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At least 397 records · Page 22

Modeling, simulation, and analysis of optical remote sensing systems

Remote Sensing of the Earth's resources from space-based sensors has evolved in the past 20 years from a scientific experiment to a commonly used technological tool. The scientific applications and engineering aspects of remote sensing systems have been studied extensively. However, most of these studies have been aimed at understanding individual aspects of the remote sensing process while relatively few have studied their interrelations. A motivation for studying these interrelationships has arisen with the advent of highly sophisticated configurable sensors as part of the Earth Observing System (EOS) proposed by NASA for the 1990's. Two approaches to investigating remote sensing systems are developed. In one approach, detailed models of the scene, the sensor, and the processing aspects of the system are implemented in a discrete simulation. This approach is useful in creating simulated images with desired characteristics for use in sensor or processing algorithm development. A less complete, but computationally simpler method based on a parametric model of the system is also developed. In this analytical model the various informational classes are parameterized by their spectral mean vector and covariance matrix. These class statistics are modified by models for the atmosphere, the sensor, and processing algorithms and an estimate made of the resulting classification accuracy among the informational classes. Application of these models is made to the study of the proposed High Resolution Imaging Spectrometer (HRIS). The interrelationships among observational conditions, sensor effects, and processing choices are investigated with several interesting results.

Kerekes, John Paul↗

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Davis, Frank W.↗

Applying remote sensing and GIS techniques in solving rural county information needs

The project designed was to acquaint county government officials and their clientele with remote sensing and GIS products that contain information about land conditions and land use. Other users determined through the course of this project were federal agencies working at the county level, agricultural businesses and others in need of spatial information. The specific project objectives were: (1) to investigate the feasibility of using remotely sensed data to identify and quantify specific land cover categories and conditions for purposes of tax assessment, cropland area measurements and land use evaluation; (2) to investigate the use of satellite remote sensing data as an aid in assessing soil management practices; and (3) to evaluate the use of remotely sensed data to assess soil resources and conditions which affect productivity.

Johannsen, Chris J.↗

Pneumatic distortion compensation for aircraft surface pressure sensing devices

In this paper a technique of compensating for pneumatic distortion in aircraft surface pressure sensing devices is developed. The compensation allows conventional pressure sensing technology to obtain improved unsteady pressure measurements. Pressure distortion caused by frictional attenuation and pneumatic resonance within the sensing system makes obtaining unsteady pressure measurements by conventional sensors difficult. Typically, most of the distortion occurs within the pneumatic tubing used to transmit pressure impulses from the surface of the aircraft to the measurement transducer. This paper develops a second-order distortion model that accurately describes the behavior of the primary wave harmonic of the pneumatic tubing. The model is expressed in state-variable form and is coupled with standard results from minimum-variance estimation theory to develop an algorithm to compensate for the effects of pneumatic distortion. Both postflight and real-time algorithms are developed and evaluated using simulated and flight data. Covariance selection and filter-tuning examples are presented. Results presented verify that, given appropriate covariance magnitudes, the algorithms accurately reconstruct surface pressure values from remotely sensed pressure measurements.

Whitmore, Stephen A.↗

Remote sensing of Earth terrain

Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Kong, J. A.↗

Reliable fusion of control and sensing in intelligent machines

Although robotics research has produced a wealth of sophisticated control and sensing algorithms, very little research has been aimed at reliably combining these control and sensing strategies so that a specific task can be executed. To improve the reliability of robotic systems, analytic techniques are developed for calculating the probability that a particular combination of control and sensing algorithms will satisfy the required specifications. The probability can then be used to assess the reliability of the design. An entropy formulation is first used to quickly eliminate designs not capable of meeting the specifications. Next, a framework for analyzing reliability based on the first order second moment methods of structural engineering is proposed. To ensure performance over an interval of time, lower bounds on the reliability of meeting a set of quadratic specifications with a Gaussian discrete time invariant control system are derived. A case study analyzing visual positioning in robotic system is considered. The reliability of meeting timing and positioning specifications in the presence of camera pixel truncation, forward and inverse kinematic errors, and Gaussian joint measurement noise is determined. This information is used to select a visual sensing strategy, a kinematic algorithm, and a discrete compensator capable of accomplishing the desired task. Simulation results using PUMA 560 kinematic and dynamic characteristics are presented.

