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Gary L. Raines

Publications and source records attributed to Gary L. Raines.

At least 19 recordsLinked to original sources
USGS2006

Thematic mapper-derived mineral distribution maps of Idaho, Nevada, and western Montana

This report provides mineral distribution maps based on TM spectral information of minerals commonly associated with hydrothermal alteration in Nevada, Idaho, and western Montana. The product of the processing is provided as four ESRI GRID files with 30 m resolution by state. UTM Zone 11 projection is used for Nevada (grid clsnv) and western Idaho (grid clsid), UTM Zone 12 is used for eastern Idaho and western Montana (grid clsid_mt). A fourth grid with a special Albers projection is used for the Headwaters project covering Idaho and western Montana (grid crccls_hs). Symbolization for all four grids is stored in the ESRI layer or LYR files and color or CLR files. Objectives of the analyses were to cover a large area very quickly and to provide data that could be used at a scale of 1:100,000 or smaller. Thus, the image processing was standardized for speed while still achieving the desired 1:100,000-scale level of detail. Consequently, some subtle features of mineralogy may be missed. The hydrothermal alteration data were not field checked to separate mineral occurrences due to hydrothermal alteration from those due to other natural occurrences. The data were evaluated by overlaying the results with 1:100,000 scale topographic maps to confirm correlation with known mineralized areas. The data were also tested in the Battle Mountain area of north-central Nevada by a weights-of-evidence correlation analysis with metallic mineral sites from the USGS Mineral Resources Data System and were found to have significant spatial correlation. On the basis of on these analyses, the data are considered useful for regional studies at scales of 1:100,000.

Data Series↗
USGS2003

Spatial digital database for the geologic map of Oregon

Introduction This report describes and makes available a geologic digital spatial database (orgeo) representing the geologic map of Oregon (Walker and MacLeod, 1991). The original paper publication was printed as a single map sheet at a scale of 1:500,000, accompanied by a second sheet containing map unit descriptions and ancillary data. A digital version of the Walker and MacLeod (1991) map was included in Raines and others (1996). The dataset provided by this open-file report supersedes the earlier published digital version (Raines and others, 1996). This digital spatial database is one of many being created by the U.S. Geological Survey as an ongoing effort to provide geologic information for use in spatial analysis in a geographic information system (GIS). This database can be queried in many ways to produce a variety of geologic maps. This database is not meant to be used or displayed at any scale larger than 1:500,000 (for example, 1:100,000). This report describes the methods used to convert the geologic map data into a digital format, describes the ArcInfo GIS file structures and relationships, and explains how to download the digital files from the U.S. Geological Survey public access World Wide Web site on the Internet. Scanned images of the printed map (Walker and MacLeod, 1991), their correlation of map units, and their explanation of map symbols are also available for download.

Oregon↗
USGS2001

Resource materials for a GIS spatial analysis course

This report consists of materials prepared for a GIS spatial analysis course offered as part of the Geography curriculum at the University of Nevada, Reno and the University of California at Santa Barbara in the spring of 2000. The report is intended to share information with instructors preparing spatial-modeling training and scientists with advanced GIS expertise. The students taking this class had completed each universities GIS curriculum and had a foundation in statistics as part of a science major. This report is organized into chapters that contain the following: Slides used during lectures, Guidance on the use of Arcview, Introduction to filtering in Arcview, Conventional and spatial correlation in Arcview, Tools for fuzzification in Arcview, Data and instructions for creating using ArcSDM for simple weights-of-evidence, fuzzy logic, and neural network models for Carlin-type gold deposits in central Nevada, Reading list on spatial modeling, and Selected student spatial-modeling posters from the laboratory exercises.

Open-File Report↗
USGS1999

Evaluation of weights of evidence to predict epithermal-gold deposits in the Great Basin of the western United States

