Spatial databases of the Humboldt Basin mineral resource assessment, northern Nevada

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Metadata:

Identification_Information
Data_Quality_Information
Spatial_Data_Organization_Information
Spatial_Reference_Information
Entity_and_Attribute_Information
Distribution_Information
Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator: Mark J. Mihalasky

Originator: Lorre A. Moyer

Publication_Date: 2004

Title:

Spatial databases of the Humboldt Basin mineral resource assessment, northern Nevada

Edition: version 1.0

Geospatial_Data_Presentation_Form: raster digital data

Series_Information:

Series_Name: U. S. Geological Survey Open-File Report

Issue_Identification: 2004-1245

Publication_Information:

Publication_Place: Menlo Park, CA

Publisher: U. S. Geological Survey

Online_Linkage: <http://pubs.usgs.gov/of/2004/1245>

Description:

Abstract:

This metadata document describes the origin, generation, and format of the Epithermal Au-Ag tract map that accompanies the assessment of metallic mineral resources in the Humboldt River Basin (HRB). A "mineral-resource assessment tract" is a geographic region (a tract of land) that has been determined to possess geologic attributes that allow for the occurrence of mineral resources of a particular type(s). The assessment, finished in 2002, was carried out for all of northern Nevada, north of 38.5 degrees latitude, but focused primarily on the HRB. The assessment team delineated non-permissive, permissive, favorable, and prospective assessment tracts for Epithermal Au-Ag mineral occurrences or deposits using digital data and a combination of knowledge- and data-driven GIS-based analyses and modeling techniques (for more information about tract delineation and ranking, see the "Identification_Information / Description / Supplemental_Information" section of the metadata). Expert knowledge was used to (1) create, select, and appraise datasets for data-driven modeling, (2) delineate permissive and non-permissive assessment tracts, and (3) evaluate and revise preliminary mineral-resource assessment tracts derived from data-driven modeling. Data-driven modeling, including weights of evidence and weighted logistic regression, was used to delineate prospective and favorable assessment tracts. This land classification is stored in the tract attribute. Modeling was carried out with the ArcView GIS extension "Arc-SDM" (Spatial Data Modeller), developed by the U.S. Geological Survey and the Geological Survey of Canada (Kemp and others, 2001).

The mineral-resource assessment tract map is a GIS product, and is provided as an ESRI integer grid file named "epi" in an ESRI interchange-format file. This file can be viewed as an image or a raster with ESRI's Spatial Analyst extension. Both the expert and data-driven components of the assessment were conducted using data that range in scale from 1:250,000 to about 1:1,000,000. Manipulation and combination of these data has further decreased their collective resolution and accuracy to nearer 1:1,000,000. In practical terms, the ground resolution of the assessment tract map is about 2 km. The assessment tract map released here constitutes only part of the assessment, which additionally includes (1) new research and up-to-date reviews of the geology, mineral resources, and data for northern Nevada and (2) discussions on land classification and how to interpret and use the map.

For simplest use the grid should be symbolized with the tract attribute.

For addition information and details, see:

Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Kemp, L.D., Bonham-Carter, G.F., Raines, G.L. and Looney, C.G., 2001, Arc-SDM: Arcview extension for spatial data modelling using weights of evidence, logistic regression, fuzzy logic and neural network analysis, [<http://www.ige.unicamp.br/sdm/>]>.

Purpose:

The Humboldt River Basin (HRB) is an arid to semiarid, internally drained basin that covers approximately 43,000 km2 in northern Nevada. The basin contains a wide variety of metallic and non-metallic mineral deposits and occurrences. In 1992, and again in 1996, the Nevada State Office of the Bureau of Land Management (BLM) requested a mineral-resource assessment of the HRB to aid their land-use planning. The purpose of the assessment was to (1) assess the favorability for undiscovered metallic mineral occurrences and deposits in the HRB and adjacent areas, (2) provide an analysis of the mineral-resource favorability that can be reproduced on the basis of the data and defined assumptions, and (3) present that assessment in a digital format, using a Geographic Information System (GIS). Finished in 2002, the assessment includes three GIS mineral-resource assessment tract maps (see below). The tract map released here constitutes only part of the assessment, which additionally includes (1) new research and up-to-date reviews of the geology, mineral resources, and data for northern Nevada and (2) discussions on land classification and how to interpret and use the assessment tract map.

The HRB mineral-resource study assessed the potential for undiscovered mineralizing systems (pluton-related polymetallic, sedimentary rock-hosted Au-Ag, and epithermal Au-Ag) and contained mineral deposits and occurrences, instead of the specific deposit types related to those systems. The rationale for this approach was that (1) mineralizing systems are larger than individual mineral deposits, (2) mineralizing systems can form more than one individual deposit type, and (3) the presence of one mineral deposit type might indicate the presence of a larger system. In some locations, the various deposit types in a mineralizing system represent a continuum of site-specific processes of mineral deposition. As a result, the economic viability of any part(s) of the mineralizing system is a function of its metal endowment. Thus, the approach that was taken in the HRB assessment addresses areas where mineralizing processes took place over relatively large areas to form concentrations of metallic minerals.

Three fundamental types of mineralizing systems are addressed in the HRB mineral-resource assessment: (1) pluton-related polymetallic, (2) sedimentary rock-hosted Au-Ag, and (3) epithermal Au-Ag. Although these three systems can have some genetic and spatial overlap, their features and origins are sufficiently distinct to allow for separate evaluation. These three types of mineralizing systems account for most of the important lode metallic mineral deposits discovered in northern Nevada since the middle of the Nineteenth Century. They are important sources of gold, silver, copper, lead, zinc, and molybdenum. Pluton-related polymetallic systems also have potential for producing platinum-group elements (PGE).

For addition information and details, see:

Supplemental_Information:

Note: The metadata section, Quantitative_Attribute_Accuracy_Assessment, is truncated in the FAQ version of the metadata, if you are interested in a more detailed discussion of the quantitative assessment of error and uncertainty related to the WofE and WLR analysis and associated tables (WOE, WOEVAR, PBR, LRCOEF) refer to the longer form of the FGDC metadata. The following is an overview of the analysis and modeling methods used to generate the HRB mineral-resource assessment tract maps.

The tract map is a GIS-based product, and was generated by integrating multiple geoscientific maps using weights of evidence (WofE) and weighted logistic regression (WLR) mineral potential modeling techniques. Modeling was carried out with the ArcView GIS extension "Arc-SDM" (Spatial Data Modeller), developed by the U.S. Geological Survey and the Geological Survey of Canada (<http://www.ige.unicamp.br/sdm/>).

The HRB mineral-resource assessment team delineated non-permissive, permissive, favorable, and prospective assessment tracts using digital data and a combination of knowledge- and data-driven GIS-based analyses and modeling techniques. This land classification is stored in the tract attribute. Expert knowledge was used to (1) create, select, and appraise datasets for data-driven modeling, (2) delineate permissive and non-permissive assessment tracts, and (3) evaluate and revise preliminary mineral-resource assessment maps derived from data-driven modeling. Data-driven modeling, including weights of evidence (WofE) and weighted logistic regression (WLR), was used to delineate prospective and favorable assessment tracts.

WofE and WLR are empirical, data-driven methodologies for integrating spatial data patterns and building predictive models (Bonham-Carter, 1994). They use (1) conditional probabilities to measure the spatial association between point objects and patterns, and (2) Bayes' probability theorem (WofE) or WLR to statistically integrate the patterns to predict the distribution of the point objects. As applied in this mineral-resource assessment, the patterns represent geoscientific phenomena that are considered useful mineral predictors, and are referred to as "evidence maps". The point objects represent known mineral sites, and are referred to as "training sites". Evidence and training datasets used to generate the Epithermal Au-Ag mineral-resource assessment tract map are described in Wallace and others (2004).