Mcinroy, John E.↗

Remote sensing of atmospheric chemistry; Proceedings of the Meeting, Orlando, FL, Apr. 1-3, 1991

The present volume on remote sensing of atmospheric chemistry discusses special remote sensing space observations and field experiments to study chemical change in the atmosphere, network monitoring for detection of stratospheric chemical change, stratospheric chemistry studies, and the combining of model, in situ, and remote sensing in atmospheric chemistry. Attention is given to the measurement of tropospheric carbon monoxide using gas filter radiometers, long-path differential absorption measurements of tropospheric molecules, air quality monitoring with the differential optical absorption spectrometer, and a characterization of tropospheric methane through space-based remote sensing. Topics addressed include microwave limb sounder experiments for UARS and EOS, an overview of the spectroscopy of the atmosphere using an FIR emission experiment, the detection of stratospheric ozone trends by ground-based microwave observations, and a FIR Fabry-Perot spectrometer for OH measurements.

Mcelroy, James L.↗

Fiber Optic Sensing System Measures Small Displacements

Fiber optic sensing system measures small changes in intensity of light propagating through its interferometric sensing head. Quantity determined using this approach is displacement or any other phenomenon that affects intensity of light. Sensing scheme involves imbalanced fiber optic interferometer as sensing head and amplitude modulation and detection at two radio frequencies. One important advantage over prior fiber sensors involving pulse-amplitude modulation is length of imbalance shorter.

Adamovsky, Grigory↗

Remote sensing studies of the northeastern portion of the lunar nearside

During the Galileo spacecraft encounter with the Earth-Moon system in December, 1992, a variety of spectral data and imagery were obtained for the eastern limb region as well as much of the lunar nearside. In order to support this encounter, we have been collecting near-infrared spectra and other remote sensing data for that portion of the northeastern nearside (NEM region) for which the highest resolution Galileo data were obtained. Analysis of spectra obtained for highlands units in the NEN region indicates that most surface units are dominated by anorthositic norite. To date, no pure anorthosites have been identified in the region. Several dark-haloed impact craters have exposed mare material from beneath highlands-rich surface units. Hence, ancient mare volcanism occurred in at least a portion of the NEN region. Endogenic dark-haloed craters in the region are the source of localized dark mantle deposits (LDMD) of pyroclastic origin and at least two compositional groups are present. The Galileo spacecraft obtained very high-resolution remote sensing data for the northeastern part of the nearside of the Moon. In order to prepare for and support this encounter, we have collected and analyzed a variety of spectral data for the NEN region. Numerous unanswered questions exist for this region. These include: (1) the composition and stratigraphy of the local highlands crust, (2) the nature and mode of formation of regional light plains, (3) the composition of localized pyroclastic deposits, and (4) the distribution of possible cryptomare in the region. The purpose of this paper is to present the preliminary results of our analyzes of remote sensing data of remote sensing data obtained for the NEN region.

