Solid state image sensor research
Solid state image sensing devices developed for meteorological satellite applications
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Solid state image sensing devices developed for meteorological satellite applications
Storage device is applicable in memory systems and in high-resolution arrays for light-responsive image sensing. The device offers high yield in multiple arrays and allows charge release with light striking only the edge of a metal electrode.
The current and near-future state-of-the-art in visual simulation equipment technology is related to the requirements of the space shuttle visual system. Image source, image sensing, and displays are analyzed on a subsystem basis, and the principal conclusions are used in the formulation of a recommended baseline visual system. Perceptibility and visibility are also analyzed.
Laboratory and field transmissometer studies on the effect of suspended particulate material upon the appearance of water are reported. Quantitative correlations were developed between remotely sensed image density, optical sea truth data, and actual sediment load. Evaluation of satellite image sea truth data for an offshore plume projects contours of transmissivity for two different tidal phases. Data clearly demonstrate the speed of change and movement of the optical plume for water patterns associated with the mouth of Mobile bay in which relatively clear Gulf of Mexico water enters the bay on the eastern side. Data show that wind stress in excess of 15 knots has a marked impact in producing suspended sediment loads.
Activities of the University of Alabama in support of state and local planning commissions are reported. Demonstrations were given of the various types of remotely sensed images available from U-2, Skylab, and LANDSAT; and their uses and limitations were discussed. Techniques to be used in determining flood prone areas were provided for environmental studies. A rapid, inexpensive method for study was developed by which imagery is copied on 35 mm film and projected on existing topographic maps for measuring delta volume and growth.
On May 17, 1977, a remote sensing experiment was conducted on the James River, Virginia, whereby thermal spectrometer and near-infrared photography data of thermal discharges at Hopewell and the Surry nuclear power plant were obtained by an aircraft for one tidal cycle. These data were used in subsequent investigations into the near field discharge trajectories. For the Gravelly Run thermal plume at Hopewell, several empirical expressions for the plume centerline were evaluated by comparisons of the computed trajectories and those observed in the remote sensing images.
A headway sensing system for an automated mixed traffic vehicle (AMTV) employing an array of optical proximity sensor elements is described, and its performance is presented in terms of object detection profiles. The problem of sensing in turns is explored experimentally and requirements for future turn sensors are discussed. A recommended headway sensor configuration, employing multiple source elements in the focal plane of one lens operating together with a similar detector unit, is described. Alternative concepts including laser radar, ultrasonic sensing, imaging techniques, and radar are compared to the present proximity sensor approach. Design concepts for an AMTV body which will minimize the probability of injury to pedestrians or passengers in the event of a collision are presented.
Geologic applications of remotely sensed imaging encompass five areas of interest. The five areas include: (1) enhancement and analysis of individual images; (2) work with small area mosaics of imagery which have been map projection rectified to individual quadrangles; (3) development of large area mosaics of multiple images for several counties or states; (4) registration of multitemporal images; and (5) data integration from several sensors and map sources. Examples for each of these types of applications are summarized.
Five algorithms being developed for performing region-based modeling operations on classified remotely-sensed images are described. The first algorithm converts images from standard grid structure into topological grid structure, while the remaining algorithms act upon topologically grid-structured images to perform region-based relabelling, overlaying, distance searching, and neighborhood scanning operations. The use of precomputed topological information, through the use of topological grid structure, makes region-based algorithms highly accessible to earth scientists.
State of the art applications of remote sensing in geological exploration programs are discussed along with research and development activities aimed at increasing the future capabilities of this technology for exploration geology. The topics considered include: technical issues in the state of the art; regional exploration models; remote sensing applications for hydrocarbon exploration; commercialization of remote sensing satellites; and data integration. Also addressed are: remote sensing applications for mineral exploration; geobotanical and environmental remote sensing; image processing techniques and applications; advanced sensors, radar, and airborne systems; and engineering, logistics, and marine applications.
The Garlock and Death Valley fault zones in SE California are two active strike-slip faults coming together on the east side of the Avawatz Mtns. The kinematics of this intersection, and the possible continuation of either fault zone, are being investigated using a combination of field mapping, and processing and interpretation of remotely sensed image data. Regional and local relationships are derivable from Thematic Mapper data (30 m resolution), including discrimination and relative age dating of alluvial fans, bedrock mapping, and fault mapping. Aircraft data provide higher spatial resolution over more limited areas. Hypotheses being considered are: (1) the Garlock fault extends east of the intersection; (2) the Garlock fault terminates at the intersection and the Death Valley fault continues southeastward; and (3) the Garlock fault has been offset right laterally by the Death Valley fault which continues to the southeast. Preliminary work indicates that the first hypothesis is invalid. From kinematic considerations, image analysis, and field work the third hypothesis is favored. The projected continuation of the Death Valley zone defines the boundary between the Mojave crustal block and the Basin and Range block.