Evidence maps are typically multi-class and include representations of geological map units, structure, and geochemical and geophysical anomalies (as well as remotely sensed images and other earth-observation data, and even conceptual or interpretive maps). In order to facilitate combination, the evidence maps are usually reduced to predictor patterns of a few discrete states, typically binary- or ternary-class, where the spatial association between the training sites and an evidence map is optimized. The evidence maps collectively constitute "layers of evidence".

Training sites are used to identify and weight the importance of predictor patterns on evidence maps. Training sites collectively possess characteristics that are common to a particular deposit type. It is presumed that their location and presence enable prediction of the particular deposit type represented. Training sites are regarded as binary, either present or absent.

WofE and WLR models consist of integrated predictor patterns and are expressed in the form of a single "favorability map" of posterior probability. The favorability map represents the spatial distribution of training sites in terms of the spatial distribution of predictor patterns, as well as the predicted distribution of yet unidentified sites. The favorability map is ranked relatively from lowest to highest as "non-permissive", "permissive", "favorable", and "prospective" mineral-resource assessment tracts. The non-permissive and permissive mineral-resource assessment tracts were delineated using a previous, knowledge-driven assessment for Nevada (Cox and others, 1996) because the assessment team felt this provided the best definition of these tracts. Prospective and favorable tracts reflect the combination of the evidence maps. For a given combination, the contribution of each evidence map to the level of favorability is derived statistically from the spatial association between the distribution pattern of the training sites and the geoscientific phenomena represented in the evidence maps. For example, if the statistical calculations determine that training sites have a greater spatial association with geochemical anomalies than with a geophysical anomalies, then the geochemical anomalies contribute more to the level of favorability than do the geophysical anomalies. The implication is that certain evidence map combinations represent a greater likelihood that mineralizing processes took place in a given area than other combinations. Thus, a prospective area represents the optimum combination of the evidence maps, whereas a favorable area consists of a somewhat less optimum, but still relatively significant, combination. For additional information about ranks, See the "Identification_Information / Use_Constraints" and "Entity_and_Attribute_Information / Detailed_Description / Attribute / Attribute_Label / TRACT" sections of the metadata, as well as Chapter 2 of Wallace and others (2004).

For this assessment, WofE was used to analyze the bivariate spatial associations between the training sites and the various evidence maps, and thus to define the predictor patterns. WLR was used to integrate (combine) the evidence maps and delineate the prospective and favorable assessment tracts. In some cases, the evidence maps selected by the assessment team had a high conditional dependence (mutually interrelated). By using WLR to combine the maps, bias caused by conditional dependency was avoided. The non-permissive-permissive tract boundary was delineated using a previous, knowledge-driven assessment for Nevada (Cox and others, 1996) because the assessment team felt this provided the best definition of these tracts.

Bonham-Carter, G.F., 1994, Geographic Information Systems for Geoscientists: Modelling with GIS (Computer Methods in the Geosciences Volume 13): Tarrytown, New York, Pergamon Press/Elsevier Science Publications, 398 p.

Singer, D.A., ed., 1996, An analysis of Nevada's metal-bearing mineral resources: Nevada Bureau of Mines and Geology Open-file Report 96-2, <http://www.nbmg.unr.edu/dox/ofr962/cover.pdf>.

For addition information and details, see:

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2004

Currentness_Reference:

Published 2004. Mineral-resource assessment tract grid created in 2001.

Status:

Progress: Complete

Maintenance_and_Update_Frequency: As needed

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -120.00

East_Bounding_Coordinate: -114.05

North_Bounding_Coordinate: 42.00

South_Bounding_Coordinate: 38.50

Keywords:

Theme:

Theme_Keyword_Thesaurus: none

Theme_Keyword: mineral-resource assessment

Theme_Keyword: epithermal Au-Ag

Theme_Keyword: metallic mineral occurrences and deposits

Theme_Keyword: weights of evidence, weighted logistic regression

Theme_Keyword: Arc-SDM (Spatial Data Modeler) for ArcView 3.x

Place:

Place_Keyword_Thesaurus: none

Place_Keyword: Elko County

Place_Keyword: Washoe County

Place_Keyword: Humboldt County

Place_Keyword: Eureka County

Place_Keyword: Lander County

Place_Keyword: Pershing County

Place_Keyword: White Pine County

Place_Keyword: Churchill County

Place_Keyword: Lyon County

Place_Keyword: Storey County

Place_Keyword: Douglas County

Place_Keyword: Humboldt River Basin

Place_Keyword: Great Basin

Place_Keyword: Nevada

Place_Keyword: South Western US

Place_Keyword: USA

Access_Constraints: none

Use_Constraints:

It is strongly recommended that the user consult the "Identification_Information / Description / Supplemental_Information" section of the metadata, as well as Chapter 2 of Wallace and others (2004), for information about the expert analysis, modeling techniques, and the vocabulary used in this mineral-resource assessment, as this information is essential for properly interpreting and applying the assessment tract maps.

Scale of Usage:

Both the expert and data-driven components of the HRB mineral-resource assessment were conducted using data that range in scale from 1:250,000 to about 1:1,000,000. These scales were chosen because many of the data sets used in the assessment were at those scales, most notably the geologic map of Nevada and various derivative maps. Manipulation of these data as part of the expert analysis and data-driven modeling processes, as well as the combination of these different scale data, has further decreased their collective resolution and accuracy to nearer 1:1,000,000. As such, the mineral-resource assessment tract maps should not be used at a scale larger than 1:1,000,000. In practical terms, the ground resolution of the assessment maps is about 2 km. Therefore, any boundary between two assessment tracts has no greater resolution than 2 km. In keeping with the regional concept of this assessment, and the possible use of the maps for land-use planning purposes, any small areas of interest that lie along or near a tract boundary should be evaluated with care and with supplementary data that are consistent with the large scale and resolution of the area being examined. Similar considerations should be applied when working with small, isolated assessment tract areas, as they are less reliably classified, as discussed further below.

The purpose of the assessment was to delineate broad areas in northern Nevada and the HRB that are relatively more or less likely to contain undiscovered mineral deposits. This purpose, and the regional scale of the data used to achieve it, should be kept in mind when using this assessment and the digital mineral-resource assessment maps. Use of maps at larger scales to examine small areas in detail diverges from the concept and purpose of the assessment and the assessment maps.

What the Prospective and Favorable Tracts Represent:

The data used for data-driven modeling were selected because they reflect geological, geochemical, and geophysical attributes common to known pluton-related polymetallic, sedimentary rock-hosted Au-Ag, and epithermal Au-Ag mineral deposits and mineralizing processes in the assessment area. The resulting prospective and favorable tracts are areas in which the data have an optimal combination of attributes found at known deposits. This does not mean that mineralizing processes took place in those areas, but rather that the models identify areas that may warrant further, more detailed evaluation before land-use or mining-related decisions are made. Conversely, it is considered unlikely that a mineralizing process took place outside of that area.

The assessment tract maps show the more optimal data combinations, from the standpoint of the possible presence of a mineralized system, as "prospective" or "favorable." These areas range in size from small to large. The smallest areas (less than or equal to about 2 square km) are artifacts of the data-driven modeling process; these should be considered "noise" and thus warrant little or no further scrutiny. Some prospective and favorable areas are extensive and represent relatively large areas that have many attributes common to known deposits. Many of these areas have known mineral deposits of the type being assessed. The confidence that these areas have been correctly classified as favorable or prospective is 90% or greater (see Chapter 2, sections "Data-Driven Component" and "Modifications During Data-Driven Modeling" in Wallace and others, 2004).