Hawke, B. R.↗

Factors affecting the identification of phytoplankton groups by means of remote sensing

A literature review was conducted on the state of the art as to whether or not information about communities and populations of phytoplankton in aquatic environments can be derived by remote sensing. In order to arrive at this goal, the spectral characteristics of various types of phytoplankton were compared to determine first, whether there are characteristic differences in pigmentation among the types and second, whether such differences can be detected remotely. In addition to the literature review, an extensive, but not exhaustive, annotated bibliography of the literature that bears on these questions is included as an appendix, since it constitutes a convenient resource for anyone wishing an overview of the field of ocean color. The review found some progress has already been made in remote sensing of assemblages such as coccolithophorid blooms, mats of cyanobacteria, and red tides. Much more information about the composition of algal groups is potentially available by remote sensing particularly in water bodies having higher phytoplankton concentrations, but it will be necessary to develop the remote sensing techniques required for working in so-called Case 2 waters. It is also clear that none of the satellite sensors presently available or soon to be launched is ideal from the point of view of what we might wish to know; it would seem wise to pursue instruments with the planned characteristics of the Moderate Resolution Imaging Spectrometer-Tilt (MODIS-T) or Medium Resolution Imaging Spectrometer (MERIS).

Weaver, Ellen C.↗

Sensing the gas metal arc welding process

Control of gas metal arc welding (GMAW) requires real-time sensing of the process. Three sensing techniques for GMAW are being developed at the Idaho National Engineering Laboratory (INEL). These are (1) noncontacting ultrasonic sensing using a laser/EMAT (electromagnetic acoustic transducer) to detect defects in the solidified weld on a pass-by-pass basis, (2) integrated optical sensing using a CCD camera and a laser stripe to obtain cooling rate and weld bead geometry information, and (3) monitoring fluctuations in digitized welding voltage data to detect the mode of metal droplet transfer and assure that the desired mass input is achieved.

Carlson, N. M.↗

Remote sensing and the Mississippi high accuracy reference network

Since 1986, NASA's Commercial Remote Sensing Program (CRSP) at Stennis Space Center has supported commercial remote sensing partnerships with industry. CRSP's mission is to maximize U.S. market exploitation of remote sensing and related space-based technologies and to develop advanced technical solutions for spatial information requirements. Observation, geolocation, and communications technologies are converging and their integration is critical to realize the economic potential for spatial informational needs. Global positioning system (GPS) technology enables a virtual revolution in geopositionally accurate remote sensing of the earth. A majority of states are creating GPS-based reference networks, or high accuracy reference networks (HARN). A HARN can be defined for a variety of local applications and tied to aerial or satellite observations to provide an important contribution to geographic information systems (GIS). This paper details CRSP's experience in the design and implementation of a HARN in Mississippi and the design and support of future applications of integrated earth observations, geolocation, and communications technology.

Mick, Mark↗

Direct and indirect methods for correcting the aerosol effect on remote sensing

Aspects of aerosol studies and remote sensing are reviewed. Aerosol scatters solar radiation before it reaches the surface and scatters and absorbs it again after it is reflected from the surface and before it reaches the satellite sensor. The effect is spectrally and spatially dependent. Therefore atmospheric aerosol (dust, smoke and air pollution particles) has a significant effect on remote sensing. Correction for the aerosol effect was never achieved on an operational basis though several case studies were demonstrated. Correction can be done in a direct way by deriving the aerosol loading from the image itself and correcting for it using the appropriate radiative transfer model or by an indirect way, by defining remote sensing functions that are less dependent on the aerosol loading. To some degree this was already achieved in global remote sensing of vegetation where a composite of several days of NDVI (Normalized Difference Vegetation Index) measurements, choosing the maximal value, was used instead of a single cloud screened value. The Atmospheric Resistant Vegetation Index (ARVI) introduced recently for the NASA Earth Observing System EOS-MODIS is the most appropriate example of indirect correction, where the index is defined in such a way that the atmospheric effect in the blue spectral channel cancels to a large degree the atmospheric in the red channel in computations of a vegetation index. Atmospheric corrections can also use aerosol climatology and ground based instrumentation.

