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Advances in spaceborne Synthetic Aperture Radar (SAR) remote sensing technology make it possible to acquire global-scale data sets that provide unique information about the Earth's continually changing surface characteristics.
This study explores the use of synthetic thermal center pivot irrigation scenes to estimate temperature retrieval accuracy for thermal remote sensed data, such as data acquired from current and proposed Landsat-like thermal systems. Center pivot irrigation is a common practice in the western United States and in other parts of the world where water resources are scarce. Wide-area ET (evapotranspiration) estimates and reliable water management decisions depend on accurate temperature information retrieval from remotely sensed data. Spatial resolution, sensor noise, and the temperature step between a field and its surrounding area impose limits on the ability to retrieve temperature information. Spatial resolution is an interrelationship between GSD (ground sample distance) and a measure of image sharpness, such as edge response or edge slope. Edge response and edge slope are intuitive, and direct measures of spatial resolution are easier to visualize and estimate than the more common Modulation Transfer Function or Point Spread Function. For these reasons, recent data specifications, such as those for the LDCM (Landsat Data Continuity Mission), have used GSD and edge response to specify spatial resolution. For this study, we have defined a 400-800 m diameter center pivot irrigation area with a large 25 K temperature step associated with a 300 K well-watered field surrounded by an infinite 325 K dry area. In this context, we defined the benchmark problem as an easily modeled, highly common stressing case. By parametrically varying GSD (30-240 m) and edge slope, we determined the number of pixels and field area fraction that meet a given temperature accuracy estimate for 400-m, 600-m, and 800-m diameter field sizes. Results of this project will help assess the utility of proposed specifications for the LDCM and other future thermal remote sensing missions and for water resource management.
We review our recent advances in understanding the role of temporal decorrelation in SAR interferometry and polarimetric SAR interferometry. We developed a physical model of temporal decorrelation based on Gaussian-statistic motion that varies along the vertical direction in forest canopies. Temporal decorrelation depends on structural parameters such as forest height, is sensitive to polarization and affects coherence amplitude and phase. A model of temporal-volume decorrelation valid for arbitrary spatial baseline is discussed. We tested the inversion of this model to estimate forest height from model simulations supported by JPL/UAVSAR data and lidar LVIS data. We found a general good agreement between forest height estimated from radar data and forest height estimated from lidar data.
Data hosted by the National Aeronautics and Space Administration (NASA) are expected to increase to over 600 PB by the end of the decade (see Figure 1). This rapid increase is, in part, driven by the launch of new, high-data-volume Earth observing missions, such as the NASA-Indian Space Research Organisation (ISRO) Synthetic Aperture Radar (NISAR), Surface Water and Ocean Topography (SWOT), Tropospheric Emissions: Monitoring of Pollution (TEMPO) and Plankton, Aerosol, Cloud ocean Ecosystem (PACE) missions.
The CloudSat satellite's Cloud Profiling Radar (CPR) is a highly sensitive 94 GHz (W-band) nadir viewing radar system flown in retrograde sun synchronous orbit useful for determining the vertical structure of cloud hydrometeors down to sensitivity of approx. -30 dBZ reflectivity factor. Given this sensitivity, it is possible to unambiguously measure precipitation rates in clouds over a spectrum extending from approx. 0.08 - 3.0 mm hr (sup -1) down to altitudes of 0.5 km with approx.0.25 km vertical binning. This enables an effective means to measure a great deal of the drizzle and light rain spectrum. However, because of its near-polar sunsynchronous orbit, CloudSat cannot sample the diurnal cycle of precipitation, nor with its nadir-only CPR view can it obtain a high duty cycle in sampling precipitation at fixed local times over fixed positions. On the other hand, the TRMM satellite, which is flown in a non-sunsynchronous 35-degree inclined orbit carrying the 13.8 GHz KU-band Precipitation Radar (PR) scanning through nadir over an approx. 225 km swath, can sample both the diurnal cycle and with a much improved duty cycle relative to CloudSat. Moreover, the PR and CPR have the same 0.25 km vertical binning capability. The PR's greatest shortcoming is its approx. +17 dBZ sensitivity, which eliminates the possibility of measuring rain rates below -0.3-0.5 mm hr(sup -1), which can involve rainfall accumulations of up to 50% of the total over some regions. This begs the question of whether by combining CPR and PR data sets, whether it is possible to obtain an augmented measurement of the diurnal precipitation cycle. By collecting complimentary datasets during CloudSat and TRMM satellite orbit crossings within a delta t = 45-min proximity window, it is possible to demonstrate that whenever TRMM detects a precipitation signal, the correlations along the vertical axis between the reflectivities acquired from the CPR and PR are in inverse proportion to the magnitude of the delta t proximity window. By taking advantage of these underlying correlations, it is possible to develop a functional which can be used to broaden the reflectivity spectrum, concomitantly the rain rate spectrum, of the PR measurements based on the inherently broader reflectivity spectrum of the CPR at the lower reflectivity end of the spectrum, concomitantly at lighter rain rates. With the functional in place, it is then possible to produce synthetic CloudSat precipitation imagery over the PR track and thus over the diurnal time period. These augmented data are then used to study the spectral-vertical diurnal properties of precipitation over oceanic regions observed by TRMM.
Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics.
Satellite remote sensing provides unique opportunities for observing ice-covered terrain. Passive-microwave data give information on snow extent on land, sea-ice extent and type, and zones of summer melting on the polar ice sheets, with the potential for estimating snow-accumulation rates on these ice sheets. All weather, high-resolution imagery of sea ice is obtained using synthetic aperture radars, and ice-movement vectors can be deduced by comparing sequential images of the same region. Radar-altimetry data provide highly detailed information on ice-sheet topography, with the potential for deducing thickening/thinning rates from repeat surveys. The coastline of Antarctica can be mapped accurately using altimetry data, and the size and spatial distribution of icebergs can be monitored. Altimetry data also distinguish open ocean from pack ice and they give an indication of sea-ice characteristics.
Characterization of FM9, polyisobutylene and their modified fuels is provided. Synthesis alternative AMA candidates was attempted. Some data for alternative AMA is shown.
SAR imagery automatically put onto map in desired projection. MAPJTC designed to rectify and transform standard image output of digital synthetic-aperture-radar (SAR) correlator into image registered with geocoded map, without manual tiepointing or other interaction with operator. Reduces procedure to two one-dimensional passes, thereby saving computer time. Program written in FORTRAN (84 percent), APAL (2 percent), and MAXL (14 percent).
Edge detection would appear to be a crucial tool for analyzing multi-polarized, multi-frequency, and multi-temporal Synthetic Aperture Radar (SAR) images. Edge structure provides a simple means for comparing different polarizations and frequencies, and for detecting changes over time. Due to the fact that edges and segments (homogeneous regions) are dual concepts, edge detection has an important role to play in identifying segments within which mean backscatter measurements for use in image classification can be made. As part of a general investigation into edge detection in SAR imagery, an initial investigation was carried out into the detectability and nature of edges in multi-polarized and multi-frequency SAR images. The contrast ratio (CR) operator was used to detect edges. This operator was previously shown to perform well at detecting edges in single-polarized and single-frequency SAR images.
Alternate aviation fuels for military or commercial use are required to satisfy MIL-DTL-83133F(2008) or ASTM D 7566 (2010) standards, respectively, and are classified as "drop-in" fuel replacements. To satisfy legacy issues, blends to 50% alternate fuel with petroleum fuels are certified individually on the basis of processing and assumed to be feedstock agnostic. Adherence to alternate fuels and fuel blends requires "smart fueling systems" or advanced fuel-flexible systems, including combustors and engines, without significant sacrifice in performance or emissions requirements. This paper provides preliminary performance (Part A) and emissions and particulates (Part B) combustor sector data. The data are for nominal inlet conditions at 225 psia and 800 F (1.551 MPa and 700 K), for synthetic-paraffinic-kerosene- (SPK-) type (Fisher-Tropsch (FT)) fuel and blends with JP-8+100 relative to JP-8+100 as baseline fueling. Assessments are made of the change in combustor efficiency, wall temperatures, emissions, and luminosity with SPK of 0%, 50%, and 100% fueling composition at 3% combustor pressure drop. The performance results (Part A) indicate no quantifiable differences in combustor efficiency, a general trend to lower liner and higher core flow temperatures with increased FT fuel blends. In general, emissions data (Part B) show little differences, but with percent increase in FT-SPK-type fueling, particulate emissions and wall temperatures are less than with baseline JP-8. High-speed photography illustrates both luminosity and combustor dynamic flame characteristics.
