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This presentation highlights methods to classify aircraft from radar data and investigates how data from flight controllers can be used to train classifiers.
A program of research has recently been initiated under the NASA Innovative Research Program to develop and test techniques for reconstructing the three-dimensional shapes of asteroids from ground-based radar observations. Presently, no methods exist to do this and the full scientific potential of current radar data sets lies untapped. The situation will become even more pronounced in approximately two years when the upgraded Arecibo radar system becomes capable of regularly producing asteroid data sets with very fine spatial resolution and high signal-to-noise ratios. If successful, the proposed research will significantly increase our knowledge of these objects. The potential and limitations of the techniques developed will be rigorously tested in a series of computer simulations and optical scattering experiments with scale models.
The state of the art determination was made for radar measurement of: soil moisture, snow, standing and flowing water, lake and river ice, determination of required spacecraft radar parameters, study of synthetic-aperture radar systems to meet these parametric requirements, and study of techniques for on-board processing of the radar data. Significant new concepts developed include the following: scanning synthetic-aperture radar to achieve wide-swath coverage; single-sideband radar; and comb-filter range-sequential, range-offset SAR processing. The state of the art in radar measurement of water resources parameters is outlined. The feasibility for immediate development of a spacecraft water resources SAR was established. Numerous candidates for the on-board processor were examined.
The application of side-looking radar images in geoscience fields can be enhanced when using overlapping image strips that are viewed in stereo. A question concerns the quality of stereo radar. This quality is described evaluating stereo viewability and using the concept of vertical exaggeration with sets of actual radar images. A conclusion is that currently available stereo radar data are not optimized, that therefore a better quality can be achieved if data acquisition is appropriately arranged, and that the actual limitations of stereo radar are still unexplored.
The application of side-looking radar images in geoscience fields can be enhanced when using overlapping image strips that are viewed in stereo. A question concerns the quality of stereo radar. This quality is described evaluating stereo viewability and using the concept of vertical exaggeration with sets of actual radar images. A conclusion is that currently available stereo radar data are not optimized, that therefore a better quality can be achieved if data acquisition is appropriately arranged, and that the actual limitations of stereo radar are still unexplored. Previously announced in STAR as N83-29489
Accurate measurement of the electron density profile and its variations is crucial to further progress in understanding the physics of the disturbed equatorial ionosphere. To accomplish this, a plasma frequency probe was included in the payload complement of two rockets flown during the Condor rocket campaign conducted from Peru in March 1983. This paper presents density profiles of the disturbed equatorial ionosphere from a night-time flight in which spread-F conditions were present and from a day-time flight during strong electrojet conditions. Results from both flights are in excellent agreement with simultaneous radar data in that the regions of highly disturbed plasma coincide with the radar signatures. The spread-F rocket penetrated a topside depletion during both the upleg and downleg. The electrojet measurements showed a profile peaking at 1.3 x 10 to the 5th per cu cm at 106 km, with large scale fluctuations having amplitudes of roughly 10 percent seen only in the upward gradient in electron density. This is in agreement with plasma instability theory. It is further shown that simultaneous measurements by fixed-bias Langmuir probes, when normalized at a single point to the altitude profile of electron density, are inadequate to correctly parameterize the observed enhancements and depletions.
In the tropical rain forests of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 100 kg/sq m in old, undisturbed floodplain stands, the P-band polarimetric radar data gathered in June of 1993 by the AIRSAR (Airborne Synthetic Aperture Radar) instrument separate most major vegetation formations and also perform better than expected in estimating woody biomass. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, as well as reliable maps of land cover, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forests inventories.
NASA is developing a Ground Validation System (GVS) as one of its contributions to the Global Precipitation Mission (GPM). The GPM GVS provides an independent means for evaluation, diagnosis, and ultimately improvement of GPM spaceborne measurements and precipitation products. NASA's GPM GVS consists of three elements: field campaigns/physical validation, direct network validation, and modeling and simulation. The GVS prototype of direct network validation compares Tropical Rainfall Measuring Mission (TRMM) satellite-borne radar data to similar measurements from the U.S. national network of operational weather radars. A prototype field campaign has also been conducted; modeling and simulation prototypes are under consideration.