The weights-of-evidence method provides a simple approach to the integration of diverse geologic information. The application addressed is to construct a model that predicts the locations of epithermal-gold mineral deposits in the Great Basin of the western United States. Weights of evidence is a data-driven method requiring known deposits and occurrences that are used as training sites in the evaluated area. Four hundred and fifteen known hot spring gold–silver, Comstock vein, hot spring mercury, epithermal manganese, and volcanogenic uranium deposits and occurrences in Nevada were used to define an area of 327.4 km 2 as training sites to develop the model. The model consists of nine weighted-map patterns that are combined to produce a favorability map predicting the distribution of epithermal-gold deposits. Using a measure of the association of training sites with predictor features (or patterns), the patterns can be ranked from best to worst predictors. Based on proximity analysis, the strongest predictor is the area within 8 km of volcanic rocks younger than 43 Ma. Being close to volcanic rocks is not highly weighted, but being far from volcanic rocks causes a strong negative weight. These weights suggest that proximity to volcanic rocks define where deposits do not occur. The second best pattern is the area within 1 km of hydrothermally altered areas. The next best pattern is the area within 1 km of known placer-gold sites. The proximity analysis for gold placers weights this pattern as useful when close to known placer sites, but unimportant where placers do not exist. The remaining patterns are significantly weaker predictors. In order of decreasing correlation, they are: proximity to volcanic vents, proximity to east-west to northwest faults, elevated airborne radiometric uranium, proximity to northwest to west and north-northwest linear features, elevated aeromagnetics, and anomalous geochemistry. This ordering of the patterns is a function of the quality, applicability, and use of the data. The nine-pattern favorability map can be evaluated by comparison with the USGS National Assessment for hot spring gold–silver deposits. The Spearman's ranked correlation coefficient between the favorability and the National Assessment permissive tracts is 0.5. Tabulations of the areas of agreement and disagreement between the two maps show 74% agreement for the Great Basin. The posterior probabilities for 51 significant deposits in the Great Basin, both used and not used in the model, show the following: 26 classified as favorable; 25 classified as permissive; and 1, Florida Canyon, classified as nonpermissive.The Florida Canyon deposit has a low favorability because there are no volcanic rocks near the deposit on the Nevada geologic map used. The largest areas of disagreement are caused by the USGS National Assessment team concluding that volcanic rocks older than 27 Ma in Nevada are not permissive, which was not assumed in this model. The weights-of-evidence model is evaluated as reasonable and delineates permissive areas for epithermal deposits comparable to expert's delineation. The weights-of-evidence model has the additional characteristics that it is well defined, reproducible, objective, and provides a quantitative measure of confidence.

California, Nevada↗
USGS1996

Great Basin geoscience data base

This CD-ROM serves as the archive for 73 digital GIS data set for the Great Basin. The data sets cover Nevada, eastern California, southeastern Oregon, southern Idaho, and western Utah. Some of the data sets are incomplete for the total area. On the CD-ROM, the data are provided in three formats, a prototype Federal Data Exchange standard format, the ESRI PC ARCVIEW1 format for viewing the data, and the ESRI ARC/INFO export format. Extensive documentation is provided to describe the data, the sources, and data enhancements. The following data are provided. One group of coverages comes primarily from 1:2,000,000-scale National Atlas data and can be assembled for use as base maps. These various forms of topographic information. In addition, public land system data sets are provided from the 1:2,500,000-scale Geologic Map of the United States and 1:500,000-scale geologic maps of Nevada, Oregon, and Utah. Geochemical data from the National Uranium Resource Evaluation (NURE) program are provided for most of the Great Basin. Geophysical data are provided for most of the Great Basin, typically gridded data with a spacing of 1 km. The geophysical data sets include aeromagnetics, gravity, radiometric data, and several derivative products. The thematic data sets include geochronology, calderas, pluvial lakes, tectonic extension domains, distribution of pre-Cenozoic terranes, limonite anomalies, Landsat linear features, mineral sites, and Bureau of Land Management exploration and mining permits.

Data Series↗
USGS1996

Digital representation of the Washington state geologic map: a contribution to the Interior Columbia River Basin Ecosystem Management Project

This report describes the digital representation of the Washington state geologic map (Hunting and others, 1961). This report contains an explantion of why the data were prepared, a description of the digital data, and information on obtaining the digital files. This report is one in a series of digital maps, data files, and reports generated by the U.S. Geological Survey to provide geologic process and mineral resource information to the Interior Columbia Basin Ecosystem Management Project (ICBEMP). The various digital maps and data files are being used in a geographic information system (GIS)-based ecosystem assessment including an analysis of diverse questions relating to past, present, and future conditions within the general area of the Columbia River Basin east of the Cascade Mountains.

Open-File Report↗
USGS1990

Metallic-mineral assessment of the Aban Al Ahmar quadrangle, sheet 25F, Kingdom of Saudi Arabia

Comprehensive detailed interdisciplinary study assesses the metallic-mineral-resource potential in the Aban Al Ahmar Quadrangle of the Kingdom of Saudi Arabia, located in the eastern margin of the northeastern Arabian Shield, utilizing techniques of geophysics, geologic mapping, remote sensing and geochemistry. The landscape of the study area is characterized by isolated mountain groups, inselbergs, and local tracts of dissected hills separated by broad, low-relief peneplain. Topics covered include mining and exploration history; geological setting; interpretation of geophysical anomalies; limonitic hydrothermally altered and mineralized rocks; geochemical interpretation; mineral resource potential; skarn deposiits associated with intermediate igneous rocks; gold deposits; tin/tungsten skarn deposits; etc.

