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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS1949

Transient Behavior of Lumped-Constant Systems for Sensing Gas Pressures

The development of theoretical equations describing the behavior of a lumped-constant pressure-sensing system under transient operation Is presented with experimental data that show agreement with the equations. A pressure-sensing system 'consisting of a tube terminating in a reservoir is investigated for the transient relation between a presSure disturbance at the open end of the tube and the pressure response in the reservoir. Design parameters are presented that can be adjusted to achieve a desired performance fran such a system when the system is considered as a transfer member of a control loop.

INSTRUMENTS - PRESSURE↗
NASA NTRS1991

Applications of ecological concepts and remote sensing technologies in archaeological site reconnaissance

The concept of integrating ecological perspectives on early man's settlement patterns with advanced remote sensing technologies shows promise for predictive site modeling. Early work with aerial imagery and ecosystem analysis is discussed with respect to the development of a major project in Maya archaeology supported by NASA and the National Geographic Society with technical support from the Mississippi State Remote Sensing Center. A preliminary site reconnaissance model will be developed for testing during the 1991 field season.

Miller, W. Frank↗
NASA NTRS1993

A review and analysis of neural networks for classification of remotely sensed multispectral imagery

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

Paola, Justin D.↗
NASA NTRS1993

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Musick, H. Brad↗
NASA NTRS1993

Recent advances in radar remote sensing of forest

On a global scale, forests represent most of the terrestrial standing biomass (80 to 90 percent). Thus, natural and anthropogenic change in forest covers can have major impacts not only on local ecosystems but also on global hydrologic, climatic, and biogeochemical cycles that involve exchange of energy, water, carbon, and other elements between the earth and atmosphere. Quantitative information on the state and dynamics of forest ecosystems and their interactions with the global cycles appear necessary to understand how the earth works as a natural system. The information required includes the lateral and vertical distribution of forest cover, the estimates of standing biomass (woody and foliar volume), the phenological and environmental variations and disturbances (clearcutting, fires, flood), and the longer term variations following deforestation (regeneration, successional stages). To this end, seasonal, annual, and decadal information is necessary in order to separate the long term effects in the global ecosystem from short term seasonal and interannual variations. Optical remote sensing has been used until now to study the forest cover at local, regional, and global scales. Radar remote sensing, which provides recent SAR data from space on a regular basis, represents an unique means of consistently monitoring different time scales, at all latitudes and in any atmospheric conditions. Also, SAR data have shown the potential to detect several forest parameters that cannot be inferred from optical data. The differences--and complementarity--lie in the penetration capabilities of SAR data and their sensitivity to dielectric and geometric properties of the canopy volume, whereas optical data are sensitive to the chemical composition of the external foliar layer of the vegetation canopy.

Letoan, Thuy↗
NASA NTRS1993

A summary of microwave remote sensing investigations planned for BOREAS

The Boreal Ecosystem - Atmosphere Study (BOREAS) is a multidisciplinary field and remote sensing study that will be implemented jointly by the United States and Canada. The goal of BOREAS is to obtain an improved understanding of the interactions between the boreal forest biome and the atmosphere in order to clarify their roles in global change. Specific objectives are to improve the understanding of the processes that govern the exchanges of water, energy, heat, carbon, and trace gases between boreal ecosystems and the atmosphere, and to develop and validate remote sensing algorithms for transferring the understanding of these processes from local to regional scales. Two principal field sites, both within Canada, were selected. The northern site is located near Thompson, Manitoba, and the southern site encompasses Prince Albert National Park in Saskatchewan. The growing season in the northern site tends to be limited by growing-degree days while the southern site is limited by soil moisture and fire frequency. Most of the field work will occur at these two sites during 1993 and 1994 as part of six field campaigns. The first of these campaigns is scheduled for August 1993 and will involve instrument installation and an operational shakedown. Three large scale Intensive Field Campaigns (IFC's) are scheduled for 1994, along with two smaller scale Focused Field Campaigns (FFC's). The first 1994 campaign will be an FFC designed to capture the biome under completely frozen conditions during the winter. The second FFC and the first IFC are scheduled to capture the spring thaw period. Another IFC will take place in the summer during a period of maximum water stress. Finally, the third FFC will be scheduled to capture the collapse into senescence during the fall.

Mcdonald, Kyle C.↗
NASA NTRS1993

Advances in spaceborne radar remote sensing

Radar sensors are being more commonly used for spaceborne sensing of Earth and Planetary surfaces and atmosphere. This is a result of advances in: better understanding wave/natural surface interaction mechanisms, measurement techniques, hardware development and data handling/visualization. A number of spaceborne radar systems are presently operational or will be launched in the next few years. In addition airborne instruments utilizing multispectral, polarmetric and interferometric capabilities are opening new vistas which will lead to major advances in radar sensing by the end of the decade. This paper is a review of recent developments and expected future advances.

