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At least 361 records · Page 20

Data Assimilation in the Ocean and in the Atmosphere: What Should be Next?

As part of the International Symposium on Assimilation of Observation in Meteorology and Oceanography, a panel discussion was held on the evening of 15 March 1995. The purpose of this panel discussion was focus on what the next major areas of research in data assimilation should be. The panelists had five minutes each for short presentations (Kalman filters, representers, etc.) and this was followed by an open discussion. This preprocessing will require a good understanding of the fine-scale phenomena. Least square methods such as Kalman filters and variational schemes are inefficient estimators of non-Gaussian field such as chemical traces. Regardless of the modeling technique employed (Lagrangian methods seem best), a least squares assimilation scheme will smear fine structure. The estimator of maximum likelihood must be sought, by examination of tracer probability distributions.

Kalnay, Eugenia↗

Implicit determination of multispectral scanner data variation over extended areas.

Description of a method by which variations in aerial multispectral scanner data can be accounted for when there is insufficient ground truth information. The data are suitably filtered and smoothed along the flight line, and the reduced results are presented in a form such that the investigator can readily determine the preprocessing that should be used and the spatial extent to which it should be applied. An algorithm is developed for the detection of cloud-shadowed areas.

Kriegler, F. J.↗

Computer vision techniques for rotorcraft low altitude flight

Rotorcraft operating in high-threat environments fly close to the earth's surface to utilize surrounding terrain, vegetation, or manmade objects to minimize the risk of being detected by an enemy. Increasing levels of concealment are achieved by adopting different tactics during low-altitude flight. Rotorcraft employ three tactics during low-altitude flight: low-level, contour, and nap-of-the-earth (NOE). The key feature distinguishing the NOE mode from the other two modes is that the whole rotorcraft, including the main rotor, is below tree-top whenever possible. This leads to the use of lateral maneuvers for avoiding obstacles, which in fact constitutes the means for concealment. The piloting of the rotorcraft is at best a very demanding task and the pilot will need help from onboard automation tools in order to devote more time to mission-related activities. The development of an automation tool which has the potential to detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles, presents challenging problems. Research is described which applies techniques from computer vision to automation of rotorcraft navigtion. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle-detection approach can be used as obstacle data for the obstacle avoidance in an automatic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. The presentation concludes with some comments on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

An Automated Flying-Insect-Detection System

An automated flying-insect-detection system (AFIDS) was developed as a proof-of-concept instrument for real-time detection and identification of flying insects. This type of system has use in public health and homeland security decision support, agriculture and military pest management, and/or entomological research. Insects are first lured into the AFIDS integrated sphere by insect attractants. Once inside the sphere, the insect's wing beats cause alterations in light intensity that is detected by a photoelectric sensor. Following detection, the insects are encouraged (with the use of a small fan) to move out of the sphere and into a designated insect trap where they are held for taxonomic identification or serological testing. The acquired electronic wing beat signatures are preprocessed (Fourier transformed) in real-time to display a periodic signal. These signals are sent to the end user where they are graphically displayed. All AFIDS data are pre-processed in the field with the use of a laptop computer equipped with LABVIEW. The AFIDS software can be programmed to run continuously or at specific time intervals when insects are prevalent. A special DC-restored transimpedance amplifier reduces the contributions of low-frequency background light signals, and affords approximately two orders of magnitude greater AC gain than conventional amplifiers. This greatly increases the signal-to-noise ratio and enables the detection of small changes in light intensity. The AFIDS light source consists of high-intensity Al GaInP light-emitting diodes (LEDs). The AFIDS circuitry minimizes brightness fluctuations in the LEDs and when integrated with an integrating sphere, creates a diffuse uniform light field. The insect wing beats isotropically scatter the diffuse light in the sphere and create wing beat signatures that are detected by the sensor. This configuration minimizes variations in signal associated with insect flight orientation.

Vann, Timi↗

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 SAR data provides high resolution (5-10 m) imagery, unaffected by cloud cover and light availability (day vs. night), common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band (once operational and available on the GEE repository) synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a Terra Moderate Resolution Imaging Spectroradiometer (MODIS) snow product to determine regional snow coverage, which affects land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd wetland 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.