The assessment tract maps do not define the specific locations of potential deposits within the broad prospective and favorable areas. Given the scale and nature of the data used for the assessment, it is possible that the data do not reflect isolated mineralizing systems and mineral deposits that are outside of prospective or favorable areas. The surface expression of the largest known mineralizing systems in northern Nevada, such as the cluster of large pluton-related polymetallic systems at Battle Mountain, is several tens of square kilometers. The surface expressions of other known, in some cases large, mineral deposits in the region have a somewhat to substantially smaller footprint. In addition, the vertical dimension of some deposits, such as the Meikle deposit in the Carlin trend or the Ken Snyder deposit in Midas, is equal to or greater than their horizontal dimension at the surface. Therefore, more detailed studies of small areas within prospective and favorable tracts require data and concepts relevant to that scale of assessment, similar to the methods employed by the mining industry to evaluate specific properties.

Point_of_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Alan R. Wallace

Contact_Organization: U. S. Geological Survey

Contact_Position: Research Geologist

Contact_Address:

Address_Type: mailing address

Address: C/O Mackay School of Mines

Address: MS-176 University of Nevada

City: Reno

State_or_Province: NV

Postal_Code: 89557

Country: USA

Contact_Voice_Telephone: 1-775-784-5789

Contact_Facsimile_Telephone: 1-775-784-5079

Contact_Electronic_Mail_Address: alan@usgs.gov

Contact_Instructions:

The originator of the dataset, Mark Mihalasky, is no longer with U. S. Geological Survey. Contact Alan Wallace (alan@usgs.gov) or Mark Mihalasky at mihalasky@hotmail.com.

Data_Set_Credit:

Mark J. Mihalasky and the Humboldt Mineral-Resource Assessment Team, Western Region Mineral Resources Team, U. S. Geological Survey. For details, see Wallace and others (2004, Chapter 2).

Security_Information:

Security_Classification_System: None

Security_Classification: Unclassified

Security_Handling_Description: None

Native_Data_Set_Environment:

Microsoft Windows 2000 Version 5.1 (Build 2600) Service Pack 1; ESRI ArcCatalog 8.3.0.800

Cross_Reference:

Citation_Information:

Originator: Mark J. Mihalasky

Originator: Lorre A. Moyer

Publication_Date: 2004

Title:

Spatial databases of the Humboldt Basin mineral resource assessment, northern Nevada

Edition: version 1.0

Geospatial_Data_Presentation_Form: ESRI integer raster

Series_Information:

Series_Name: Open-File Report

Issue_Identification: 2004-1245

Publication_Information:

Publication_Place: Denver, CO

Publisher: U. S. Geological Survey

Other_Citation_Details:

Mineral assessment tract grid and metadata created at U. S. Geological Survey, Reno Field Office, Reno, Nevada.

Online_Linkage: <http://pubs.usgs.gov/of/2004/1245>

Larger_Work_Citation:

Citation_Information:

Originator:

Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R.

Publication_Date: 2004

Title:

Assessment of metallic mineral resources in the Humboldt River Basin, northern Nevada

Edition: Version 1.0

Geospatial_Data_Presentation_Form: none

Series_Information:

Series_Name: U.S. Geological Survey Bulletin

Issue_Identification: 2004-2218

Publication_Information:

Publication_Place: Denver, CO

Publisher: U. S. Geological Survey

Online_Linkage: <http://pubs.usgs.gov/bul/b2218/>

Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:

Considering the measures described below, the tracts delineated meet USGS standards. A Student T test of the confidence in this map indicates a high degree of confidence, approximately greater than 97%, that the reported logistic-regression posterior probabilities are not zero in the permissive, favorable, and prospective tracts. A quantitative assessment of error and uncertainty related to WofE and WLR analysis and modeling is provided in the form of four dBASE tables that are generated by Arc-SDM:

1) woe - Spatial associations among the evidence maps and training sites (mineral occurrences and deposits).

2) woevar - Standard deviations for the spatial weights of association.

3) prb - Results of pair-wise and overall tests for conditional independence.

4) lrcoef - Logistic regression coefficients

The contents of these tables is embedded in this metadata document under the "Quantitative_Attibute_Accuracy_Explanation" section below. The following information will help with interpretation of these tables:

Conditional Independence:

An important assumption made in WofE modeling is that the evidence layers be conditionally independent (CI) of one another with respect to the training sites. Evidence layer dependencies were tested for using a pairwise and an overall goodness-of-fit test, both of which make use of the observed versus the predicted number of observations (training sites). The pairwise test measures CI between all possible pairings of evidence maps (with respect to the training sites) by calculating the chi-square statistic for each map pair. The overall test is a measure of the CI between all of the evidence maps in a model as a whole. The overall test consists a comparison between the predicted number of training sites to the observed number (observed/predicted, referred to as the "CI ratio").

Error and Uncertainty:

An important aspect to interpreting a favorability map is recognizing and quantifying the uncertainty inherent to the posterior probabilities. The two primary sources of uncertainty are: (1) the uncertainty due to variances in weight estimates (W+ and W-); and (2) the uncertainty due to one or more of the evidence maps having incomplete coverage (i.e., missing data).

In addition to the uncertainties due to weights and missing data variances, a relative confidence of the posterior probability can be calculated by dividing the posterior probability by its standard deviation, which is an informal Student t-test to determine whether the posterior probability is greater than zero for a selected level of statistical significance. This confidence test is often more useful than the weights or missing data variances because it indicates the degree of confidence to which the posterior probabilities are meaningful, as opposed to being an artifact of chance effects or interactions. Care should be taken when interpreting the relative certainty because it is based on a normal distribution and sensitive to CI violations.

For additional information on conditional independence, error, and uncertainty, see:

Agterberg, F.P., Bonham-Carter, G.F., Cheng, Q., and Wright, D.F., 1993, Weights of evidence modeling and weighted logistic regression for mineral potential mapping, in Davis, J.C., and Herzfeld, U.C., eds., Computers in Geology, 25 Years of Progress: Oxford, England, Oxford University Press, p. 13-32.

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Value: Refer to Explanation below.

Attribute_Accuracy_Explanation:

The weights table, woe.dbf, generated by Arc-SDM. This table relates to the bivariate spatial associations among the evidence maps and training sites, and provides the spatial weights of association (W+, W-) measured between the training sites and of the evidence maps, as well as the strength of the spatial association (contrast) and its significance (confidence, as measured by the Studentized contrast, which is the contrast divided by its standard deviation).

The following is a description of the fields that make up the table:

Evidence

Name of the evidential theme (evidence map). Names and descriptions of the evidential layers are summarized in the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and detailed in "Entity_and_Attribute_Information / Detailed_Description".

W<#>

The name for each of the fields containing the calculated weights, one for each class that occurs in any of the input evidential themes. If a class of the particular number does not occur in a evidence map, its cell in that field will be blank. Field names are defined as:

W_99 = missing data, where the source evidence are unavailable. W0 = predictor pattern absent (W-). W1 = predictor pattern present (W+).

Contrast

The difference between the highest weight and the smallest weight (W+ - W-).

Confidence

A measure of the confidence that the reported contrast is not zero. The measure is the Studentized contrast, which is the contrast divided by its standard deviation.

