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Dobson, C.

Publications and source records attributed to Dobson, C..

11 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Utilizing Fission Technology to Enable Rapid and Affordable Access to any Point in the Solar System

Fission technology can enable rapid, affordable access to any point in the solar system. Potential fission-based transportation options include bimodal nuclear thermal rockets, high specific energy propulsion systems, and pulsed fission propulsion systems. In-space propellant re-supply enhances the effective performance of all systems, but requires significant infrastructure development. Safe, timely, affordable utilization of first-generation space fission propulsion systems will enable the development of more advanced systems. First generation systems can build on over 45 years of US and international space fission system technology development to minimize cost.

Houts, Mike↗
NASA NTRS1993

The Extreme Ultraviolet Explorer archive

The objectives and data products of the EUVE public archive, created to handle the storage, maintenance, and distribution of EUVE data and ancillary documentation, information, and software, are briefly reviewed. Archive data products presently include calibration target spectra, a catalog of past and future calibration targets, the EUVE Bright Source List, extreme ultraviolet skymaps and images of extended sources, a list of approved guest observer targets, a bibliography of EUVE publications, and C routines to calculate interstellar medium transmission at EUV wavelengths.

Polomski, E.↗
NASA NTRS1992

Data indexing techniques for the EUVE all-sky survey

This poster describes techniques developed for manipulating large full-sky data sets for the Extreme Ultraviolet Explorer project. The authors have adapted the quatrilateralized cubic sphere indexing algorithm to allow us to efficiently store and process several types of large data sets, such as full-sky maps of photon counts, exposure time, and count rates. A variation of this scheme is used to index sparser data such as individual photon events and viewing times for selected areas of the sky, which are eventually used to create EUVE source catalogs.

Lewis, J.↗
NASA NTRS1987

Synergism requirements and concepts for SAR and HIRIS on EOS

A study is conducted to ascertain the synergistic advantages obtainable by combining, in the EOS orbital instrument platform, instruments for the optical and microwave measurements of biophysical properties important in ecosystem modeling. Attention is given to the comparative coverages of the SAR, HIRIS, TIMS and MODIS instruments that will be carried by the platform, and to the ongoing development of joint inversion algorithms for the modeling of the ecosystems-related data thus obtained. A three-dimensional characterization of the physical attributes of the vegetation canopy and its background surface will be attempted.

Cimino, J. B.↗
NASA NTRS1987

The global forest ecosystem as viewed by ERS-1, SIR-C and EOS

A program is presented to perform coordinated global experiments designed to use the unique features of synthetic aperture radar (SAR) sensors such as the ones on ERS-1, SIR-C and EOS to characterize the physical nature of forest stands as input to global ecosystem and climatology models. Details about the objectives, program and expected results are presented.

Sieber, A. J.↗
NASA NTRS1983

Identification of corn fields using multidate radar data

Airborne C- and L-band radar data acquired over a test site in western kansas were analyzed to determine corn-field identification accuracies obtainable using single-channel, multichannel, and multidate radar data. An automated pattern-recognition procedure was used to classify 144 fields into three categories: corn, pasture land, and bare soil (including wheat stubble and fallow). Corn fields were identified with accuracies ranging from 85 percent for single channel, single-date data to 100 percent for single-channel, multidate data. The effects of radar parameters such as frequency, polarization, and look angle as well as the effects of soil moisture on the classification accuracy are also presented.

Shanmugan, K. S.↗
NASA NTRS1983

Improved spatial mapping of rainfall events with spaceborne SAR imagery

The Seasat satellite acquired the first spaceborne synthetic-aperture radar (SAR) images of the earth's surface, in 1978, at a frequency of 1.275 GHz (L-band) in a like-polarization mode at incidence angles of 23 + or - 3 deg. Although this may not be the optimum system configuration for radar remote sensing of soil moisture, interpretation of two Seasat images of Iowa demonstrates the sensitivity of microwave backscatter to soil moisture content. In both scenes, increased image brightness, which represents more radar backscatter, can be related to previous rainfall activity in the two areas. Comparison of these images with ground-based rainfall observations illustrates the increased spatial coverage of the rainfall event that can be obtained from the satellite SAR data. These data can then be color-enhanced by a digital computer to produce aesthetically pleasing output products for the user community.

Ulaby, F. T.↗
NASA NTRS1981

Crop classification using multidate/multifrequency radar data

Both C- and L-band radar data acquired over a test site near Colby, Kansas during the summer of 1978 were used to identify three types of vegetation cover and bare soil. The effects of frequency, polarization, and the look angle on the overall accuracy of recognizing the four types of ground cover were analyzed. In addition, multidate data were used to study the improvement in recognition accuracy possible with the addition of temporal information. The soil moisture conditions had changed considerably during the temporal sequence of the data; hence, the effects of soil moisture on the ability to discriminate between cover types were also analyzed. The results provide useful information needed for selecting the parameters of a radar system for monitoring crops.

Ulaby, F. T.↗
NASA NTRS1981

Within-field variability of plant and soil parameters

The variability of ground truth data collected for vegetation experiments was investigated. Two fields of wheat and one field of corn were sampled on two different dates. The variability of crop and soil parameters within a field, between two fields of the same type, and within a field over time were compared statistically. The number of samples from each test site required in order to be able to determine with confidence the mean and standard deviations for a given variable was determined. Eight samples were found to be adequate for plant height determinations, while twenty samples were required for plant moisture and soil moisture characterization. Eighteen samples were necessary for detecting within field variability over time and for between field variability for the same crop. The necessary sample sites vary according to the physiological growth stage of the crop and recent weather events that affect the moisture and/or height characteristics of the field in question.

Ulaby, F. T.↗
NASA NTRS1981

Resolution requirements for a soil moisture imaging radar

Image simulation techniques were employed to establish the relationship between spatial resolution and the accuracy of soil moisture estimated by an imaging radar. A spaceborne synthetic aperture radar at an orbital altitude of 600 km, operating at 4.5 GHz with HH polarization configuration and covering a ground swath width of 143 km corresponding to an angle of incidence range extending between 7-22 degrees relative to the vertical, provided the images simulated by a 17.7 km x 19.3 km test site. The role of resolution was evaluated by simulating various sets of images with resolutions ranging from 20 m x 20 m to 1 km x 1 km. Each simulated image was subjected to a soil moisture prediction algorithm whose input is limited to the image intensity level. Results show that the 1 km x 1 km resolution provides the best prediction accuracy for most soil moisture distributions except for drought-like conditions for which the 100 m x 100 m resolution is found to be preferred. In general it was found that the soil moisture of about 90% of the pixels is predicted with an error of + or - 20% of field capacity or less.

Dobson, C.↗