Inundation↗

Basic research planning in mathematical pattern recognition and image analysis

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

Bryant, J.↗

Computer vision techniques for rotorcraft low-altitude flight

A description is given of research that applies techniques from computer vision to automation of rotorcraft navigation. The effort emphasizes the development of a methodology for detecting the ranges to obstacles in the region of interest based on the maximum utilization of passive sensors. The range map derived from the obstacle detection approach can be used as obstacle data for the obstacle avoidance in an automataic guidance system and as advisory display to the pilot. The lack of suitable flight imagery data, however, presents a problem in the verification of concepts for obstacle detection. This problem is being addressed by the development of an adequate flight database and by preprocessing of currently available flight imagery. Some comments are made on future work and how research in this area relates to the guidance of other autonomous vehicles.

Sridhar, Banavar↗

Overview of the LaNCETS Flight Experiment and CFD Analysis. Supplemental Movies

This presentation focuses on nearfield airborne pressure signatures from the Lift and Nozzle Change Effect on Tail Shocks (LaNCETS) flight test experiment. The primary motivation for nearfield probing in the supersonic regime is to measure the shock structure of aircraft in an ongoing effort to overcome the overland sonic boom barrier for commercial supersonic transportation. LaNCETS provides the opportunity to investigate lift distribution and engine plume effects. During Phase 1 flight testing an F-15B was used to probe the F-15 LaNCETS aircraft in order to validate CFD and pre-flight prediction tools. A total of 29 probings were taken at 40,000 ft. altitude at Machs 1.2, 1.4 and 1.6. LaNCETS Phase 1 flight data are presented as a detailed pressure signature superimposed over a picture of the LaNCETS aircraft. The attenuation of the Inlet-Canard shocks with distance as well as its forward propagation and the coalescence of the noseboom shock are illustrated. A detailed CFD study on a simplified LaNCETS aircraft jet nozzle was performed providing the ability to more accurately capture the shocks from the propulsion system and emphasizing how under- and over-expanding the nozzle affects the existence of shock trains inside the jet plume. With Phase 1 being a success preparations are being made to move forward to Phase 2. Phase 2 will fly similar flight conditions, but this time changing the aircraft's lift distribution by biasing the canard positions, and changing the plume shape by under- and over-expanding the nozzle. Nearfield probing will again be completed in the same manner as in Phase 1. An additional presentation focuses on LaNCETS CFD solution methodology. Discussions highlight grid preprocessing, grid shearing and stretching, flow solving and contour plots. Efforts are underway to better capture the flow features via grid modification and flow solution methodology, which will help to achieve better agreement with flight data. An included CD-ROM provides animations of the nearfield probing procedure and of real data from one of the probings integrated with GPS positional and velocity data. An additional in-flight video from the rear seat of the probing aircraft is also provided.

Cliatt, Larry J., II↗

Extraction of ozone and chlorophyll-A distribution from AVIRIS data

The potential of airborne imaging spectrometry for assessing and monitoring natural resources is studied. Therefore, an AVIRIS scene of the NASA's MacEurope 1991 campaign - acquired in Central Switzerland - is used. The test site consists of an urban area, the Lake Zug with its surrounding fields, the Rigi mountain in the center of the test site, and the Lake of Four Cantons. The region is covered by the AVIRIS flight #910705, run 6 and 7 of the NASA ER-2 aircraft resulting in an average nominal pixel size of about 18 m. Simultaneous to the ER-2 overflight spectroradiometric measurements have been taken in various locations. Preselected reference targets were measured in the field with a GER Mark V spectroradiometer, and radiance measurements were taken to the lake using a Li-Cor LI 1800UW specroradiometer below and above the water surface. A comprehensive meteorological data set was obtained by joining the POLLUMET experiment which carried out measurements to investigate the summer smog in Switzerland on the same day. The quality assessment for the actual data set can be found in detail in Meyer et al. A parametric approach calculating the location of the airplane was used to simulate the observation geometry. This parametric preprocessing procedure, which takes care of effects of flight line and attitude variations as well as the pixel-by-pixel topographic corrections is described in Meyer.