The last row of the table contains additional information about model parameters. Below is the column heading and a statement of what that column contains in the last row:

Evidential field - The name of the training site file used for modeling.

1st W<#> field - Total number of training sites.

2nd W<#> field - Total study area in unit cells (km square, in this case).

3rd W<#> field - The prior probability (the total number of training sites divided by the total study area).

For additional explanation, see:

The WOE Table for EPI:

EVIDENCE  W_99       W0       W1       W2      W3   CONTRAST CONFIDENCE

Asfreq    0.0000  -0.0772   3.0238                    3.1009    7.8265

Epilith   0.0000  -1.3170   1.6168  1.0966   1.1941   2.9338    7.8748

magtrrn   0.0000  -0.1344   1.2943                    1.4286    5.9748

Epi.shp   127.0000   193369.9900    0.0007

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Value: Refer to explanation below.

Attribute_Accuracy_Explanation:

The weights variance table, woevar.dbf, generated by Arc-SDM. This table provides the variances for the spatial weights of association (W+, W-) reported in the weights table, woe.dbf.

The weights variance table has the same structure as the weights table, but with the following exceptions:

1) The names of fields containing variances are denoted as V<#>, which correspond to W<#>, respectively.

2) Contrast and confidence are not reported.

3) The training point file name and study area are not reported in the final row.

Names and descriptions of the evidential layers are summarized in the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and detailed in "Entity_and_Attribute_Information / Detailed_Description".

For additional explanation, see:

For specific information on the calculation of the variances for W+ and W-, see:

Mihalasky, M.J., and Bonham-Carter, G.F., 2001, The spatial association between metallic mineral sites and lithodiversity in Nevada: Natural Resources Research, v. 10, no. 3, p. 209-226.

The WOEVAR Table for EPI:

EVIDENCE       V_99       V0         V1        V2         V3

Asfreq          0.0000     0.0121    0.1449

Epilith         0.0000     0.0385    0.1003     0.0771     0.0128

Magtrrn         0.0000     0.0094    0.0477

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Value: Refer to explanation below.

Attribute_Accuracy_Explanation:

The conditional independence test table of probabilities, prb.dbf, generated by Arc-SDM. This table relates to the integration of the evidence maps to produce the favorability map, and provides information on (1) pair-wise chi-square test of conditional independence between evidence maps, and (2) the overall measure of condition independence.

Pair-wise Test:

The table is written like a spreadsheet, with the second through last evidence maps written as column headings, and the first through next-to-last evidence maps written to rows in the first column ("ETHEME"). Names and descriptions of the evidential layers are summarized in the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and detailed in "Entity_and_Attribute_Information / Detailed_Description".

A chi-squared statistic is calculated for the observed number of training sites falling in each evidence map class and is compared to the expected number of sites. Null hypothesis of CI is not rejected (i.e. CI is accepted) at the (probability) level of significance.

Values less than 0.05 indicate some conditional dependence.

The algorithm used for calculating the probabilities iterates a maximum number of times. If a probability is not determined before this maximum is reached, a Null value is returned and the cell in the probability table is set to 0, suggesting a problem with conditional independence.

Overall Test:

Arc-SDM reports a ratio that can be used as an overall assessment of conditional independence among your data sets. This ratio is calculated as follows:

The product of area and posterior probability summed over each unique condition is the number of training sites predicted by the model. A ratio is calculated by dividing the actual (observed) number of sites input to the model by the predicted number of sites.

This ratio will always be between 0 and 1. A value of 1 (never occurs in practice) indicates conditional independence among the evidence maps used in the model. Values much smaller than 1 indicate a conditional independence problem.

An overall test value less than 0.85 indicates significant conditional dependency.

For additional explanation, see:

The PRB table for EPI:

ETHEME       EPILITH     MAGTRRN

Asfreq        0.3093      0.4200

Epilith                   0.2211

Overall Test of Conditional Independence: 0.8900

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Value: Refer to explanation below.

Attribute_Accuracy_Explanation:

The logistic regression coefficients table, lrcoef.dbf, generated by Arc-SDM. This contains the WLR coefficients for the favorability map. The magnitude of a coefficient indicates its relative importance in determining the posterior probabilities of the favorability map.

The following is a description of the fields that make up the table:

Theme_id

Unique identifier for the evidence maps.

Theme

Evidence map name, field name (class value (if expanded)). If the evidence map is a multi-class map (as opposed to binary-class), each class of the map will be expanded to a single binary-class predictor pattern and identified by its class value, which is reported reported in brackets. Names and descriptions of the evidential layers are summarized in the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and detailed in "Entity_and_Attribute_Information / Detailed_Description".

Coefficient

Logistic regression coefficient.

LR_std_dev

Standard deviation of the coefficient.

For additional explanation, see:

The LRCOEF table for EPI:

  THEME ID       THEME              COEFFICIENT      LR_STD_DEV

      1      Constant Value          -8.500227       0.171739

      2      asfreq                   1.064101       0.248386

      3      epilith ( 0 )            0.758493       0.068187

      4      epilith ( 1, 2, 3 )      2.568358       0.409168

Logical_Consistency_Report:

This mineral-resource assessment tract map is a derivative product created by a unique conditions overlap (see Bonham-Carter, 1994) among several evidence layers, which are summarized in the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and detailed in "Entity_and_Attribute_Information / Detailed_Description". As such, its spatial fidelity is related to the compounded fidelity of all evidence layers that were combined.

For an overview of the spatial fidelity of the tract map, see the "Identification_Information / Use_Contraints" section of the metadata above. For information on the spatial fidelity of each evidence layer, see source data information as outlined and referenced in Wallace and others (2004). For the fidelity related to analysis and modeling, the see the results of tests for conditional independence, error, and uncertainty provided under the "Attibute_Accuracy" section of the metadata above.

Completeness_Report:

The Humboldt River Basin (HRB) assessment was carried out for the whole of northern Nevada, north of latitude 38 degrees 30 minutes, but focused primarily on the HRB and adjoining areas. The permissive tract, previously delineated in an earlier assessment by Singer (1996), was used for the HRB assessment but truncated at 38 degrees 30 minutes north latitude. Favorable and prospective mineral-resource assessment tracts, products of the HRB assessment, were merged with the Singer (1996) permissive tracts but are truncated to the extent of (1) the geochemistry evidence map coverage and (2) the extent of the permissive tract (for details, see Wallace and others, 2004, Chapter 2).

Singer, D.A., ed., 1996, An analysis of Nevada's metal-bearing mineral resources: Nevada Bureau of Mines and Geology Open-file Report 96-2, <http://www.nbmg.unr.edu/dox/ofr962/cover.pdf>.

Positional_Accuracy:

Horizontal_Positional_Accuracy:

Horizontal_Positional_Accuracy_Report:

This mineral-resource assessment tract map is a derivative product that was generated by integrating a number of geological, geochemical, and geophysical evidence layers (the specific layers are summarized in the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and detailed in "Entity_and_Attribute_Information / Detailed_Description"). Because of compounding spatial error associated with the integration operation, the mineral-resource assessment tract map is considered to have an accuracy of approximately 1:1,000,000. In practical terms, the ground resolution of the map is about 2 km. For additional details, see the "Identification_Information / Use_Constraints" and "Data_Quality_Information / Logistical_Consistency_Report" sections of the metadata above.

Quantitative_Horizontal_Positional_Accuracy_Assessment:

Horizontal_Positional_Accuracy_Value: 2000 meters

Horizontal_Positional_Accuracy_Explanation:

Regional scale. No better than approximately 1:1,000,000 scale. For additional details, see the "Identification_Information / Use_Constraints" and "Data_Quality_Information / Logistical_Consistency_Report" sections of the metadata above.

