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At least 1,171 records · Page 65

Demonstration of Repeat-Pass POLINSAR Using UAVSAR: The RMOG Model

In this paper we show our first POLINSAR results using the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) developed by the Jet Propulsion Laboratory (JPL). UAVSAR is a L-band repeat-pass polarimetric and interferometric system designed for measuring vegetation structure and monitoring crustal deformations. In order to extract canopy height from POLINSAR data and account for temporal decorrelation, we formulate a physical model of the temporal-volumetric coherence, random motion over ground (RMOG) model. Canopy height extracted from single-baseline UAVSAR data using the RMOG model is shown to be in agreement with canopy height measured by the Land, Vegetation, and Ice Sensor (LVIS) lidar.

polarimetry↗

Comparison of visualized turbine endwall secondary flows and measured heat transfer patterns

Various flow visualization techniques were used to define the secondary flows near the endwall in a large heat transfer data. A comparison of the visualized flow patterns and the measured Stanton number distribution was made for cases where the inlet Reynolds number and exit Mach number were matched. Flows were visualized by using neutrally buoyant helium-filled soap bubbles, by using smoke from oil soaked cigars, and by a few techniques using permanent marker pen ink dots and synthetic wintergreen oil. Details of the horseshoe vortex and secondary flows can be directly compared with heat transfer distribution. Near the cascade entrance there is an obvious correlation between the two sets of data, but well into the passage the effect of secondary flow is not as obvious.

Gaugler, R. E.↗

Comparison of visualized turbine endwall secondary flows and measured heat transfer patterns

Various flow visualization techniques were used to define the seondary flows near the endwall in a large heat transfer data. A comparison of the visualized flow patterns and the measured Stanton number distribution was made for cases where the inlet Reynolds number and exit Mach number were matched. Flows were visualized by using neutrally buoyant helium-filled soap bubbles, by using smoke from oil soaked cigars, and by a few techniques using permanent marker pen ink dots and synthetic wintergreen oil. Details of the horseshoe vortex and secondary flows can be directly compared with heat transfer distribution. Near the cascade entrance there is an obvious correlation between the two sets of data, but well into the passage the effect of secondary flow is not as obvious. Previously announced in STAR as N83-14435

Gaugler, R. E.↗

A Numerical Climate Observing Network Design Study

This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: "Optimal observations for variational data assimilation".

Stammer, Detlef↗

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as the optical and SAR data proves high resolution (5-10 m) imagery, and SAR data is unaffected by cloud cover and light availability (day vs. night), which are common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a MODIS snow mask product to mask global snow coverage, which would affect land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd watershed located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management..

Lori Berberian↗

Calibration Methodology for the Lightweight Rainfall Radiometer STAR Aircraft Sensor

A proposed methodology for the in-flight calibration of a Synthetic Thinned Aperture Radiometer (STAR) airborne sensor with the potential application to a space flight version. The application of the spaceflight version of this instrument will address several pressing issues related to the Global Precipitation Measurement Mission (GPM). The X-Band Lightweight Rainfall Radiometer using STAR technology (LRR-X) is an aircraft sensor that is jointly developed by the NASA Goddard Space Flight Center and the University of Michigan. This paper will describe the theory of calibration as well as the hardware design specifications used by the method. The on-board hardware uses individual uncorrelated warm loads on each receiver as well as to a single noise diode providing a correlated noise source to each receiver. A procedure for maintaining onboard calibration with an optimum running average using correlated bursts of thermal noise interleaved with scene data will be exercised during the maiden flight of the LRR-X instrument during the spring of 2003. The final component of calibration of a synthetic aperture radiometer is the image reconstruction algorithm that uses the measured correlations to produce the temperature brightness (TB) images. An overview of system-level testing, both on the ground and in-flight, will be presented to validate the absolute accuracy of the image reconstruction algorithm.

Principe, Caleb↗

Test results on the Viking gas chromatograph-mass spectrometer experiment

The gas chromatograph-mass spectrometer instrument to be utilized in the Viking 1975 Molecular Analysis experiment has undergone preliminary testing in its flight configured version. A synthetic mixture of 24 components as well as a sample of the Murchison meteorite has been used for this purpose. The resulting data not only allowed the identification of most of the organic compounds known to be present, but also revealed the identity of a few unexpected ones. Thus, the sensitivity and reliability of the instrument and data system are satisfactorily demonstrated.