The first topographic and ice-motion maps of the northwestern flank of Hielo Patagonico Norte (HPN, northern Patagonia Icefield), in Chile, were produced using satellite synthetic-aperture interferometric radar data acquired by NASA's Spaceborne Imaging Radar C instrument in October 1994. The topographic map has a IO m vertical precision with a 30 m horizontal spacing, which should be sufficient to serve as a reference for monitoring future mass changes of the icefield. The ice-motion map is accurate to within 4 mm/ d (or 1/ ma). The radar-derived surface topography and ice velocity are used to estimate the ice discharge from the accumulation area of four outlet glaciers, and the calving flux and mass balance of Glaciar San Rafael. The results demonstrate the use of SAR interferometry for monitoring glaciological parameters on a spatial and temporal scale unattainable by any other means.
We have examined the L-band radiometer and radar data from NASA’s Soil Moisture Active Passive (SMAP) mission for ocean research and applications. We find that the SMAP data are in excellent agreement with the geophysical model function (GMF) derived from the Aquarius data up to a wind speed of 20 ms-1. For severe wind conditions, the higher resolution data from SMAP allowed us to assess the sensitivity of L-band radiometer signals to hurricane force winds. We applied the L-band GMF to the retrieval of ocean surface wind and SSS from the SMAP data. Comparison with the European Center for Medium-Range Weather Forecasting, WindSat and RapidSCAT wind speeds suggests that SMAP’s radiometer wind speed reaches an excellent accuracy of about 1.1-1.7 ms-1 below a wind speed of 20 ms-1. We have also found that the maximum wind speed derived from the SMAP radiometer data can reach 140 knots for severe storms and are generally in good agreement with the hurricane track analysis and operational aircraft Stepped Frequency Microwave Radiometer wind speeds. The spatial patterns of the SMAP SSS agree well with climatological distributions, but exhibit several unique spatial and temporal features.
The effect of adding visible channel (VIS) data to the IR data in satellite rain estimation schemes was investigated by comparing the abilities of satellite threshold schemes based on VIS, IR channel, or bispectral (VIS/IR) data to estimate convective precipitation. Using the methodology of Bellon and Austin (1986), empirical relationships between the satellite and radar data were determined for two areas: the Florida Area Cumulus Experiment (FACE) area and a 25-km area on a side centered on 26 N, 81 W, which was inclusive of the FACE area but exclusive of points within 50 km or greater than 170 km of the Miami WSR-57 radar. The results did not demonstrate an unequivocal effect of VIS data. The normalized rms error data for the three estimation schemes used in a four-day experiment are presented.
A comparison of theoretical calculations with the results of radar meteor observations shows that the theory of radio meteors satisfactorily represents observational data. Radar meteor observations are incompatible with the idea of low density for small meteoroids in the ablation process. The main mechanism of ablation is evaporation. During intensive evaporation, small meteoroids have a density close to that of usual stone meteorites.
Three objectives were outlined: (1) global distribution, geometry and composition of continental rock units; (2) morphology and structure of the continental crust; and (3) monitoring selected surface processes. Mapping soil, sediment and rock characteristics for land surfaces requires the use of visible, reflected, thermal and radio parts of the spectrum. Digital topographic data (elevation, slope angle, slope magnitude) are needed to correct reflectance, emission, and radar data. In addition, images of the topographic data provide fundamental information on the morphology and structure of the land.
A statistical framework for climatological Z-R parameter estimation is developed and simulation experiments are conducted to examine sampling properties of the estimators. Both parametric and nonparametric models are considered. For parametric models, it is shown that Z-R parameters can be estimated by maximum likelihood, a procedure with optimal large sample properties. A general nonparametric framework for climatological Z-R estimation is also developed. Nonparametric procedures are attractive because of their flexibility in dealing with certain types of measurement errors common to radar data. Simulation experiments show that even under favorable assumptions on error characteristics of radar and raingages, large datasets are required to obtain accurate Z-R parameter estimates. Another important conclusion is that estimation results are generally quite sensitive to radar and raingage measurement thresholds. For fixed sample size, the simulation results can be used to provide quantitative assessments of the accuracy of Z-R model parameter estimates. These results are particularly useful for error analysis of precipitation products that are derived using climatological Z-R relations. One example is the large-area rainfall estimates derived using the height-area rainfall threshold (HART) technique.