Aban Al Ahmar quadrangle↗
USGS1988

Mineral resources of the Whipple Mountains and Whipple Mountains Addition Wilderness Study Areas, San Bernardino County, California

At the request of the U.S. Bureau of Land Management, approximately 85,100 acres of the Whipple Mountains Wilderness Study Area (CDCA-312) and 1,380 acres of the Whipple Mountains Addition Wilderness Study Area (AZ-050-010) were evaluated for identified mineral resources (known) and mineral resource potential (undiscovered). In this report, the Whipple Mountains and Whipple Mountains Addition Wilderness Study Areas are referred to as simply "the study area." Most of the mines and prospects with identified resources in the Whipple Mountains Wilderness Study Area are within areas designated as having mineral resource potential. The area in and around the Turk Silver mine and the Lucky Green group and the area near the northwest boundary of the study area have high mineral resource potential for copper, lead, zinc, gold, and silver. An area along the west boundary of the study area has moderate resource potential for copper lead, zinc, gold, and silver. An area in the east adjacent to the Whipple Mountains Addition Wilderness Study Area has moderate resource potential for copper, gold, and silver resources. One area on the north boundary and one on the southeast boundary of the study area have low mineral resource potential for copper, lead, zinc, gold, and silver. Two areas, one on the north boundary and one inside the east boundary of the study area, have moderate resource potential for manganese. A small area inside the south boundary of the study area has high resource potential for decorative building stone, and the entire study area has low resource potential for sand and gravel and other rock products suitable for construction. Two areas in the eastern part of the study area have low resource potential for uranium. There is no resource potential for oil and gas or geothermal resources in the Whipple Mountains Wilderness Study Area. Sites within the Whipple Mountains Wilderness Study Area with identified resources of copper, gold, silver, manganese and (or) decorative building stone are located at the Stewart mine, New American Eagle mine, Turk Silver mine, Twin Lode mine, decorative stone property, Lucky Green group, Blue Cloud mine, Nickel Plate mine, Crescent mine, Quadrangle Copper group, and the Copper Basin mine. The Whipple Mountains Addition Wilderness Study Area has moderate resource potential for copper, gold, and silver resources and low resource potential for sand and gravel and other rock products. There is no resource potential for oil and gas or for geothermal energy in the Whipple Mountains Addition Wilderness Study Area. Although there are no identified resources in the Whipple Mountains Addition Wilderness Study Area, sites within and immediately adjacent warrant further study because of gold assays from widespread, numerous samples.

California↗
USGS1984

REMOTE-SENSING MINERAL DISCOVERIES IN THE MOJAVE DESERT OF CALIFORNIA.

As a result of remote sensing studies in the Mojave Desert of California three previously unknown stockwork molybdenum systems have been discovered. It is not known if economic deposits of molybdenum and associated minerals occur in these areas; there is, however, sufficient data to judge that these areas are worthy of further exploration. The purpose of this paper is to present case histories of two of these discoveries. These discoveries have been made from laboratory analyses of Landsat multispectral scanner images to map limonitic materials and from field reconnaissance to determine if the limonite is due to hydrothermal alteration. In those areas that seemed most promising, airborne spectrometer surveys were employed to mapped Al-OH minerals, and audio-magnetotelluric (AMT) and telluric-traversing surveys were performed to obtain information at depth.

Conference Paper↗
USGS1984

TECHNIQUE FOR ENHANCING DIGITAL COLOR IMAGES BY CONTRAST STRETCHING IN MUNSELL COLOR SPACE.

The Munsell color system can be used to further enhance the appearance of high-quality digital color-composite images. A color-balanced 'standard' color-composite image is first produced using any desired contrast stretching algorithm. The stretched digital data are then transformed into the cylindrical Munsell color space. An enhanced version of a color-composite image is produced by stretching the saturation parameter over the full digital range and inverting the modified Munsell coordinates to red-blue-green (tristimulus) data space. The resulting image has greater color-saturation contrast than the original image, without hue change. Contrast stretching in Munsell color space reduces the correlation between individual bands or ratios and is similar to decorrelation processing based on principal-components transforms. However, principal components are based on data variance, with less variance being explained by each higher order component.

Conference Paper↗