Elachi, C.↗
NASA NTRS1993

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

Wang, L.↗
NASA NTRS1994

Electrostatically suspended and sensed micro-mechanical rate gyroscope

The goal of this work is development of fully electrostatically suspended and rebalancing angular rate sensing micro-gyroscope fabricated according to standard VLSI techniques. Fabrication of test structures is proceeding. Off chip electronics for the electrostatic sensing and driving circuits has been tested. The prototype device will be assembled in a hybrid construction including the FET input stages of the sensors.

Torti, R.↗
NASA NTRS1994

Observations in the solar spectrum interest for remote sensing purposes

The polarization of the sunlight scattered by atmospheric aerosols or cloud droplets and reflected from ground surfaces or plant canopies may convey much information when used for remote sensing purposes. The typical polarization features of aerosols, cloud droplets, and plant canopies, as observed by ground based and airborne sensors, are investigated, looking especially for those invariant properties amenable to description by simple models when possible. The question of polarization measurements from space is addressed. The interest of such measurements for remote sensing purposes is investigated, and their feasibility is tested by using results obtained during field campaigns of the airborne POLDER instrument, a radiometer designed to measure the directionality and polarization of the sunlight scattered by the ground atmosphere system.

Herman, M.↗
NASA NTRS1994

Remote sensing of forest ecosystem dynamics: Measurements and modeling

The development of an integrated approach to the modeling of forest dynamics encompassing submodels of forest growth and succession, soil processes and radiation interactions, is reported. Remote sensing technology is a key element of this study in that it provides data for developing, initializing, updating, and validating the models. The objectives are reviewed, the data collected and models in use are discussed, and a framework for studying interactions between the forest growth, soil process and energy interaction components, is described. Remote sensing technology used in the study includes optical and microwave field, aircraft and satellite borne instruments. The types of data collected during intensive field and aircraft campaigns included bidirectional reflectance, thermal emittance and multifrequency, multipolarization synthetic aperture radar backscatter. Synthetic imagery of derived products such as forest biomass and NDVI (Normalized Difference Vegetative Index), and collections of ground data are being assembled in a georeferenced data base. These data are used to drive or test multidiscipline simulations of forested ecosystems. Enhancements to the modeling environment permit considerable flexibility in configuring simulations and selecting results for reporting and graphical display.

Williams, Darrel L.↗
NASA NTRS1994

SEQ-POINTER: Next generation, planetary spacecraft remote sensing science observation design tool

Since Mariner, NASA-JPL planetary missions have been supported by ground software to plan and design remote sensing science observations. The software used by the science and sequence designers to plan and design observations has evolved with mission and technological advances. The original program, PEGASIS (Mariners 4, 6, and 7), was re-engineered as POGASIS (Mariner 9, Viking, and Mariner 10), and again later as POINTER (Voyager and Galileo). Each of these programs were developed under technological, political, and fiscal constraints which limited their adaptability to other missions and spacecraft designs. Implementation of a multi-mission tool, SEQ POINTER, under the auspices of the JPL Multimission Operations Systems Office (MOSO) is in progress. This version has been designed to address the limitations experienced on previous versions as they were being adapted to a new mission and spacecraft. The tool has been modularly designed with subroutine interface structures to support interchangeable celestial body and spacecraft definition models. The computational and graphics modules have also been designed to interface with data collected from previous spacecraft, or on-going observations, which describe the surface of each target body. These enhancements make SEQ POINTER a candidate for low-cost mission usage, when a remote sensing science observation design capability is required. The current and planned capabilities of the tool will be discussed. The presentation will also include a 5-10 minute video presentation demonstrating the capabilities of a proto-Cassini Project version that was adapted to test the tool. The work described in this abstract was performed by the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

Boyer, Jeffrey S.↗
NASA NTRS1994

Nondestructive time-of-capture, location and velocity sensing in intact capture

Velocity sensing of hypervelocity particles was a significant field of interest from the 1960s to 1970s. Generically, velocity sensing has been approached by either of two methods: first, detecting direct plasma or light emissions onto a solid surface, or second, performing time-of-flight by film penetration, or by detecting charged particles passing a static electric field. Impact plasma techniques required the destruction of the particles. Multiple-film penetrations were also destructive, especially for small particles. There is a need for an integrated, reliable, and simple location and velocity sensor compatible to our intact capture underdense medium without contributing additional damage to the captured particle. Since cometary dust, like cosmic dust, is essentially randomly distributed, knowing the time of the dust capture and the location of the capture on the collector permits the identification of the specific dust particle captured. Velocity information helps to determine the trajectory of the dust particle. Our discovery of a very suitable acoustic sensor and fruitful experimental results have led to the realization of a flight velocity sensor with intact capture underdense media.