Vertical_Positional_Accuracy:

Vertical_Positional_Accuracy_Report: not applicable

Lineage:

Source_Information:

Source_Citation:

Citation_Information:

Originator: Stewart, J.H., and Carlson, J.E.

Publication_Date: 1978

Title: Geologic map of Nevada

Geospatial_Data_Presentation_Form: map

Series_Information:

Series_Name: none

Issue_Identification: none

Publication_Information:

Publication_Place: Denver, CO

Publisher: U.S. Geological Survey and Nevada Bureau of Mines and Geology

Source_Scale_Denominator: 500000

Type_of_Source_Media: paper

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1978

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: Stewart and Carlson (1978)

Source_Contribution:

This dataset was used to create and proof the digital version of the geologic map of Nevada (Raines and others, 1996), which in turn was used to create the following evidence maps for WofE and WLR modeling:

1) Epithermal-lithologic units. The 101 geologic map units were reclassified to five, expert-ranked lithologic host units for epithermal deposits and occurrences, as defined in Wallace and others (2004, Chapter 9). For analysis and modeling, this dataset is considered to have a resolution of 1,000 meters.

For the specific evidence maps used to create this mineral-resource assessment tract map, see the "Entity_and_Attribute_Information / Overview_Description" section of the metadata below, and more detailed information in "Entity_and_Attribute_Information / Detailed_Description".

For references cited and additional information on the evidence maps listed above, see Wallace and others (2004, Chapter 2).

Source_Information:

Source_Citation:

Citation_Information:

Originator: Raines, G.L., Sawatzky, D.L., and Connors, K.A.

Publication_Date: 1996

Title: Great Basin geoscience data base

Geospatial_Data_Presentation_Form: vector digital data - map

Series_Information:

Series_Name: U.S. Geological Survey Digital Data Series

Issue_Identification: DDS-41

Publication_Information:

Publication_Place: Denver, CO

Publisher: U.S. Geological Survey

Source_Scale_Denominator: 500000

Type_of_Source_Media: CD-ROM

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1996

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: Raines and others (1996)

Source_Contribution:

This dataset was used to create the following evidence maps for WofE and WLR modeling:

1) Lithodiversity. Lithodiversity for the geologic map of Nevada was generated by counting the number of unique map units in a square moving window that is 2.5-by-2.5 km in dimension. Lithodiversity was calculated by centering the window on each cell, counting the number of unique geologic map units within the neighborhood, assigning the number to the center cell, and then incrementing the window by one cell. The lithodiversity map was reclassified such that each map class value (an integer) represents diversity. For example, lithodiversity map class 5 represents five geologic units within a sample neighborhood. Mihalasky (2001) and Mihalasky and Bonham-Carter (1999; 2001) discuss methods of preparation and processing of lithodiversity. For analysis and modeling, this dataset is considered to have a resolution of 1,000 meters.

2) Pluton proximity. The plutonic rocks, represented in terms of unit abbreviations from the geologic map of Nevada, include Tri, Tmi, Ti, Tr2, Tr1, TJgr, Tgr, Mzgr, Kgr, KJd, Jgr, TRgr, and TRlgr. These units range in age from Middle-Late Triassic to late Miocene, but with respect to total area covered, the units predominantly are Mesozoic. Plutonic and intrusive bodies were buffered with a distance interval of 1 km. The plutons were included as part of the first buffer. For analysis and modeling, this dataset is considered to have a resolution of 1,000 meters.

For references cited and additional information on the evidence maps listed above, see Wallace and others (2004, Chapter 2).

Source_Information:

Source_Citation:

Citation_Information:

Originator: Folger, H.W.

Publication_Date: 2000

Title:

Analytical results and sample locations of reanalyzed NURE stream-sediment and soil samples for the Humboldt River Basin mineral-environmental assessment, northern Nevada

Edition: 1.0

Geospatial_Data_Presentation_Form: tabular data, with geographic coordinates

Series_Information:

Series_Name: Open-File Report

Issue_Identification: 00-421

Publication_Information:

Publication_Place: Denver, CO

Publisher: U.S. Geological Survey

Type_of_Source_Media: CD-ROM

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2000

Source_Currentness_Reference:

Publication date. Stream-sediment and soil samples were collected in the 1970s under the National Uranium Resource Evaluation program (NURE) and were reanalyzed in the 1990s (Folger, 2000). Details of the program can be found in Smith (2000).

Folger, H.W., 2000, Analytical results and sample locations of reanalyzed NURE stream-sediment and soil samples for the Humboldt River Basin mineral-environmental assessment, northern Nevada: U.S. Geological Survey Open-File Report 2000-421, 1 CD-ROM.

Smith, S.M., 2000, National Geochemical Database - Reformatted Data from the National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance (HSSR): U.S. Geological Survey Open-File Report 97-0492, v. 1.20, [<http://pubs.usgs.gov/of/1997/ofr-97-0492/]>.

Source_Citation_Abbreviation: Folger (2000)

Source_Contribution:

This dataset was used to create the following evidence maps for WofE and WLR modeling:

1) As-frequency. Represents As concentration (partial digestion) that was processed in the frequency domain. The concentration values were log transformed (base-10) and converted to a continuous raster surface with 1,000-meter cell size using a minimum-curvature spatial interpolator. The data were resolved into several textural components by computing the spatial frequency structure of the surface, then deriving a series of band-pass frequency filters to decompose the surface in the frequency domain into distinct layers, each with varying degrees of smoothness. The residual As anomaly evidence map corresponds to subtraction of the long- and medium-wavelength components of the signal. The rationale for this method, and the preparation and processing of this dataset, are discussed in greater detail in Wallace and others (2004, Chapter 5). For analysis and modeling, this dataset is considered to have a resolution of 1,000 meters.

For references cited and additional information on the evidence maps listed above, see Wallace and others (2004, Chapter 2).

Source_Information:

Source_Citation:

Citation_Information:

Originator: Hildenbrand, T.G., and Kucks, R.P.

Publication_Date: 1988

Title: Total intensity magnetic anomaly map of Nevada

Geospatial_Data_Presentation_Form: raster digital data - map

Series_Information:

Series_Name: Nevada Bureau of Mines and Geology Map

Issue_Identification: 93A

Publication_Information:

Publication_Place: Reno, NV

Publisher: Nevada Bureau of Mines and Geology

Source_Scale_Denominator: 750000

Type_of_Source_Media: paper; electronic transfer

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1988

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: Hildenbrand and Kucks (1988)

Source_Contribution:

This dataset was used to create the following evidence maps for WofE and WLR modeling:

1) Magnetic terranes. Reflect regions of similar anomaly features or geophysical fabric. The terranes were derived from the inspection of a total intensity aeromagnetic map, derivative magnetic maps, and maximum horizontal gradients of magnetic potential anomalies. The regions were outlined in vector format and converted to raster with a 500-meter cell size. The preparation and processing of these datasets is discussed in greater detail in Wallace and others (2004, Chapter 6). For analysis and modeling, this dataset is considered to have a resolution of 1,000 meters. A subset of this evidence map, showing the magnetic terranes related to middle Miocene mafic intrusive zones, was created and used for the epithermal assessment (see Wallace and others, 2004, Chapter 9).

For references cited and additional information on the evidence maps listed above, see Wallace and others (2004, Chapter 2).

Source_Information:

Source_Citation:

Citation_Information:

Originator: Ponce, D.A.