The types of remote sensing images which have applications in geophysical studies are reviewed. Features of the Shuttle Imaging Radar, a synthetic aperture radar, are described and a sample image is provided to illustrate the capabilities for mapping large-scale geological structure. A combined Landsat-Seasat image is shown to yield data on crustal composition. Sea surface topographic features that result from gravitational effects are demonstrated to be amenable to characterization with another Seasat instrument, a radar altimeter. Magsat data allow identification of magnetic perturbations produced by crustal magnetization. Finally, auroral imagery gathered with the Atmospheric Dynamics Explorer are presented which show that the effects of particles bombarding the atmosphere can be detected at UV wavelengths.
A focused-mesh electron multiplier (FMEM) has been combined with a wedge and strip position-sensitive anode to create a novel detector that is considered likely to have a number of applications in space astronomy and laboratory image sensing. Results from the first application of a wedge and strip anode to an FMEM are presented including spatial resolution, spatial linearity, background rate, and pulse risetime. The converted multiplier retains the attributes of an FMEM that made it attractive in the first place, such as low background, high speed, and high dynamic range.
The author examines both theoretically and through a simulation study the feasibility of identifying the location within a large reference gray-level array of a smaller sensed array to an accuracy finer than one pixel. It is assumed that the sensed image before discretization into pixels consists of a translated, but not rotated, section of the reference image with some superposed noise. The theoretical and empirical results show that when the noise has standard deviation no larger than that of a realistic reference field, the upper quartile of the registration error is on the order of 0.25-0.5 pixels.
A technique for deriving large-scale pollution parameters from NIR and visible satellite remote-sensing images obtained over land or water is described and demonstrated on AVHRR images. The method is based on comparison of the upward radiances on clear and hazy days and permits simultaneous determination of aerosol optical thickness with error Delta tau(a) = 0.08-0.15, particle size with error + or - 100-200 nm, and single-scattering albedo with error + or - 0.03 (for albedos near 1), all assuming accurate and stable satellite calibration and stable surface reflectance between the clear and hazy days. In the analysis of AVHRR images of smoke from a forest fire, good agreement was obtained between satellite and ground-based (sun-photometer) measurements of aerosol optical thickness, but the satellite particle sizes were systematically greater than those measured from the ground. The AVHRR single-scattering albedo agreed well with a Landsat albedo for the same smoke.
Satellites acquire information on a global and repetitive basis. They are thus ideal tools for use when global scale and analysis over time is required. Data from satellites comes in digital form which means that it is ideally suited for incorporation in digital data bases and that it can be evaluated using automated techniques. The development of a global multi-source data set which integrates digital information is proposed regarding some 15,000 major industrial sites worldwide with remotely sensed images of the sites. The resulting data set would provide the basis for a wide variety of studies of the global economy. The preliminary results give promise of a new class of global policy model which is far more detailed and helpful to local policy makers than its predecessors. The central thesis of this proposal is that major industrial sites can be identified and their utilization can be tracked with the aid of satellite images.
Research efforts in FY 1990 included studies employing regional scale numerical models as aids in evaluating potential contributions of specific satellite observing systems (current and future) to numerical prediction. One study involves Observing System Simulation Experiments (OSSEs) which mimic operational initialization/forecast cycles but incorporate simulated Advanced Microwave Sounding Unit (AMSU) radiances as input data. The objective of this and related studies is to anticipate the potential value of data from these satellite systems, and develop applications of remotely sensed data for the benefit of short range forecasts. Techniques are also being used that rely on numerical model-based synthetic satellite radiances to interpret the information content of various types of remotely sensed image and sounding products. With this approach, evolution of simulated channel radiance image features can be directly interpreted in terms of the atmospheric dynamical processes depicted by a model. Progress is being made in a study using the internal consistency of a regional prediction model to simplify the assessment of forced diabatic heating and moisture initialization in reducing model spinup times. Techniques for model initialization are being examined, with focus on implications for potential applications of remote microwave observations, including AMSU and Special Sensor Microwave Imager (SSM/I), in shortening model spinup time for regional prediction.
Two essential elements needed in the process of inference and decision-making are prior probabilities and likelihood functions. When both of these components are known accurately and precisely, the Bayesian approach provides a consistent and coherent solution to the problems of inference and decision-making. In many situations, however, either one or both of the above components may not be known, or at least may not be known precisely. This problem of partial knowledge about prior probabilities and likelihood functions is addressed. There are at least two ways to cope with this lack of precise knowledge: robust methods, and interval-valued methods. First, ways of modeling imprecision and indeterminacies in prior probabilities and likelihood functions are examined; then how imprecision in the above components carries over to the posterior probabilities is examined. Finally, the problem of decision making with imprecise posterior probabilities and the consequences of such actions are addressed. Application areas where the above problems may occur are in statistical pattern recognition problems, for example, the problem of classification of high-dimensional multispectral remote sensing image data.