI processing and an update on the ongoing work on the improvement of the RFI detection and mitigation performance.

Microwave remote sensing↗

Identification of Sea Surface Temperature and Sea Surface Salinity Fronts along the California Coast: Application Using Saildrone and Satellite Derived Products

Coastal upwelling regions are one of the most dynamic areas of the world’s oceans. The California and Baja California Coasts are impacted by both coastal upwelling and the California Current, leading to frontal activity that is captured by gradients in both Sea Surface Temperature (SST) and Sea Surface Salinity (SSS). Satellite data are a great source of spatial data to study fronts. However, biases near coastal areas and coarse resolutions can impair its usefulness in upwelling areas. In this work gradients in SST from NASA Multi-Scale Ultra-High Resolution (MUR) and in two SSS products derived from the Soil Moisture Active Passive (SMAP) NASA mission are compared directly with gradients derived from the Saildrone uncrewed vehicles to validate the gradients as well as to assess their ability to detect known frontal features. The three remotely sensed data sets (MURSST/JPL, SMAP SSS/RSS, SMAP SSS) were co-located with the Saildrone data prior to the calculation of the gradients. Wavelet analysis is used to determine how well the satellite derived SST and SSS products are reproducing the Saildrone derived gradients. Overall results indicate the remote sensing products are reproducing features of known areas of coastal upwelling. Differences between the SST and SSS gradients are mainly associated with the limitations of the microwave derived SSS coverage near land and its reduced spatial resolution. The results are promising for using remote sensing data sets to monitor frontal structure along the California Coast and the application to long term changes in coastal upwelling and dynamics.

Sea Surface Salinity↗

Multi-frequency, multi-polarization SAR and radiometer sea ice classification

Microwave remotely sensed data were acquired simultaneously in March 1988 over Beaufort, Chukchi, and Bering Sea ice using the JPL multifrequency, polarimetric synthetic aperture radar (SAR), and multifrequency dual-polarization GSFC radiometer. The experiment was conducted as a series of coordinated underflights of the DMSP SSM/I satellite radiometer to validate ice products derived from its radiance values. Concurrent flights by an NRL P-3 aircraft enabled overlapping high-resolution, single-frequency images to be acquired over the same surfaces using a Ka-band scanning microwave radiometer. Precise coregistration to an accuracy of 100 m, +/- 25 m enables comparison of temporally and spatially coincident active and passive microwave datasets. Three-channel polarimetric SAR data are compared with dual-polarized radiometer data at several SSM/I frequencies, showing backscatter signatures to be highly correlated with radiometric temperatures. Further comparisons are used to evaluate ice concentration retrievals and to show how multiparameter datasets can be used to resolve ambiguities present in identifying certain sea ice forms with a single microwave instrument.

Drinkwater, Mark R.↗

Freshwater ice thickness observations using passive microwave sensors

Walden Reservoir, a freshwater lake in north-central Colorado, was overflown six times by a NASA C-130 aircraft between January 1977 and April 1980. The aircraft was equipped with four microwave radiometers operating between 0.81 and 6.0 cm in wavelength (37.0 to 5.0 GHz). The 6.0-cm radiometer data showed a good relationship with ice thickness based on a sample of four ice thickness values. The 1.67- and 1.35-cm radiometer data showed weaker relationships with ice thickness. The 0.81-cm sensor data showed no positive relationship with ice thickness. None of the relationships was statistically significant because of the small sample size. The 6.0-cm sensor data in the nadir-viewing mode was found to have the most potential of all the wavelengths studied, for use in remotely determining ice thickness. The 6.0-cm radiometer probably sensed the entire thickness of the ice on the reservoir (ranging from 25.4 to 67.3 cm in thickness) and was apparently not significantly affected by the snow overlying the ice. The shorter wavelengths are scattered by the snow overlying the ice and are more suitable for snow studies than for ice thickness studies.

