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The author has identified the following significant results. There is strong indication that spatially rare feature classes may be missed in clustering classifications based on 2% random sampling. Therefore, it seems advisable to augment random sampling for cluster analysis with directed sampling of any spatially rare features which are relevant to the analysis.
Twenty highland samples from Apollo 14, 15, and 17 and the eucrites Juvinas and Morre County were analyzed by radiochemical neutron activation for Ag, Au, Bi, Br, Cd, Cs, Ge, In, Ir, Ni, Os, Pd, Rb, Re, Sb, Se, Te, Tl, U, and Zn. The meteoritic components of 82 highland rocks were recalculated with the new corrections for the indigenous contribution and were classified by discriminant and cluster analysis as well as ternary diagrams, using Ir, Re, Au and Ni as diagnostic elements. To characterize these groups more fully, average abundances of meteoritic volatiles (Sb, Ge, Ag, Se, Te, and Bi) were calculated from regressions against Ir.
Size can be used as a criterion to select 18 large (larger than 1 cm) samples from among 148 melt-rock fragments of all sizes. This selection provides a suite of large samples which represent the important chemical variants among highland melt rocks; each large sample has enough material for a number of sample-destructive studies, as well as for future reference. Cluster analysis of the total data base of 148 highland melt rocks shows six distinct groups: anorthosite, gabbroic anorthosite, anorthositic gabbro ('highland basalt'), low K Fra Mauro, intermediate-K Fra Mauro, and high-K. Large samples are available for four of the melt-rock groups (gabbroic anorthosite, anorthositic gabbro, low-K Fra Mauro, and intermediate-K Fra Mauro). This sample selection reveals two subgroups of anorthositic gabbro (one anorthite-poor with negative Eu anomaly and one anorthite-rich without Eu anomaly). There is a sharp distinction between those Apollo 16 melt rocks and glasses which have both been classified as 'gabbroic anorthosite'.
A silicon imaging photometer system (SIPS) was used to obtain visible and near-infrared spectral imaging data in four narrow bandpasses (0.38, 0.56, 0.85, and 1.05 microns) for a 400-by-400-km lunar region which includes the Serenitatis-Tranquillitatis border. Three ratio frames were used to make color composites of radio images, and spectral maps based on interactive 'cluster' analysis were produced from four video channels. A low albedo titanium-poor unit occurs near the southern edge of the Serenitatis and south of the basin; this unit appears to postdate the high-titanium dark Tranquillitatis and 'blue-ring' material and may be associated with an Al/Si anomaly noticed in Apollo orbital X-ray data.
The region in the vicinity of the Luna 24 handling site (40-70 deg E; 0-20 deg N) is studied by means of the Apollo orbital fluorescent X-ray Al/Si and Mg/Al data and earth-based normal albedo measurements. By means of unsupervised non-parametric cluster analysis this region is divided into eight surface units. One of these units centered in the Proclus region deviates from the usual trend of increasing normal albedo with increasing Al/Si values and decreasing Mg/Al values
An initial application of multispectral LIDAR data from the NASA airborne oceanographic lidar (AOL) to the mapping of watermass boundaries is presented. The approach uses the multispectral lidar data from the fluorosensing mode in a cluster analysis to define water types. Individual data points are classified as to parent water type(s) and then plotted in plan view to show the watermass boundaries and mixing regions. The methodology was applied to the AOL data from the SUPERFLUX overflights. The results are compared to salinity-mapping radar results from the same region.
Cluster analysis and an ordination procedure were performed on two data matrices to investigate real and environmental spatial relationships. Multiple regression analysis was used to relate the measured environmental variables to the phytoplankton community changes. Qualitative type phytoplankton data proved to be less structured in both of these spaces, relative to the biomass data. The salinity gradients of the northern transects covaried significantly with the phytoplankton association changes. In the southern transects the light variable was most important in explaining the variance in the ordination axes. These data suggest the close relationships between phytoplankton community changes and the physical hydrology of the area.
Electron microprobe analyses have been performed on glasses of impact origin in Apollo 11 breccias (10059, 10060, 10061), Apollo 12 soil (12070), and Apollo 15 breccias (15318, 15425, 15426, 15427). These glasses were produced by shock melting of regolith, rather than of rock. Simple concepts for better understanding and interpreting the chemical data from impact glasses have been developed. These concepts are a significant improvement on earlier strategies, which centered principally on cluster analysis. Using ratios of refractory lithophile elements, the compositional effects of fractional vaporization often associated with impact melting to obtain chemical information about the mare and highland components in the regoliths parental to the glasses have been 'seen through'. This method is also applied to the mare-derived impact glasses from Apollo 16 in order to place constraints on the types of volcanic components occurring in Mare Nectaris. Since impact glasses can be used to derive chemical constraints on the indigenous lithologies comprising multi-component regoliths; the frequent occurrence of these glasses, as well as their low masses, should make them critically important for study when small quantities of grab-samples are returned by future unmanned spacecraft from planets, satellites, and asteroids where regoliths are present.
An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.
The radar altimetry, roughness (RMS slopes), and reflectivity data acquired for Venus represent the only global radar information available for any of the planets. In addition, the Pioneer Venus radar instrument was able to sound the surface at normal incidence so that it was possible to accurately measure the small-scale surface slopes and reflectivity (dielectric and porosity properties) at the same time as the surface elevation. Analyses of the topography of Venus demonstrate that it differs in its distribution from the Moon, Mars, or the Earth. While the range of topography extends from -2.5 km below the reference level to 11.5 km above, most of Venus falls within 1 km of the mean elevation, this is in sharp contrast to the Earth. The narrow, unimodal nature of the distribution of topography on Venus evidently exerts control on the other radar-derived properties of the surface. When clustering analysis techniques are applied to the Venus radar data sets, the result demonstrates that topographic zones serve as the best criteria for distinguishing regions on Venus which have related radar properties. The individual radar data sets are investigated separately and in conjunction with topography.