Schaepman, M.↗

An intelligent user interface for browsing satellite data catalogs

A large scale domain-independent spatial data management expert system that serves as a front-end to databases containing spatial data is described. This system is unique for two reasons. First, it uses spatial search techniques to generate a list of all the primary keys that fall within a user's spatial constraints prior to invoking the database management system, thus substantially decreasing the amount of time required to answer a user's query. Second, a domain-independent query expert system uses a domain-specific rule base to preprocess the user's English query, effectively mapping a broad class of queries into a smaller subset that can be handled by a commercial natural language processing system. The methods used by the spatial search module and the query expert system are explained, and the system architecture for the spatial data management expert system is described. The system is applied to data from the International Ultraviolet Explorer (IUE) satellite, and results are given.

Cromp, Robert F.↗

An intelligent user interface for browsing satellite data catalogs

A large scale domain-independent spatial data management expert system that serves as a front-end to databases containing spatial data is described. This system is unique for two reasons. First, it uses spatial search techniques to generate a list of all the primary keys that fall within a user's spatial constraints prior to invoking the database management system, thus substantially decreasing the amount of time required to answer a user's query. Second, a domain-independent query expert system uses a domain-specific rule base to preprocess the user's English query, effectively mapping a broad class of queries into a smaller subset that can be handled by a commercial natural language processing system. The methods used by the spatial search module and the query expert system are explained, and the system architecture for the spatial data management expert system is described. The system is applied to data from the International Ultraviolet Explorer (IUE) satellite, and results are given.

Cromp, Robert F.↗

Agricultural requirements for precipitation measurements

The requirements for precipitation measurements from space for hydrologic forecasting applications are discussed. The structure of the hydrologic forecasting service of the National Weather Service (NWS) is described, and an attempt is made to estimate the sampling and accuracy requirements for a range of spatial and temporal averaging scales corresponding to various NWS hydrologic applications. Finally, the data base requirements are addressed. The critical point is made that for the data source to be most useful operationally at the NWS River Forecast Centers, the data must be available on-line in a format compatible with computer processing. Several data base systems are illustrated in a scenario for a multi-sensor rainfall analysis system (MSRANS). Actually, MSRANS is the software existing within the various computer environments required to preprocess, process, and analyze rainfall information from multiple sources.

Strommen, N. D.↗

A prototype expert system in OPS5 for data error detection

A prototype expert system has been developed in the OPS5 language to perform error checking on data which spacecraft builders/users supply to the NASA Goddard Space Flight Center for processing on the Communications Link Analysis and Simulation System (CLASS) computer. This prototype expert system, called Trajectory Preprocessing System (TRAPS), contains 49 rules. In its operational phase, TRAPS will run in the Oak Ridge Production Language (ORPL) on the CLASS computer. ORPL, an implementation of OPS5 in MULTIFORTH on a desktop computer, is now being ported to SS-FORTH on the CLASS computer. This paper discusses the expert system problem domain, development approch, tools, results, and future plans stemming from the TRAPS project.

Rash, James↗

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗

Compression of high spectral resolution imagery

The Earth Orbiting Satellite (EOS), scheduled for launch in the mid-1990s, will include a next-generation multispectral imaging system (HIRIS) having unprecedented spatial and spectral resolution. Its high resolution, however, comes at the cost of a raw data rate which exceeds the communication channel capacity assigned to the entire EOS mission. This paper explores noisy compression algorithms which may compress multispectral data by up to 30:1 or more. Algorithm performance is measured using both traditional and mission-oriented criteria (e.g., feature classification consistency). It is shown that vector quantization, merged with suitable preprocessing techniques, is the most viable candidate.

Baker, Richard L.↗

Integration of geometric modeling and advanced finite element preprocessing

The structure to a geometry based finite element preprocessing system is presented. The key features of the system are the use of geometric operators to support all geometric calculations required for analysis model generation, and the use of a hierarchic boundary based data structure for the major data sets within the system. The approach presented can support the finite element modeling procedures used today as well as the fully automated procedures under development.

Shephard, Mark S.↗

Image-plane processing of visual information

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Huck, F. O.↗

Program Aids Specification Of Multiple-Block Grids

3DPREP computer program aids specification of multiple-block computational grids. Highly interactive graphical preprocessing program designed for use on powerful graphical scientific computer workstation. Divided into three main parts, each corresponding to principal graphical-and-alphanumerical display. Relieves user of some burden of collecting and formatting many data needed to specify blocks and grids, and prepares input data for NASA's 3DGRAPE grid-generating computer program.

Sorenson, R. L.↗