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Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

Hoffer, R. M.↗

Testing the Drop-Size Distribution-Based Separation of Stratiform and Convective Rain Using Radar and Disdrometer Data from a Mid-Latitude Coastal Region

Stratiform and convective rain are associated with different microphysical processes and generally produce drop-size distributions (DSDs) with different characteristics. Previous studies using data from (a) a tropical coastal location, (b) a mid-latitude continental location with semi-arid climate, and (c) a sub-tropical continental location, found that the two rain types could be separated in the NW–Dm space, where Dm is the mass-weighted mean diameter and NW is the normalized intercept parameter. In this paper, we investigate the same separation technique using data and observations from a mid-latitude coastal region. Three-minute DSDs from disdrometer measurements are used for the NW- versus Dm-based classification and are compared with simultaneous observations from an S-band polarimetric radar 38 km away from the disdrometer site. Specifically, RHI (range-height indicator) scans over the disdrometer were used for confirmation. Results show that there was no need to modify the separation criteria from previous studies. Three-minute DSDs from the same location were used as input to scattering calculations to derive retrieval equations for NW and Dm for the S-band radar using an improved technique and applied to the RHI scans to identify convective and stratiform rain regions. Two events are shown as illustrative examples.

Merhala Thurai↗

Observations of vertical velocity power spectra with the SOUSY VHF radar

A data set taken with the SOUSY VHF radar from October 28 to November 13, 1981 was used to calculate the power spectrum of the vertical velocities directly from the vertical beam measurements. The spectral slopes for the frequency spectra have been determined out to periods of several days and have been found to have values near -1 in the troposphere and shallower slopes in the lower stratosphere. The value of -1 is in agreement with the value found by Larsen et al. (1985) and Balsley and Carter (1982) in the range from a few minutes to 1 hr.

Larsen, M. F.↗

An analysis of multi-frequency high resolution radar rain rate data

Approximately 100,000 records of data at 3.05, 9.35, and 15.56 GHz, each set associated with a single look angle, are edited and analyzed to determine the characteristic dimensions of the rain cells observed and the rain rate distributions within these cells. The results, consistent with earlier results, demonstrate the feasibility of using attenuating frequency radars for high resolution rain rate measurements.

Devasirvatham, D. M. J.↗

Extraction of quantitative surface characteristics from AIRSAR data for Death Valley, California

Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were collected for the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley, California, USA, in Sep. 1989. AIRSAR is a four-look, quad-polarization, three frequency instrument. It collects measurements at C-band (5.66 cm), L-band (23.98 cm), and P-band (68.13 cm), and has a GIFOV of 10 meters and a swath width of 12 kilometers. Because the radar measures at three wavelengths, different scales of surface roughness are measured. Also, dielectric constants can be calculated from the data. The AIRSAR data were calibrated using in-scene trihedral corner reflectors to remove cross-talk; and to calibrate the phase, amplitude, and co-channel gain imbalance. The calibration allows for the extraction of accurate values of rms surface roughness, dielectric constants, sigma(sub 0) backscatter, and polarization information. The radar data sets allow quantitative characterization of small scale surface structure of geologic units, providing information about the physical and chemical processes that control the surface morphology. Combining the quantitative information extracted from the radar data with other remotely sensed data sets allows discrimination, identification and mapping of geologic units that may be difficult to discern using conventional techniques.

Kierein-Young, K. S.↗

Detection of lowland flooding using active microwave systems

The development of radar systems with longer wavelenths (greater than 3 cm) has provided new possibilities regarding the utilization of radar. Thus, it has been found that the interpretation of data from radar images can be a valuable classification aid for applications related to water resources. In the case of an interpreter accustomed to photographic or visible/infrared images, an evaluation of radar images presents some problems, because the radar is sensing a set of surface characteristics which have little influence on visible/infrared systems. Detectable features in radar images caused by differences in dielectric properties are usually associated with the water content of either soils or vegetation. The present paper is concerned with studies which were initiated in 1976. The studies had the objective to define the magnitude of the effects on radar data caused by flood waters under vegetation. The obtained results indicate the feasibility to detect flood conditions beneath a forest canopy, and to obtain an improved definition of the land-water boundary.