A classification database using the reflectivity (derived from the altimetry data), rms slope, and the first principal component of altimetry and topographic slope is presented. The resultant clustered data is examined qualitatively as well as quantitatively, to establish the statistical integrity of each cluster by use of an interactive, ternary plotting algorithm. This algorithm plots, for a cluster, the position of each of its pixels within a ternary diagram whose apices represent reflectivity, rms slope, and the first principal component. The digital values in these three databases are normalized such that unity is represented by a value of 255 in each database. The frequencies of each plotted point within the ternary diagram are recorded in order to establish the mode of each cluster. The pixels of each cluster are displayed as one separate color; their ternary plot will show not only the interrelations between clusters, but also the presence of any anomalous points within a cluster. Existing lunar and terrestrial analog radar data is used to establish fields within this ternary diagram that are indicative of as many different geologic materials and tectonics settings as possible. The resultant fields are used to determine empirically the geologic significance of the clusters resulting from the cluster analysis.
The general characteristics and microwave radiative properties of sea ice in the Weddell Sea region during the onset of spring are studied by using the Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) and other satellite sensors, in conjunction with in situ observations from the Mikhail Somov. The position of the ice edge, the gradient of ice concentration, and the width of the Marginal Ice Zone are inferred from the microwave data, and are found to be consistent with ship observations, especially at 18 GHz. The sensitivities of the various SMMR frequencies to surface and other effects are investigated by using multispectral cluster analysis. The results show considerable variability in emissivity, especially at 37 GHz, likely associated with varying degrees of surface wetness. Ice concentrations are derived by using two methods: one that assumes fixed emissivities for consolidated ice and an iterative procedure that accounts for the variable emissivities observed. Using the procedure that allows the emissivities to be variable gives ice concentrations that are more consistent with qualitative field observations.
Two primary areas are being pursued: (1) Applications of TOMS total ozone data to estimate the tropopause height and consequently to improve the temperature retrievals from satellite measurements; and (2) Applications of cluster analysis to satellite soundings. The strategy is to either use regression retrievals stratified by tropopause or to use the tropopause information as a constraint on the solution to the physical retrieval method.
The architectures, programming characteristics, and ranges of application of past, present, and planned array processors for the digital processing of remote-sensing images are compared. Such functions as radiometric and geometric corrections, principal-components analysis, cluster coding, histogram generation, grey-level mapping, convolution, classification, and mensuration and modeling operations are considered, and both pipeline-type and single-instruction/multiple-data-stream (SIMD) arrays are evaluated. Numerical results are presented in a table, and it is found that the pipeline-type arrays normally used with minicomputers increase their speed significantly at low cost, while even further gains are provided by the more expensive SIMD arrays. Most image-processing operations become I/O-limited when SIMD arrays are used with current I/O devices.
The semiarid climate of the U.S. northern High Plains region has been studied with respect to rain rates and their evolution during summertime convective storms, using radar data from a total of 750 radar echo clusters. Analysis of this data suggests that the average rain rate R among storms is in a first approximation independent of the total rain volume, if the entire storm duration is considered in the averaging process. R primarily depends on the reflectivity threshold considered in calculating the area coverage integrated over the lifetime of the storm. R evolution during storms is analyzed by dividing each storm lifetime into 10 min, 1, 2, and 4 hours, as well as growing and decaying periods. The value of R remained independent of the total rain volume when the growing or decaying periods of storms were considered separately.
Spectral information content was quantitatively measured for simulated SPOT, Thematic Mapper, and simulated Thematic Mapper data acquired over Santa Cruz County, California. Two techniques were employed: spectral separability summarized through optimal wave band evaluation, and histogram cluster analysis. Using data from the three sources it is shown that three spectral bands can provide separability nearly as high as six bands provide, if the three bands are optimally chosen for the cover type. Analysis of the Santa Cruz scene emphasizes the importance of TM bands 1 and 5 in particular. The three bands of the SPOT scanner are shown to provide sufficient separability for cover types within the study area. The higher spatial resolution data (20 meters) provided by SPOT contain more distinct distributions than data from the other sources studied. Techniques should be developed to exploit this additional information.
Thematic mapping data was analyzed and verified by comparison to previously gathered transect samples and to aerial photographs. A bare-soil field with exposed paleosols characterized by slight enrichment of iron was investigated. Spectral relationships were first investigated statistically by creating a data set with DN values spatially matched as nearly as possible to field sample points. Chemical data for each point included organic carbon, free iron oxide, and amorphous iron content. The chemical data, DN values, and various band ratios were examined with the program package Statistix in order to find the combinations of reflectance data most likely to show a relationship which would dependably separate the exposed paleosols from the other soils. Cluster analysis and Fastclas classification procedures were applied to the most promising of the band ratio combinations.
A probabilistic scheme is developed to predict process resource usage in UNIX. Given the identity of the program being run, the scheme predicts CPU time, file I/O, and memory requirements of a process at the beginning of its life. The scheme uses a state-transition model of the program's resource usage in its past executions for prediction. The states of the model are the resource regions obtained from an off-line cluster analysis of processes run on the system. The proposed method is shown to work on data collected from a VAX 11/780 running 4.3 BSD UNIX. The results show that the predicted values correlate well with the actual. The correlation coefficient between the predicted and actual values of CPU time is 0.84. Errors in prediction are mostly small. Some 82% of errors in CPU time prediction are less than 0.5 standard deviations of process CPU time.