Biemann, K.↗

Summary of synfuel characterization and combustion studies

Combustion component research studies aimed at evolving environmentally acceptable approaches for burning coal derived fuels for ground power applications were performed at the NASA Lewis Research Center under a program titled the ""Critical Research and Support Technology Program'' (CRT). The work was funded by the Department of Energy and was performed in four tasks. This report summarizes these tasks which have all been previously reported. In addition some previously unreported data from Task 4 is also presented. The first, Task 1 consisted of a literature survey aimed at determining the properties of synthetic fuels. This was followed by a computer modeling effort, Task 2, to predict the exhaust emissions resulting from burning coal liquids by various combustion techniques such as lean and rich-lean combustion. The computer predictions were then compared to the results of a flame tube rig, Task 3, in which the fuel properties were varied to simulate coal liquids. Two actual SRC 2 coal liquids were tested in this flame tube task.

Schultz, D. F.↗

Multi-polarization C-band SAR for soil moisture estimation

Previous studies of synthetic aperture radar (SAR) imagery have shown qualitative relationships between radar backscatter and soil moisture. However, to be able to use these data in operational programs it will be necessary to establish quantitatively how the radar return is related to soil moisture and the effects of surface roughness, soil type, and vegetation cover and growth stage, as a function of frequency and polarization. To this end, a multi-year experiment began in 1990 as a cooperative venture amongst the Canada Center (Agriculture Canada), and the Universities of Guelph, Sherbrooke, Laval, and Waterloo. During 1990, SAR imagery was acquired during two periods (May and Jun.) to correspond to times of minimal and substantial vegetation cover. SAR data were acquired on three days in May and on four days in Jul. to cover different soil moisture conditions. This unique comprehensive data set is used to investigate the relationships between soil moisture and radar backscatter. The experiment and data collected are described, and a preliminary qualitative interpretation of the relationship between soil moisture and image tone is provided.

Brown, R. J.↗

The July 1990 Gulf Stream Experiment

The specific scientific tasks addressed in the July 1990 Gulf Stream (GS) experiment were the following: (1) Kelvin wake behavior across fronts at various ship speeds, (2) the physics of temperature front/radar cross section (RCS) mismatch, (3) wave-current interactions in curvature fronts, and (4) the hydrodynamic structure and origin of synthetic-aperture-radar (SAR) slick-like features. Overall, the GS Experiment was most successful, and about 60 percent of the planned data was collected. On-going efforts concentrate on the analysis and interpretation of the data. An overview of the experiment and preliminary results of the data analysis are given.

Valenzuela, G. R.↗

The metallicity and luminosity of RV Tauri variables from medium-resolution spectra

Results are reported from spectroscopic observations of members of the RV Tauri class of pulsating variable stars at moderate resolution, and from photometric observations of these stars with the B and V filters of the Johnson UBV system and the first four filters of the Wing eight-color narrowband near-IR system. Of the 22 variables observed, TiO absorption was detected in eight, and 10 variables displayed hydrogen-line emission at some phase. Spectral classifications were assigned relative to the MK process. Color excesses were determined for those variables for which spectroscopic and photometric data were obtained within a few days of each other. The spectra obtained at a resolution of 2.5 A were fitted with synthetic spectra to determine the stellar atmospheric parameters. The range in metallicity among the variables was found to be quite extensive, -0.3 to -0.7, and may reflect a mixture of stellar populations or masses.

Wahlgren, Glenn M.↗

Techniques and applications of SAR interferometry for ERS-1

The ERS-1 Synthetic Aperture Radar (SAR) demonstrated that it is possible to measure high resolution topography over large areas using interferometry with repeat orbit data sets. Given that the ERS-1 orbit is known with high precision, an automatic system for generation of interferograms is presented. Least squares estimation using ground control points provides an accurate method for determining the precise interferometric baseline. The system parameters which affect the accuracy of the Digital Elevation Models (DEM's) are errors in the interferometric baseline, decorrelation caused by baseline separation, thermal noise, and surface change. An adaptive filter based on the local interferometric coherence was developed to improve phase unwrapping of the interferogram. Final accuracies of the DEM's generated for single scene pairs in Alaska (U.S.) and Bonn (Germany) are on the order of 5 to 10 m.

Werner, Charles L.↗

Observations of ice-sheet motion in Greenland using satellite radar interferometry

We present interferometric observations of ice-sheet motion in western Greenland based on pairs of ERS-1 synthetic aperture radar (SAR) images. These observations provide the first detailed regional view of ice motion associated with dynamically supported topography near the margin of an ice sheet. The interferograms of this area are much more complicated than other interferograms of ice sheets presented to date. We devote the largest part of this paper to explaining the source of the complexity in these interferograms. A synthetic interferogram based on a simple model helps to illustrate the effects of different components of the ice velocity field in interferometric data and suggests a method for estimating the large-scale ice velocity field from such data.