Publication_Date: 1997

Title: Gravity data of Nevada

Edition: 1.0

Geospatial_Data_Presentation_Form: tabular data, with geographic coordinates

Series_Information:

Series_Name: U.S. Geological Survey Digital Data Series

Issue_Identification: DDS-42

Publication_Information:

Publication_Place: Denver, CO

Publisher: U.S. Geological Survey

Type_of_Source_Media: CD-ROM

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1997

Source_Currentness_Reference: publication date

Source_Citation_Abbreviation: Ponce (1997)

Source_Contribution:

This dataset was used to create the following evidence maps for WofE and WLR modeling:

1) Depth to basement. Reflects thickness of Cenozoic cover deposits. Isostatic residual gravity data were used to produce a map of the thickness of Cenozoic deposits based on assumed variations of density with depth in these deposits (Chapter 6; Jachens and others, 1996). The depth to basement map does not serve as an evidence map proper. Rather, it is used as an overlay on the mineral-resource tract maps to mask out areas that are covered by Cenozoic deposits that are more than 1 km thick. The preparation and processing of these datasets is discussed in Wallace and others (2004, Chapter 6). For analysis and modeling, this dataset is considered to have a resolution of 2,000 meters.

For references cited and additional information on the evidence maps listed above, see Wallace and others (2004, Chapter 2).

Process_Step:

Process_Description:

The mineral-resource tracts were created by merging knowledge-driven-derived tracts (non-permissive and permissive) and data-driven-derived tracts (favorable and prospective). The non-permissive and permissive tracts were delineated by Singer (1996). The favorable and prospective tracts were delineated using WofE and WLR data-driven analysis and modeling techniques, which can be subdivided into three main procedures: (1) measurement of spatial association between the training sites and the evidence maps, (2) optimization of the evidence maps for prediction (creation of predictor patterns), and (3) combination of the predictor patterns to create favorability maps.

Construction of the final mineral-resource assessment tract maps consisted of four steps: (1) clipping of the favorable and prospective tracts to the extent of geochemistry evidence map coverage (see Wallace and others, 2004, Chapters 2 and 5), (2) clipping of the favorable and prospective tracts to knowledge-driven-delineated permissive tract (Singer, 1996), (3) merging of the clipped favorable and prospective tracts with the knowledge-driven-delineated permissive tract, and (4) masking out of areas where the depth to basement is greater than 1 km (see Wallace and others, 2004, Chapter 6).

For a more thorough discussion of WofE and WLR analysis and modeling techniques, see Bonham-Carter (1989, 1994), Agterberg and others (1990), Wright and Bonham-Carter (1996), Raines (1999), Mihalasky (2001), Raines and Mihalasky (2002), Wallace and others (2004)

Agterberg, F.P., Bonham-Carter, G.F., Wright, D.F., 1990, Statistical pattern integration for mineral exploration, in Gaál, G., and Merriam, D.F., eds., Computer Applications in Resource Estimation Prediction and Assessment of Metals and Petroleum: New York, Pergamon Press, p. 1-12.

Bonham-Carter, G.F., Agterberg, F.P., and Wright, D.F., 1989, Weights of evidence modelling: A new approach to mapping mineral potential, in Agterberg, F.P., and Bonham-Carter, G.F., eds., Statistical Applications in the Earth Science: Geological Survey of Canada, Paper 89-9, p. 171-183.

Mihalasky, M.J., 2001, Mineral potential modelling of gold and silver mineralization in the Nevada Great Basin-A GIS-based analysis using weights of evidence: U.S. Geological Survey Open-File Report 01-291, 448 p., [<http://pubs.usgs.gov/of/2001/of01-291/]>.

Raines, G.L., 1999, Evaluation of weights of evidence to predict epithermal-gold deposits in the Great Basin of the western United States: Natural Resources Research, v. 8, p. 257-276.

Raines, G.L., and Mihalasky, M.J., 2002, A reconnaissance method for regional-scale mineral-resource assessment, based exclusively on geologic-map data: Natural Resources Research, v. 11, no. 4, p. 241-248.

Singer, D.A., 1996, An analysis of Nevada's metal-bearing mineral resources: Nevada Bureau of Mines and Geology Open-File Report 96-2, <http://www.nbmg.unr.edu/dox/ofr962/cover.pdf>

Wright, D.F., and Bonham-Carter, G.F., 1996, VHMS favourability mapping with GIS-based integration models, Chisel Lake-Anderson Lake area, in Bonham-Carter, G.F., Galley, A. G., and Hall, G. E. M., eds., EXTECH I: A Multidisciplinary Approach to Massive Sulphide Research in the Rusty Lake-Snow Lake Greenstone Belts, Manitoba: Geological Survey of Canada Bulletin 426, p. 339-376, 387-401.

Process_Date: 2000-2001

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Alan Wallace

Contact_Organization: U. S. Geological Survey

Contact_Position: Research Geologist

Contact_Address:

Address_Type: mailing address

Address: C/O Mackay School of Mines

Address: MS-176 University of Nevada

City: Reno

State_or_Province: NV

Postal_Code: 89557

Country: USA

Contact_Voice_Telephone: 1-775-784-5789

Contact_Facsimile_Telephone: 1-775-784-5079

Contact_Electronic_Mail_Address: alan@usgs.gov

Hours_of_Service: No set hours

Contact_Instructions:

Originator is no longer with U.S. Geological Survey Western Mineral Resources Team. Contact Alan Wallace (alan@usgs.gov) or Mark Mihalasky at mihalasky@hotmail.com.

Spatial_Data_Organization_Information:

Indirect_Spatial_Reference: none

Direct_Spatial_Reference_Method: Raster

Raster_Object_Information:

Raster_Object_Type: Grid Cell

Row_Count: 3900

Column_Count: 5142

Vertical_Count: 1

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Map_Projection:

Map_Projection_Name: Lambert Conformal Conic

Lambert_Conformal_Conic:

Standard_Parallel: 33.0

Standard_Parallel: 45.0

Longitude_of_Central_Meridian: -117.0

Latitude_of_Projection_Origin: 0.0

False_Easting: 0.0

False_Northing: 0.0

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: row and column

Coordinate_Representation:

Abscissa_Resolution: 100.000000

Ordinate_Resolution: 100.000000

Planar_Distance_Units: meters

Geodetic_Model:

Horizontal_Datum_Name: North American Datum 1927

Ellipsoid_Name: Clarke 1866

Semi-major_Axis: 6,378,206.4

Denominator_of_Flattening_Ratio: 294.98

Entity_and_Attribute_Information:

Detailed_Description:

Entity_Type:

Entity_Type_Label: epi

Entity_Type_Definition:

Epithermal Au-Ag Metallic Mineral-Resource Assessment Tract - ESRI value attribute table. The first two fields of this table consist of value and count, which are standard ESRI grid attributes. The remaining fields were appended to the value attribute table and contain (1) the presence or absence of a given predictor pattern (all fields taken collectively represent a specific unique overlap condition among the predictor patterns), (2) WofE and WLR statistics for each unique overlap condition (which is appended from the file wofe.dbf, a table generated by Arc-Sdm), and (3) the categorical mineral-resource assessment tract rank, which is detailed in the attribute "Tract".

Entity_Type_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., in review, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute:

Attribute_Label: VALUE

Attribute_Definition: Internal feature number.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0

Range_Domain_Maximum: 20

Attribute_Units_of_Measure: none

Attribute_Measurement_Resolution: 1

Attribute:

Attribute_Label: COUNT

Attribute_Definition: The count of grid cells with a particular value.