Ormsby, J. P.↗

Image processing for hazard recognition in on-board weather radar

A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

Kelly, Wallace E.↗

Radar cross-section measurements and simulation of a tethered satellite. The small expendable deployer system end-mass payload

The first Small Expendable Deployer System (SEDS-1), a tethered satellite system, was developed by NASA and launched March 29, 1993 as a secondary payload on a United State Air Force (USAF) Delta-2 launch vehicle. The SEDS-1 successfully deployed an instrumented end-mass payload (EMP) on a 20-km nonconducting tether from the second stage of the Delta 2. This paper describes the effort of NASA Langley Research Center's Antenna and Microwave Research Branch to provide assistance to the SEDS Investigators Working Group (IWG) in determining EMP dynamics by analyzing the mission radar skin track data. The radar cross section measurements taken and simulations done for this study are described and comparisons of the measured data with the simulated data for the EMP at 6 GHz are presented.

Cravey, Robin L.↗

Data Acquisition System for Multi-Frequency Radar Flight Operations Preparation

A three-channel data acquisition system was developed for the NASA Multi-Frequency Radar (MFR) system. The system is based on a commercial-off-the-shelf (COTS) industrial PC (personal computer) and two dual-channel 14-bit digital receiver cards. The decimated complex envelope representations of the three radar signals are passed to the host PC via the PCI bus, and then processed in parallel by multiple cores of the PC CPU (central processing unit). The innovation is this parallelization of the radar data processing using multiple cores of a standard COTS multi-core CPU. The data processing portion of the data acquisition software was built using autonomous program modules or threads, which can run simultaneously on different cores. A master program module calculates the optimal number of processing threads, launches them, and continually supplies each with data. The benefit of this new parallel software architecture is that COTS PCs can be used to implement increasingly complex processing algorithms on an increasing number of radar range gates and data rates. As new PCs become available with higher numbers of CPU cores, the software will automatically utilize the additional computational capacity.

Leachman, Jonathan↗

The life cycle of thunderstorm gust fronts as viewed with Doppler radar and rawinsonde data

This paper presents the time-dependent analysis of the thunderstorm gust front with the use of Project NIMROD data. RHI cross sections of reflectivity and Doppler velocity are constructed to determine the entire vertical structure. The life cycle of the gust front is divided into four stages: (1) the formative stage; (2) the early mature stage; (3) the late mature stage; and (4) the dissipation stage. A new finding is a horizontal roll detected in the reflectivity pattern resulting from airflow that is deflected upward by the ground, while carrying some of the smaller precipitation ahead of the main echo core of the squall line. This feature is called a 'precipitation roll'. As determined from rawinsonde data, the cold air behind the gust front accounts for the observed surface pressure rise. Calculations confirm that the collision of two fluids produce a nonhydrostatic pressure at the leading edge of the outflow. The equation governing the propagation speed of a density current accurately predicts the movement of the gust front.

Wakimoto, R. M.↗

A method of classification for multisource data in remote sensing based on interval-valued probabilities

An axiomatic approach to intervalued (IV) probabilities is presented, where the IV probability is defined by a pair of set-theoretic functions which satisfy some pre-specified axioms. On the basis of this approach representation of statistical evidence and combination of multiple bodies of evidence are emphasized. Although IV probabilities provide an innovative means for the representation and combination of evidential information, they make the decision process rather complicated. It entails more intelligent strategies for making decisions. The development of decision rules over IV probabilities is discussed from the viewpoint of statistical pattern recognition. The proposed method, so called evidential reasoning method, is applied to the ground-cover classification of a multisource data set consisting of Multispectral Scanner (MSS) data, Synthetic Aperture Radar (SAR) data, and digital terrain data such as elevation, slope, and aspect. By treating the data sources separately, the method is able to capture both parametric and nonparametric information and to combine them. Then the method is applied to two separate cases of classifying multiband data obtained by a single sensor. In each case a set of multiple sources is obtained by dividing the dimensionally huge data into smaller and more manageable pieces based on the global statistical correlation information. By a divide-and-combine process, the method is able to utilize more features than the conventional maximum likelihood method.

