The use of LANDSAT digital data and computer implemented techniques for an erosion hazard-reforestation needs assessment
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Anderson, J. E.↗
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A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1
An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.
Ingels, F. M.↗
A comparison between GOES-1 IR digital data and radar data for the 4 April 1977 severe storms outbreak
The 4 April 1977 severe storms outbreak over Georgia and Alabama provided an excellent opportunity to examine the complementary characteristics between satellite and radar data.
Peslen, C. A.↗
Digital data reformatter/deserializer
A method and apparatus is presented for reformatting and de-serializing a serially-received sequence of data words, each consisting of a fixed number of binary data bits. A block of nm bits is serially fed into a shift register or serially-connected group of shift registers. In lieu of the(nm-1)th shifts, the bits are rearranged within the shift register in parallel fashion, according to a prescribed scheme. Shifting then continues, until the first bit of each data word appears in the last bit position in the shift register, at which time that data word is shifted in parallel into an output buffer stage, from which it is outputted in parallel, after a fixed delay.
Engel, A.↗
Development of a tree classifier for discrimination of surface mine activity from Landsat digital data
In a cooperative project with the Geological Survey of Alabama, the Mississippi State Remote Sensing Applications Program has developed a single purpose, decision-tree classifier using band-ratioing techniques to discriminate various stages of surface mining activity. The tree classifier has four levels and employs only two channels in classification at each level. An accurate computation of the amount of disturbed land resulting from the mining activity can be made as a product of the classification output. The utilization of Landsat data provides a cost-efficient, rapid, and accurate means of monitoring surface mining activities.
Solomon, J. L.↗
Interpretation of LANDSAT digital data using a cubic color model based on relative energies
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Cate, R. B.↗
Identification of lateral spectral contrasts in the lower Hudson River Estuary using Landsat digital data
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Birnie, R. W.↗
Water quality mapping from Landsat digital data
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Khorram, S.↗
Detection of variations in aspen forest habitat from LANDSAT digital data: Bear River Range, Utah
The aspen forests of the Bear River Range were analyzed and mapped using data recorded on July 2, 1979 by the LANDSAT III satellite; study efforts yielded sixty-seven light signatures for the study area, of which three groups were identified as aspen and mapped at a scale of 1:24,000. Analysis and verification of the three groups were accomplished by random location of twenty-six field study plots within the LANDSAT-defined aspen areas. All study plots are included within the Cache portion of the Wasatch-Cache National Forest. The following selected site characteristics were recorded for each study plot: a list of understory species present; average percent cover density for understory species; aspen canopy cover estimates and stem measurements; and general site topographic characteristics. The study plot data were then analyzed with respect to corresponding Landsat spectral signatures. Field studies show that all twenty-six study plots are associated with one of the three aspen groups. Further study efforts concentration on characterizing the differences between the site characteristics of plots falling into each of the three aspen groups.
Merola, J. A.↗
Infrared digital data analysis of severe storms and hurricanes from geosynchronous satellite
A severe storm in Louisiana on March 24, 1976 is considered, taking into account gravity wave observations made with the aid of a Doppler sounder array and remote sensing studies of the cloud top. Attention is also given to the Hurricane Frederic on September 12, 1979. A study which takes into account the observations regarding the gravity waves and the satellite observations of clouds associated with Hurricane Frederic shows that gravity waves were excited by overshooting turrets above the tropopause. The altitude of the turrets above the tropopause is an indication for the intensity of a cyclone, while the change in cloud top height provides an indication related to the amplification of hurricane intensity.
Hung, R. J.↗
The use of large-scale aerial photography for interpreting Landsat digital data in an elk habitat-analysis project
Large-scale aerial photography was used to interpret Landsat multispectral scanner data processed through an unsupervised classifier. After scale adjustment and interpretation by application of an elk-habitat photointerpretation legend, the photographs were registered with the spectral classification, and the co-occurrence of spectral picture elements with photointerpreted habitat classes was tabulated. Analysis of the resulting table of data permitted the description of spectral classes in terms meaningful and useful to elk research and management unit in the Blue Mountains of northeastern Oregon.