Attribute_Definition_Source: <http://www.esri.com/library/glossary/t_z.html#V>

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 10

Range_Domain_Maximum: 9922800

Attribute_Units_of_Measure: none

Attribute_Measurement_Resolution: 1

Attribute:

Attribute_Label: ASFREQ

Attribute_Definition:

Presence or absence of predictor pattern asfreq Arsenic anomaly, Asfrequency, representing NURE As concentration (partial digestion) that was processed in the frequency domain.

Attribute_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 0

Enumerated_Domain_Value_Definition: predictor pattern absent

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 1

Enumerated_Domain_Value_Definition: predictor pattern present

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute:

Attribute_Label: EPILITH

Attribute_Definition:

Presence or absence of predictor pattern epilith - Epithermal-lithologic units. The 101 geologic map units were reclassified to five, expert-ranked lithologic host units for epithermal deposits and occurrences. See Wallace and others (2004) for details on how and why the units were reclassified.

Attribute_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: -99

Enumerated_Domain_Value_Definition: predictor pattern missing

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 0

Enumerated_Domain_Value_Definition: predictor pattern absent

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 1

Enumerated_Domain_Value_Definition:

predictor pattern present (evidence map class 1; expertly ranked as "permissive, Jungo", meaning permissive with respect to the Jungo lithotectonic terrane of central, northwestern Nevada

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 2

Enumerated_Domain_Value_Definition:

predictor pattern present (evidence map class 2; expertly ranked as "permissive, medium")

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 3

Enumerated_Domain_Value_Definition:

predictor pattern present (evidence map class 3; expertly ranked as "prospective, high")

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute:

Attribute_Label: MAGTRRN

Attribute_Definition:

Presence or absence of predictor pattern magtrrn - Magnetic terranes, reflecting regions of similar anomaly features or geophysical fabric.

Attribute_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: -99

Enumerated_Domain_Value_Definition: predictor pattern missing

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 0

Enumerated_Domain_Value_Definition: predictor pattern absent

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: 1

Enumerated_Domain_Value_Definition: predictor pattern present

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute:

Attribute_Label: AREA_SQM

Attribute_Definition:

Area in square meters of the unique condition overlap, calculated by Arc-SDM.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00

Range_Domain_Maximum: 89104670000.00

Attribute_Units_of_Measure: meters square

Attribute_Measurement_Resolution: 1

Attribute:

Attribute_Label: TRNGPOINTS

Attribute_Definition:

Number of training sites that fall within the unique condition overlap.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0

Range_Domain_Maximum: 32

Attribute_Units_of_Measure: count

Attribute_Measurement_Resolution: 1

Attribute:

Attribute_Label: POST_PROB

Attribute_Definition:

Posterior probability. The probability that a unit cell (1 km for this study) contains a training site. Due to conditional dependency problems, this probability it highly inflated.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.19899036

Attribute_Units_of_Measure: Probability [0,1]

Attribute:

Attribute_Label: PSTPRBNRM

Attribute_Definition:

Normalized posterior probability. The posterior probability re-scaled so that the overall measure of conditional independence is satisfied. Re-scaling is done by multiplying by Training Site / Sum of (area * probaiblity), where the summation is over all unique conditions.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.17757539

Attribute_Units_of_Measure: Probability [0,1]

Attribute:

Attribute_Label: POST_LOGIT

Attribute_Definition:

Posterior logit. The sum of weights from each evidence map added to the prior logit.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: -8.85611661

Range_Domain_Maximum: 0.00000000

Attribute_Units_of_Measure: Logits

Attribute:

Attribute_Label: SUM_WEIGHT

Attribute_Definition: The sum of the weights (W+ and W-) for each evidence map.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: -1.52860000

Range_Domain_Maximum: 5.93490000

Attribute_Units_of_Measure: none

Attribute:

Attribute_Label: UNCERTAINT

Attribute_Definition:

Uncertainty. The standard deviation due to the calculation of weights.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.08741655

Attribute_Units_of_Measure: none

Attribute:

Attribute_Label: MSNG_DATA

Attribute_Definition: Missing data. The standard deviation due to missing data.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.00114926

Attribute_Units_of_Measure: none

Attribute:

Attribute_Label: TOT_UNCRTY

Attribute_Definition:

Total uncertainty. The combined standard deviation due to weights and missing data.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.08741655

Attribute_Units_of_Measure: none

Attribute:

Attribute_Label: LRPOSTPROB

Attribute_Definition: Posterior probability calculated using logistic regression.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.06964000

Attribute_Units_of_Measure: Probability [0,1]

Attribute:

Attribute_Label: LRTVALUE

Attribute_Definition:

Weighted logistic regression posterior probability Studentized-T value. This is the WLR posterior probability divided by its standard deviation.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 10.20019000

Attribute_Units_of_Measure: none

Attribute_Value_Accuracy_Information:

Attribute_Value_Accuracy:

An Lrtvalue greater than 2 indicates approximately 97% confidence that the reported logistic-regression posterior probability is not zero.

Attribute:

Attribute_Label: LR_STD_DEV

Attribute_Definition: Logistic regression posterior probability standard deviation.

Attribute_Definition_Source:

Attribute_Domain_Values:

Range_Domain:

Range_Domain_Minimum: 0.00000000

Range_Domain_Maximum: 0.02618000

Attribute_Units_of_Measure: none

Attribute:

Attribute_Label: TRACT

Attribute_Definition:

Mineral-resource assessment tract. Descriptive class name assigned to the WLR posterior probability by the assessment team.

Attribute_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: Non-Permissive

Enumerated_Domain_Value_Definition:

Non-permissive tracts are those areas judged to have a negligible probability of containing a mineral deposit or occurrence, or that are covered by more than 1 km of Cenozoic rocks or alluvial sediments. As described by Singer (1993), these areas have roughly less than a 1 in 100,000 to 1,000,000 chance of containing undiscovered deposits of the type being assessed. The non-permissive designation is based on absence of geologic environments and (or) known mineralizing processes that are understood to be necessary for formation of the type of mineral occurrence or deposit under consideration. Non-permissive tracts delineated in the HRB mineral-resource assessment are similar to those used and defined in the Nevada assessment (Singer, 1996), differing only in the depth-to-basement maps used to define areas of thick Cenozoic volcanic or sedimentary deposits.

Note: In the attribute table associated with this ESRI grid, non-permissive mineral-resource assessment tracts have blank attributes, as these tracts were delineated by knowledge-driven means, not by data-driven WofE and WLR analysis and modeling techniques.

For additional information, see Wallace and others (2004).

Singer, D.A., 1993, Basic concepts in the three-part quantitative assessments of undiscovered mineral resources: Nonrenewable Resources, v. 2, p. 69-81.

Singer, D.A., ed., 1996, An analysis of Nevada's metal-bearing mineral resources: Nevada Bureau of Mines and Geology Open-file Report 96-2, <http://www.nbmg.unr.edu/dox/ofr962/cover.pdf>.

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: Permissive

Enumerated_Domain_Value_Definition:

Permissive areas, approximately corresponding to a rank level of "low favorability" for undiscovered deposits. Permissive tracts delineated in the HRB mineral-resource assessment are similar to those used and defined in the Nevada assessment (Singer, 1996), differing only in the depth-to-basement maps used to define areas of thick Cenozoic volcanic or sedimentary deposits. Permissive tracts are regions that might contain a mineralized system within a depth of 1 km beneath the surface. These tracts may or may not contain mineral deposits or occurrences, and their designation as permissive does not necessarily imply that any resources, if they are present, will be discovered. This designation is based on the presence of one or more geologic factors that the assessment team considered to be important, some of which may be widespread, and that are known to have been involved with the formation of mineral deposits and occurrences elsewhere in the assessment area. By definition, permissive tracts include favorable and prospective areas and thus are considered to contain virtually all undiscovered deposits of a certain type or group.