SEASAT will be an earth-satellite system designed to monitor and observe ocean dynamics in order to provide data for real-time use and predictive purposes. SEASAT-A will be a prototype satellite which will provide experience for system development and some operational demonstration capability. The SEASAT-A will use passive and active visible, infrared, and microwave sensing techniques. The payload will include a scanning radiometer (SR) and a scanning multichannel microwave radiometer (SMMR), which are passive sensors, a short-pulse altimeter, a scatterometer, and a synthetic aperture radar, which are active. The major functional elements considered in the definition-phase studies are the sensors, data handling, communications, attitude control, power, orbit adjust, thermal control, structures, and mechanical design. An existing satellite bus, with sensors and sensor modules to be developed, is to be used on SEASAT-A.
Within NASA's Aviation Safety Program, the Synthetic Vision Systems Project is developing display system concepts to improve pilot terrain/situation awareness by providing a perspective synthetic view of the outside world through an on-board database driven by precise aircraft positioning information updating via Global Positioning System-based data. This work is aimed at eliminating visibility-induced errors and low visibility conditions as a causal factor to civil aircraft accidents, as well as replicating the operational benefits of clear day flight operations regardless of the actual outside visibility condition. Synthetic vision research and development activities at NASA Langley Research Center are focused around a series of ground simulation and flight test experiments designed to evaluate, investigate, and assess the technology which can lead to operational and certified synthetic vision systems. The technical challenges that have been encountered and that are anticipated in this research and development activity are summarized.
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.
As part of the Arctic Ice Dynamics Joint Experiment (AIDJEX) several repetitive coverages of L-band (25 cm wavelength) side-looking airborne radar images have been flown over coastal areas of Alaska and a test area in the Arctic. These images allow the analysis of sea ice and its drift. Radar is particularly suited for the mapping and interpretation of Arctic sea ice due to independence from sunlight and the capability to penetrate clouds. Ice floes and leads can be readily identified on the radar images. Measurement of ice floe drift is based on the transformation of radar image coordinates into a geocentric coordinate system using inertial guidance data from the survey aircraft. The paper will demonstrate an example of Arctic ice drift measurements from L-band synthetic aperture radar imagery with an absolute accuracy of about 5%. The conclusions are of particular value in view of planned spaceborne side-looking radar missions in polar orbits.
The status is reviewed of electromagnetic scattering theory relative to the interpretation of microwave remote sensing data acquired from spaceborne platforms over the ocean surface. Particular emphasis is given to the assumptions which are either implicit or explicit in the theory. The multiple scale scattering theory developed during this investigation is extended to non-Gaussian surface statistics. It is shown that the important statistic for the case is the probability density function of the small scale heights conditioned on the large scale slopes; this dependence may explain the anisotropic scattering measurements recently obtained with the AAFE Radscat. It is noted that present surface measurements are inadequate to verify or reject the existing scattering theories. Surface measurements are recommended for qualifying sensor data from radar altimeters and scatterometers. Additional scattering investigations are suggested for imaging type radars employing synthetically generated apertures.
Linear discriminant analysis and supervised classification evaluated. Report discusses processing of multispectral remote-sensing imagery to identify kinds of sedimentary rocks by spectral signatures in geological and geographical contexts. Raw image data are spectra of picture elements in images of seven sedimentary rock units exposed on margin of Wind River Basin in Wyoming. Data acquired by Landsat Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and NASA/JPL airborne synthetic-aperture radar (SAR).
Report describes international collaboration on experiments in calibration of synthetic-aperture radar (SAR) systems. Purposes of experiments were to: address problems associated with calibration of data, cross-calibrate between sets of imaging-radar data obtained by different systems, test designs of ground calibration equipment, and find candidate sites for calibration of future satellite-borne SAR systems.