The objectives of this hydrologic cycle study are to understand and model (1) surface energy and land-atmosphere water transfer processes, and (2) interactions between convective storms and surface energy fluxes. A surface energy budget measurement campaign was carried out by an interdisciplinary science team during the period July 8 - August 19, 1991 as part of the Convection and Precipitation/Electrification Experiment (CaPE) in the vicinity of Cape Canaveral, FL. Among the research themes associated with CaPE is the remote estimation of rainfall. Thus, in addition to surface radiation and energy budget measurements, surface mesonet, special radiosonde, precipitation, high-resolution satellite (SPOT) data, geosynchronous (GOES) and polar orbiting (DMSP SSM/I, OLS; NOAA AVHRR) satellite data, and high altitude airplane data (AMPR, MAMS, HIS) were collected. Initial quality control of the seven surface flux station data sets has begun. Ancillary data sets are being collected and assembled for analysis. Browsing of GOES and radar data has begun to classify days as disturbed/undisturbed to identify the larger scale forcing of the pre-convective environment, convection storms and precipitation. The science analysis plan has been finalized and tasks assigned to various investigators.
A common problem for archaeologists studying ancient settlement in the Maya Lowlands is overcoming the dense vegetation in order to obtain an accurate regional perspective of the presence of archaeological sites, their exact locations and their overall extents. Most often this is done by extensive ground surveys in which many individuals chop parallel paths through the vegetation in search of sites. Once a site is found an effort is made to mark its location on a regional map and to explore its perimeter. Obtaining locational information has been made dramatically easier in recent years with the advent of improved Global Positioning Systems (GPS), however the process of initial identification of sites and the determination of their borders is exceedingly labor intensive and has remained relatively unchanged since the beginning of settlement surveys in the region in the 1950 s. Currently, we are revolutionizing settlement survey in the Maya Lowlands by using remotely sensed data from IKONOS, Quickbird, and Eo 1, satellites as well as airborne AIRSAR radar data. The Ancient Maya built their cities, towns and even their smallest hamlets using excavated limestone and lime plasters. We propose that the decay of these structures provides a unique microenvironment for the growth of vegetation as the levels of moisture and nutrition within the ruins vary substantially from those in the surrounding forest. These microenvironmental differences on the ground are likewise represented by compositional differences in the forest canopy both in the species present and in leaf color (representing moisture/nutritional stress) visible through the analysis of high-resolution satellite data. In this way the detailed analysis of forest composition can reveal a detailed picture of the ancient settlements that lie beneath it. Preliminary examinations using this technique have been very successful and we are refining these techniques in order to efficiently comprehend the details of Ancient Maya settlement in the Lowlands.
As we continue to advance the U.S. National Airspace into the next generation of air traffic, we face challenges in both increase in complexity, as well as, a significant growth in traffic volume. Addressing these challenges, while maintaining the same level of safety is an important application of data mining. Because of these significant shifts in airspace design and usage there is a need to identify current and emergent safety risks along with their potential precursors. In recent years NASA has made advancements in developing scalable methods to address this effort in the Big Data paradigm. Multiple kernel anomaly detection approaches have been employed on both surveillance radar data and flight operational quality assurance data to identify operationally significant safety risks. Additionally, events have been explored with a recently developed precursor identification tool to discover states that reveal an increased probability of a safety event. These tools can be used to discover emerging safety risks that may not be currently monitored, which allows for mitigation tactics to be employed and ultimately make the overall airspace safer. This talk will discuss an overview of these methods and a discussion of the findings.
On 07 March 2018 at 20:05 local time (08 March 03:05 UTC), a dramatic meteor occurred over Olympic Coast National Marine Sanctuary (OCNMS) off of the Washington state coast (“OCNMS fall”, henceforth). Data to include seismometry (from both on-shore and submarine seismometers), weather radar imagery (Figure 1), and a moored weather buoy, were used to accurately identify the fall site. The site was visited by the exploration vessel E/V Nautilus (Ocean Exploration Trust) on 01 July 2018 [1] and by the research vessel R/V Falkor (Schmidt Ocean Institute) from 03-06 June 2019. Remotely operated vehicles (ROVs) from both vessels were used to search for meteorites and sample seafloor sediments. These expeditions performed the first attempts to recover meteorites from a specific observed fall in the open ocean. Analysis of weather radar data indicates that this fall was unusually massive and featured meteorites of unusually high mechanical toughness, such that large meteorites were disproportionately produced compared to other meteorite falls (Figure 2)[2-4]. We report the recovery of many (>100) micrometeorite-sized melt spherules and other fragments, and one small (~1mm3 ) unmelted meteorite fragment identified to date. Approximately 80% of the fragments were recovered from a single sample, collected from a round pit in the seafloor sediment. Melt spherules are almost exclusively type I iron-rich spherules with little discernible oxidation. Analyses are currently underway to attempt to answer the primary science question by identifying the parent meteorite type. Also, differences in the number and nature of samples collected by Nautilus and Falkor reveal a distinct loss rate to oxidation over the 15 months following the fall that is useful to inform future recovery efforts.