Kim, Hakil↗

Recent Measurements of the Orbital Debris Environment at NASA Johnson Space Center

Space debris presents many challenges to current space operations. Although, the probability of collision between an operational spacecraft and a piece of space debris is quite small, the potential losses can be quite high. Prior to 1990, characterization of the orbital debris environment was divided into two categories. Objects larger than 10 cm are monitored by the United States Space Surveillance Network (SSN) and documented in the U.S. Space Command (USSPACECOM) catalog. Knowledge of debris smaller than 0.1 cm has come from the analyses of returned surfaces. The lack of information about the debris environment in the size range from 0.1 to 1 0 cm led to a joint NASA-DOD effort for orbital debris measurements using the Haystack radar and the unbuilt Haystack Auxiliary (HAX) radars. The data from these radars have been critical to the design of shielding for the International Space Station and have been extensively used in the creation of recent models describing the orbital debris environment. Recent debris campaigns have been conducted to verify and validate through comparative measurements, the results and conclusions drawn from the Haystack/HAX measurements. The Haystack/HAX measurements and results will be described as well as the results of the recent measurement campaigns.

Stansbery, E. G.↗

NASA Tech Briefs, December 2004

opics include: High-Rate Digital Receiver Board; Signal Design for Improved Ranging Among Multiple Transceivers; Automated Analysis, Classification, and Display of Waveforms; Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO; Format for Interchange and Display of 3D Terrain Data; Program Analyzes Radar Altimeter Data; Indoor Navigation using Direction Sensor and Beacons; Software Assists in Responding to Anomalous Conditions; Software for Autonomous Spacecraft Maneuvers; WinPlot; Software for Automated Testing of Mission-Control Displays; Nanocarpets for Trapping Microscopic Particles; Precious-Metal Salt Coatings for Detecting Hydrazines; Amplifying Electrochemical Indicators; Better End-Cap Processing for Oxidation-Resistant Polyimides; Carbon-Fiber Brush Heat Exchangers; Solar-Powered Airplane with Cameras and WLAN; A Resonator for Low-Threshold Frequency Conversion; Masked Proportional Routing; Algorithm Determines Wind Speed and Direction from Venturi-Sensor Data; Feature-Identification and Data-Compression Software; Alternative Attitude Commanding and Control for Precise Spacecraft Landing; Inspecting Friction Stir Welding using Electromagnetic Probes; and Helicity in Supercritical O2/H2 and C7H16/N2 Mixing Layers.

Source record↗

A traffic accident dataset for Chattanooga, Tennessee

This publication presents an annotated accident dataset which fuses traffic data from radar detection sensors, weather condition data, and light condition data with traffic accident data (as illustrated in Fig. 1) in a format that is easy to process using machine learning tools, databases, or data workflows. The purpose of this data is to analyze, predict, and detect traffic patterns when accidents occur. Each file contains a timeseries of traffic speeds, flows, and occupancies at the sensor nearest to the accident, as well as 5 neighboring sensors upstream and downstream. It also contains information about the accident type, date, and time. In addition to the accident data, we provide baseline data for typical traffic patterns during a given time of day. Overall, the dataset contains 6 months of annotated traffic data from November 2020 to April 2021. During this timeframe, and 361 accidents occurred in the monitored area around Chattanooga, Tennessee. This dataset served as the basis for a study on topology-aware automated accident detection for a companion publication [1].

97 MATHEMATICS AND COMPUTING↗

Data processing techniques used with MST radars: A review

The data processing methods used in high power radar probing of the middle atmosphere are examined. The radar acts as a spatial filter on the small scale refractivity fluctuations in the medium. The characteristics of the received signals are related to the statistical properties of these fluctuations. A functional outline of the components of a radar system is given. Most computation intensive tasks are carried out by the processor. The processor computes a statistical function of the received signals, simultaneously for a large number of ranges. The slow fading of atmospheric signals is used to reduce the data input rate to the processor by coherent integration. The inherent range resolution of the radar experiments can be improved significant with the use of pseudonoise phase codes to modulate the transmitted pulses and a corresponding decoding operation on the received signals. Commutability of the decoding and coherent integration operations is used to obtain a significant reduction in computations. The limitations of the processors are outlined. At the next level of data reduction, the measured function is parameterized by a few spectral moments that can be related to physical processes in the medium. The problems encountered in estimating the spectral moments in the presence of strong ground clutter, external interference, and noise are discussed. The graphical and statistical analysis of the inferred parameters are outlined. The requirements for special purpose processors for MST radars are discussed.

Rastogi, P. K.↗