Kaufman, Yoram J.↗

Recalibration of the Viyager PRA antenna for polarization sense measurement

The Voyager Planetary Radio Astronomy (PRA) antenna and receiver system provides an indication of the sense of elliptical or circular polarization of radiation that is not correct for all directions of incidence. The true sense could be determined for all directions if accurate calibration data were available. It was not feasible to make the calibration before the Voyagers were launched. Lecacheux & Ortega-Molina (1987), however, were able to derive such calibration data from planetary radio observations made in flight. They expressed their results in terms of the tilt of a plane (the E-plane) that divides the incident ray directions for which the indicated polarization sense is correct from those directions for which the indicated sense is reversed. We demonstrate that there are certain directions for which this calibration is itself in error, and that the surface dividing the two sets of incident rays is more complex than a tilted plane. We are able to make a crude approximation to the true surface from the limited data available.

Wang, L.↗

Effect of radiance-to-reflectance transformation and atmosphere removal on maximum likelihood classification accuracy of high-dimensional remote sensing data

Many analysis algorithms for high-dimensional remote sensing data require that the remotely sensed radiance spectra be transformed to approximate reflectance to allow comparison with a library of laboratory reflectance spectra. In maximum likelihood classification, however, the remotely sensed spectra are compared to training samples, thus a transformation to reflectance may or may not be helpful. The effect of several radiance-to-reflectance transformations on maximum likelihood classification accuracy is investigated in this paper. We show that the empirical line approach, LOWTRAN7, flat-field correction, single spectrum method, and internal average reflectance are all non-singular affine transformations, and that non-singular affine transformations have no effect on discriminant analysis feature extraction and maximum likelihood classification accuracy. (An affine transformation is a linear transformation with an optional offset.) Since the Atmosphere Removal Program (ATREM) and the log residue method are not affine transformations, experiments with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data were conducted to determine the effect of these transformations on maximum likelihood classification accuracy. The average classification accuracy of the data transformed by ATREM and the log residue method was slightly less than the accuracy of the original radiance data. Since the radiance-to-reflectance transformations allow direct comparison of remotely sensed spectra with laboratory reflectance spectra, they can be quite useful in labeling the training samples required by maximum likelihood classification, but these transformations have only a slight effect or no effect at all on discriminant analysis and maximum likelihood classification accuracy.

Hoffbeck, Joseph P.↗

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Tsang, Leung↗

Flood Management Enhancement Using Remotely Sensed Data

SENTAR, Inc., entered into a cooperative agreement with NASA Goddard Space Flight Center (GSFC) in December 1994. The intent of the NASA Cooperative Agreement was to stimulate broad public use, via the Internet, of the very large remote sensing databases maintained by NASA and other agencies, thus stimulating U.S. economic growth, improving the quality of life, and contributing to the implementation of a National Information Infrastructure. SENTAR headed a team of collaborating organizations in meeting the goals of this project. SENTAR's teammates were the NASA Marshall Space Flight Center (MSFC) Global Hydrology and Climate Center (GHCC), the U.S. Army Space and Strategic Defense Command (USASSDC), and the Alabama Emergency Management Agency (EMA). For this cooperative agreement, SENTAR and its teammates accessed remotely sensed data in the Distributed Active Archive Centers, and other available sources, for use in enhancing the present capabilities for flood disaster management by the Alabama EMA. The project developed a prototype software system for addressing prediction, warning, and damage assessment for floods, though it currently focuses on assessment. The objectives of the prototype system were to demonstrate the added value of remote sensing data for emergency management operations during floods and the ability of the Internet to provide the primary communications medium for the system. To help achieve these objectives, SENTAR developed an integrated interface for the emergency operations staff to simplify acquiring and manipulating source data and data products for use in generating new data products. The prototype system establishes a systems infrastructure designed to expand to include future flood-related data and models or to include other disasters with their associated remote sensing data requirements and distributed data sources. This report covers the specific work performed during the seventh, and final, milestone period of the project, which began on 1 October 1996 and ended on 31 January 1997. In addition, it provides a summary of the entire project.

Romanowski, Gregory J.↗

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation composition was noted in the change detection image.

Hogan, Christine A.↗