Tsou, Peter↗
NASA NTRS1995

Remote-sensing based technique to account for sub-grid scale variability of land surface properties

A method has been presented for the representation of sub-grid scale variability of surface properties within a land surface processes model. The method uses remotely-sensed data to directly or indirectly estimate probability density functions (PDF's) or key surface variables. Application of this technique in a coupled land surface-atmosphere model requires only grid-scale values of the variables of interest, obtained from low-resolution satellite imagery or surface/remote sensing data assimilation. The PDF's of each controlling surface property are superimposed on the respective grid-scale values to simulate sub-grid scale heterogeneity. Sensitivity studies will be carried out to ascertain the relative importance of the heterogeneity of several variables, and the degree to which non-linear property-process interactions impact large-scale fluxes.

Crosson, William L.↗
NASA NTRS1993

A role for AVIRIS in the Landsat and Advanced Land Remote Sensing Systems program

As a calibrated imaging spectrometer flying at a 20 km altitude, AVIRIS may contribute to the Landsat and the Advanced Land Remote Sensing System efforts. These contributions come in the areas of: (1) on-orbit calibration, (2) specification of new spectral bands, (3) validation of algorithms, and (4) investigation of an imaging spectrometer of the Advanced Land Remote Sensing System.

Green, Robert O.↗
NASA NTRS1994

Remote Sensing of Earth's Surface and Atmosphere: Interdisciplinary Scientific Commission A of the COSPAR Plenary Meeting, 29th, Washington, DC, 28 Aug. - 5 Sep., 1992

This conference reviewed the recent developments in remote monitoring of surface temperatures, which will be significant in future global change studies. Various techniques to derive surface temperature from existing and future remote sensing systems such as earth observing system (EOS) are discussed. Five sessions were held: (1) The nature of the problem of remote sensing of surface temperatures; (2) Surface temperature measurements from current satellites; (3) Modeling and surface observations of various techniques to measure temperature and/or emissivity, modeling of vegetation; (4) The effects of variable spectral emissivity from the determination of surface kinetic temperature using multispectral thermal infrared measurements; and (5) Future satellite systems including EOS/ASTER, EOS/MODIS-N, and EOS/AIRS.

Kahle, A. B.↗
NASA NTRS1995

Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensing

The advent of remote sensing, the develpmemt of new optical instrumentation, and the associated advances in hydrological optics have transformed oceanography; it is now feasible to describe ocean-scale biogeochemical dynamcis from satellite observations, verified and complemented by measurements from optical sensors on profilers, moorings, and drifters. Only near-surface observations are common to both remote sensing and in situ observation, so it is critical to understand processes in the upper euphotic zone. Unfortunately, the biological principles that must be used to interpret optical variability near the sea surface are weaker than we would like, because relatively few experiments and analyses have examined bio-optical relationships under high irradiance characteristic of the upper optical depth. Special consideration of this stratum is justified, because there is good evidence that bio-optical relationships are altered near the surface; (1) the fluorescence yield from chlorophyll declines, leading to bias in the estimation of pigment from fluorometry; (2) the modeled relationship between solar-stimulated fluorecence and photosynthesis seems to deviate significantly from that presented for the lower euphotic zone; and (3) carbon-specific and cellular attenuation cross sections of phytoplankton change substantially during exposures to bright light. Even the measurement of primary productivity is problematic near the sea surface, because vertical mixing is not simulated and artifactual inhibition of photosynthesis can result. These problems can be addressed by focusing more sampling effort, experimental simulation, and analytical consideration on the upper optical depth, and by shortening timescales for the measurement of marine photosynthesis. Special efforts to study near-surface processes are justified, because new bio-optical algorithms will require quantitaitve descriptions of the responses of phytoplankton to bright light.

Cullen, John J.↗
NASA NTRS1995

Content-based retrieval of remote sensed images using a feature-based approach

A feature-based representation model for content-based retrieval from a remote sensed image database is described in this work. The representation is formed by clustering spatially local pixels, and the cluster features are used to process several types of queries which are expected to occur frequently in the context of remote sensed image retrieval. Preliminary experimental results show that the feature-based representation provides a very promising tool for content-based access.

Vellaikal, Asha↗