Hall, D. K.↗

Pan-tropical daily L-band microwave land surface emissivity retrieval from GNSS-R observations

The uncertainties in microwave land surface emissivity (MLSE) measurements have long limited the use of spaceborne microwave radiometer data. As an emerging observation method, Global Navigation Satellite System Reflectometry (GNSS-R) has demonstrated great potential in several land and ocean applications. In this study, a method for obtaining daily MLSE dataset in the pan-tropical region from Cyclone GNSS (CYGNSS) observations is presented and evaluated. The CYGNSS observations are first aggregated into the Equal-Area-Scalable-Earth (EASE) 2.0 36 km grid by a combined weight function of distance, time, and signal-to-noise ratio variance. Then, the method employs a pixel-by-pixel regression algorithm to conduct the daily MLSE retrieval using reference emissivity derived from the Soil Moisture Active Passive (SMAP) brightness temperature. The CYGNSS MLSE shows good agreement with SMAP MLSE, delivering an overall root-mean-square error (RMSE) of 0.022 and 0.017 for horizontal and vertical polarization, respectively, during the training set spanning the whole year of 2018. Furthermore, on the test set from January 2019 to May 2019, the RMSE values amounted to 0.030 and 0.023 for horizontal and vertical polarization, respectively. Temperature records from the International Soil Moisture Network are employed to calculate the emissivity and for in-situ validation, which yield an RMSE of 0.034 and 0.026 for the two polarizations, respectively. The proposed algorithm provides an encouraging approach to obtain accurate daily MLSE dataset for microwave remote sensing. Compared to the SMAP MLSE, the CYGNSS MLSE has a remarkable improvement of 86% in temporal resolution, greatly complementing the existing microwave emissivity datasets.

54 ENVIRONMENTAL SCIENCES↗

Remote Sensing of Cloud Properties using Ground-based Measurements of Zenith Radiance

An extensive verification of cloud property retrievals has been conducted for two algorithms using zenith radiances measured by the Atmospheric Radiation Measurement (ARM) Program ground-based passive two-channel (673 and 870 nm) Narrow Field-Of-View Radiometer. The underlying principle of these algorithms is that clouds have nearly identical optical properties at these wavelengths, but corresponding spectral surface reflectances (for vegetated surfaces) differ significantly. The first algorithm, the RED vs. NIR, works for a fully three-dimensional cloud situation. It retrieves not only cloud optical depth, but also an effective radiative cloud fraction. Importantly, due to one-second time resolution of radiance measurements, we are able, for the first time, to capture detailed changes in cloud structure at the natural time scale of cloud evolution. The cloud optical depths tau retrieved by this algorithm are comparable to those inferred from both downward fluxes in overcast situations and microwave brightness temperatures for broken clouds. Moreover, it can retrieve tau for thin patchy clouds, where flux and microwave observations fail to detect them. The second algorithm, referred to as COUPLED, couples zenith radiances with simultaneous fluxes to infer 2. In general, the COUPLED and RED vs. NIR algorithms retrieve consistent values of tau. However, the COUPLED algorithm is more sensitive to the accuracies of measured radiance, flux, and surface reflectance than the RED vs. NIR algorithm. This is especially true for thick overcast clouds where it may substantially overestimate z.

Chiu, J. Christine↗

Recent advances in remote sensing; Proceedings of the First International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981

The state of the art in remote sensing of the earth and the planets was discussed in terms of sensor performance, signal processing, and data interpretation. Particular attention was given to lidar for characterizing atmospheric particulates, the modulation of short waves by long ocean gravity waves, and runoff modeling for snow-covered areas. The use of NOAA-6 spacecraft AVHRR data to explore hydrologic land surface features, the effects of soil moisture and vegetation canopies on microwave and thermal microwave emissions, and regional scale evapotranspiration rate determination through satellite IR data are examined. A Shuttle experiment to demonstrate high accuracy global time and frequency transfer is described, along with features of the proposed Gravsat, radar image processing for rock-type discrimination, and passive microwave sensing of temperature and salinity in coastal zones.

Mcintosh, R.↗