Isaacson, D. L.↗
Estimating total standing herbaceous biomass production with LANDSAT MSS digital data
Rangeland biomass data were correlated with spectral vegetation indices, derived from LANDSAT MSS data. LANDSAT data from five range and three other land use sites in Willacv and Cameron Counties were collected on October 17 and December 10, 1975, and on July 31 and September 23, 1976. The overall linear correlation of total standing herbaceous biomass with the LANDSAT derived perpendicular vegetation index was highly significant (r = 0.90**) for these four dates. The standard error of estimate was 722 kg/ha. Biomass data were recorded for two of these range sites for 8 months (March through October) during the 1976 growing season. Standing green biomass accounted for most of the increase in herbage, starting in June and ending about September and October. These results indicate that satellite data may be useful for the estimation of total standing herbaceous biomass production that could aid range managers in assessing range condition and animal carrying capacities of large and inaccessible range holdings.
Richardson, A. J.↗
Computer implemented land cover classification using LANDSAT MSS digital data: A cooperative research project between the National Park Service and NASA. 3: Vegetation and other land cover analysis of Shenandoah National Park
Four LANDSAT frames, each corresponding to one of the four seasons were spectrally classified and processed using NASA-developed computer programs. One data set was selected or two or more data sets were marged to improve surface cover classifications. Selected areas representing each spectral class were chosen and transferred to USGS 1:62,500 topographic maps for field use. Ground truth data were gathered to verify the accuracy of the classifications. Acreages were computed for each of the land cover types. The application of elevational data to seasonal LANDSAT frames resulted in the separation of high elevation meadows (both with and without recently emergent perennial vegetation) as well as areas in oak forests which have an evergreen understory as opposed to other areas which do not.
Cibula, W. G.↗
Experimental philosophy leading to a small scale digital data base of the conterminous United States for designing experiments with remotely sensed data
Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.
Labovitz, M. L.↗
Error control for reliable digital data transmission and storage systems
A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. In LSI and VLSI technology, memories are often organized on a multiple bit (or byte) per chip basis. For example, some 256K-bit DRAM's are organized in 32Kx8 bit-bytes. Byte oriented codes such as Reed Solomon (RS) codes can provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. In this paper we present some special decoding techniques for extended single-and-double-error-correcting RS codes which are capable of high speed operation. These techniques are designed to find the error locations and the error values directly from the syndrome without having to use the iterative alorithm to find the error locator polynomial. Two codes are considered: (1) a d sub min = 4 single-byte-error-correcting (SBEC), double-byte-error-detecting (DBED) RS code; and (2) a d sub min = 6 double-byte-error-correcting (DBEC), triple-byte-error-detecting (TBED) RS code.
Costello, D. J., Jr.↗
Processing circuit with asymmetry corrector and convolutional encoder for digital data
A processing circuit is provided for correcting for input parameter variations, such as data and clock signal symmetry, phase offset and jitter, noise and signal amplitude, in incoming data signals. An asymmetry corrector circuit performs the correcting function and furnishes the corrected data signals to a convolutional encoder circuit. The corrector circuit further forms a regenerated clock signal from clock pulses in the incoming data signals and another clock signal at a multiple of the incoming clock signal. These clock signals are furnished to the encoder circuit so that encoded data may be furnished to a modulator at a high data rate for transmission.
Pfiffner, Harold J.↗
A gridding approach to detect patterns of change in coastal wetlands from digital data
The conversion of land to water or water to land in the Grand Bayou wetlands area from 1972 to 1981 is evaluated on the basis of Landsat MSS band 2 and 4 images. A postclassification (land vs water) procedure is employed, and grids 1, 5, 10, 25, and 50 pixels square are superimposed on the classified data in an effort to reduce the effects of poor georegistration of the images (simulated by shifting one set of grids two pixels vertically and horizontally). The results are presented in tables, maps, and sample images and characterized in detail. Grids 5 or 10 pixels square are found to give percentage land/water change values and locations similar to those obtained in pixel-by-pixel analysis of nearly perfectly matched images.
Pelletier, R. E.↗
An automated digital data collection and analysis system for the Charpy Impact Tester
The standard Charpy Impact Tester has been modified by the addition of a system of hardware and software to improve the accuracy and consistency of measurements made during specimen fracturing experiments. An optical disc, light source, and detector generate signals that indicate the pendulum position as a function of time. These signals are used by a computer to calculate the velocity and kinetic energy of the pendulum as a function of its position.
Kohne, Glenn S.↗