Joughin, Ian R.↗

Two-Dimensional Synthetic Aperture Radiometry over Land Surface During Soil Moisture Experiment in 2003 (SMEX03)

Microwave radiometry at low frequencies (L-band, approx. 1.4 GHz) has been known as an optimal solution for remote sensing of soil moisture. However, the antenna size required to achieve an appropriate resolution from space has limited the development of spaceborne L-band radiometers. This problem can be addressed by interferometric technology called aperture synthesis. The Soil Moisture and Ocean Salinity (SMOS) mission will apply this technique to monitor global-scale surface parameters in the near future. The first airborne experiment using an aircraft prototype of this approach, the Two-Dimensional Synthetic Aperture Radiometer (2D-STAR), was performed in the Soil Moisture Experiment in 2003 (SMEX03). The L-band brightness temperature data acquired in Alabama by the 2DSTAR was compared with ground-based measurements of soil moisture and with C-band data collected by the Polarimetric Scanning Radiometer (PSR). Our results demonstrate a good response of the 2D-STAR brightness temperature to changes in surface wetness, both in agricultural and forest lands. The behavior of the horizontally polarized brightness temperature data with increasing view-angle over the forest area was noticeably different than over bare soil. The results from the comparison of 2D-STAR and PSR indicate a better response of the 2D-STAR to the surface wetness under both wet and dry conditions. Our results have important implications for the performance of the future SMOS mission.

Ryu, Dongryeol↗

Software Reduces Radio-Interference Effects in Radar Data

A computer program suppresses the effects of narrow-band radio-frequency interference (RFI) on the data collected by a wide-band radar system. The need for this program arises because some advanced wide-band synthetic-aperture radar systems utilize frequency bands that include frequencies used by other radio services. In this program, the RFI environment is represented by an auto-regressive process, the frequency band of which is narrow relative to that of the radar. Most of the RFI signals, both narrow- and wide-band, are estimated in one pass of a least-mean-square (LMS) adaptive filter. The program implements three popular LMS algorithms: the time-domain LMS, the frequency-domain LMS, and the filter-bank LMS adaptive-filter algorithms. The program can be run in a manual or automatic mode. In the manual mode, the user selects the filter parameters prior to execution. In the automatic mode, the program utilizes median-filter and spectral-estimation techniques plus the variable-step-size LMS algorithm for automatic determination of filter parameters, and the parameters are adaptively changed as functions of the inputs, resulting in better overall performance.

Le, Charles T-C↗

Mapping Wetland and Riparian Areas to Support Rio Grande Cutthroat Trout Habitat Restoration

The Rio Grande cutthroat trout (Oncorhynchus clarki virginalis; RGCT) population has declined significantly over the last century due to habitat loss, competition, and hybridization with non-native trout species. The species currently occupies roughly 11% of its historic habitat. Conservation efforts led by government and private actors have succeeded in increasing RGCT populations since the early 2000s. State, federal, and private partners began the largest native trout restoration initiative in North America. Since 2002, these efforts have included wetland and riparian area restoration and RGCT reintroduction. Current restoration efforts focus on restoring the Costilla Creek Watershed located in Colorado and New Mexico to provide cool water temperatures, improve water quality, and maintain suitable habitat for the trout species. To guide these restoration efforts, the team conducted a rapid assessment to locate and characterize wetland and riparian areas in the Costilla Creek watershed. The team utilized NASA data from the Landsat 8 Operational Land Imager (OLI), as well as the Sentinel-2 MultiSpectral Instrument (MSI), and the Sentinel-1 Synthetic Aperture Radar (SAR) for May 2016 to October 2019. To produce probability maps of wetland presence, the team used the Software for Assisted Habitat Modeling (SAHM) incorporating predictor variables generated from topographic indices, spectral indices, and radar. The top three models (General Wetland model, Stream and Wetland Connectivity model, and Inclusive Wetland model) showed a strong ability to detect wetlands. They all had AUC values greater than 0.9 and had high overlap with wetland areas during visual assessment over high-resolution imagery. The General Wetland model output was converted into a wetland polygon dataset and polygons were classified by wetland type. The resulting maps and datasets will support partners in determining the extent of possible RGCT habitat and identifying where habitat restoration efforts may be needed.

NASA DEVELOP↗

Beaufort-Chukchi ice margin data from Seasat - Ice motion

The motion of sea ice in the summer and fall marginal zone of the Beaufort and Chukchi seas is observed by tracking ice features in sequential Seasat synthetic aperture radar images. Four examples of ice motion fields are shown and discussed with translation observation density finer than one observation per 5 km for the most part. In this region the components of proportional relative motion are shown to commonly have values in the range 0.1 to 0.25/day throughout the marginal zone, which itself has a scale of the order of 100 km.

Carsey, Frank↗