Note: In the attribute table associated with the ESRI grid, permissive mineral-resource assessment tracts that have blank attributes are outside the extent of geochemistry evidence map coverage and were delineated by knowledge-driven means. Tracts that have values are within the extent of geochemistry evidence map coverage, where data-driven WofE and WLR analysis and modeling was carried out to delineate the favorable and prospective tracts.

For additional information, see Wallace and others (2004).

Singer, D.A., ed., 1996, An analysis of Nevada's metal-bearing mineral resources: Nevada Bureau of Mines and Geology Open-file Report 96-2, <http://www.nbmg.unr.edu/dox/ofr962/cover.pdf>.

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: Favorable

Enumerated_Domain_Value_Definition:

Favorable areas, approximately corresponding to a rank level of "moderate favorability" for undiscovered deposits. The favorable mineral-resource assessment tract was generated using WofE and WLR analysis and modeling techniques, but limited in extent to areas where NURE geochemistry evidence maps were available (this area covers most of northern Nevada, except for the southern-most, southwestern, and eastern-most extent of the study area; for additional details, see Wallace, 2004, Chapters 2 and 5). The HRB assessment team created and (or) selected datasets for mineral-resource analysis and modeling that represent a number of important regional processes believed to be related to formation of mineral deposits and occurrences. The relative rankings of the tracts (permissive, favorable, and prospective) reflect the combination of these datasets for each type of mineralizing system assessed. For a given combination, the contribution of each evidence map to the level of favorability is derived mathematically from the spatial association between the distribution pattern of the known mineral occurrences and deposits and the geoscientific phenomena represented in the maps. For example, if the mathematical calculations determine that mineral occurrences and deposits have a greater spatial association with geochemical anomalies than with a geophysical anomalies, then the geochemical anomalies contribute more to the level of favorability than do the geophysical anomalies. The implication is that certain evidence map combinations represent a greater likelihood that mineralizing processes took place in a given area than other combinations. Thus, a prospective area (tract) represents the optimum combination of the evidence maps, whereas a favorable area (tract) consists of a somewhat less optimum, but still relatively significant, combination. Combining the evidence maps and determining the threshold between prospective and favorable also is done mathematically. For the volcanic rock-hosted Au-Ag assessment tract map, the favorable-prospective rank boundary is defined by plotting WLR favorability against cumulative assessment area and identifying the most prominent break-point in the curve above the prior favorability (prior probability = 0.0007; favorable-prospective posterior probability boundary = 0.002; for details, see Wallace and others, 2004, Chapters 2 and 9). The shape and distribution of the prospective and favorable tracts is determined by the overlap intersections among the patterns of geoscientific phenomena represented in each of the evidence maps.

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Enumerated_Domain:

Enumerated_Domain_Value: Prospective

Enumerated_Domain_Value_Definition:

Prospective areas, approximately corresponding to a rank level of "high favorability" for undiscovered deposits. The prospective mineral-resource assessment tract was generated using WofE and WLR analysis and modeling techniques, but limited in extent to areas where NURE geochemistry evidence maps were available (this area covers most of northern Nevada, except for the southern-most, southwestern, and eastern-most extent of the study area; for additional details, see Wallace, 2004, Chapters 2 and 5). The HRB assessment team created and (or) selected datasets for mineral-resource analysis and modeling that represent a number of important regional processes believed to be related to formation of mineral deposits and occurrences. The relative rankings of the tracts (permissive, favorable, and prospective) reflect the combination of these datasets for each type of mineralizing system assessed. For a given combination, the contribution of each evidence map to the level of favorability is derived mathematically from the spatial association between the distribution pattern of the known mineral occurrences and deposits and the geoscientific phenomena represented in the evidence maps. For example, if the mathematical calculations determine that mineral occurrences and deposits have a greater spatial association with geochemical anomalies than with a geophysical anomalies, then the geochemical anomalies contribute more to the level of favorability than do the geophysical anomalies. The implication is that certain evidence map combinations represent a greater likelihood that mineralizing processes took place in a given area than other combinations. Thus, a prospective area (tract) represents the optimum combination of the evidence maps, whereas a favorable area (tract) consists of a somewhat less optimum, but still relatively significant, combination. Combining the evidence maps and determining the threshold between prospective and favorable also is done mathematically. For the volcanic rock-hosted Au-Ag assessment tract map, the favorable-prospective rank boundary is defined by plotting WLR favorability against cumulative assessment area and identifying the most prominent break-point in the curve above the prior favorability (prior probability = 0.0007; favorable-prospective posterior probability boundary = 0.002; for details, see Wallace and others, 2004, Chapters 2 and 9). The shape and distribution of the prospective and favorable tracts is determined by the overlap intersections among the patterns of geoscientific phenomena represented in each of the evidence maps.

Enumerated_Domain_Value_Definition_Source:

Mihalasky, M.J.,and Wallace, A.R., 2004, CHAPTER 2. Assessment Concepts and Methodology, in, Wallace, A.R., Ludington, S., Mihalasky, M.J., Peters, S.G., Theodore, T.G., Ponce, D.A., John, D.A., and Berger, B.R., 2004, Assessment of metallic mineral resources in the Humboldt River Basin, Northern Nevada, with a section on PGE potential of the Humboldt mafic complex by M.L. Zientek, G.B. Sidder, and R.A. Zierenberg: U.S. Geological Survey Bulletin B-2218, CD-ROM.

Overview_Description:

Entity_and_Attribute_Overview:

The following is a list of the evidence maps used to create the epithermal Au-Ag favorable and prospective mineral-resource assessment tracts:

asfreq - Arsenic anomaly, As-frequency, representing NURE As concentration (partial digestion) that was processed in the frequency domain.

epilith - Epithermal-lithologic units. The 101 geologic map units were reclassified to five, expert-ranked lithologic host units for epithermal deposits and occurrences.

magtrrn - Magnetic terranes, reflecting regions of similar anomaly features or geophysical fabric.

Entity_and_Attribute_Detail_Citation:

For addition information on the evidence maps listed in "Entity_and_Attribute_Overview", see the "Lineage / Source_Information / Source_Contribution" section of the metadata above.

Source data and processing of the datasets used for modeling are detailed in:

Distribution_Information:

Distributor:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: U.S. Geological Survey

Contact_Address:

Address_Type: mailing address

Address: USGS Information Services (Open-File Report Sales)

Address: Box 25286

Address: Denver Federal Center

City: Denver

State_or_Province: CO

Postal_Code: 80225

Country: USA

Contact_Voice_Telephone: 303-202-4700

Contact_Facsimile_Telephone: 303-202-4188

Contact_Electronic_Mail_Address: custserv@usgs.gov

Hours_of_Service: 8:00 AM to 4:00 PM (Mountain Time)

Contact_Instructions:

This report is available in an electronic format at the following URL = <http://pubs.usgs.gov/of/2004/1245>

Resource_Description:

Downloadable online data and CD-ROM as <http://pubs.usgs.gov/of/2004/1245>

Distribution_Liability:

Although all data and software have been used by the U.S. Geological Survey (USGS), no warranty, expressed or implied, is made by the USGS as to the accuracy of the data and related materials and (or) the functioning of the software. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data, software, or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Format_Name: Compressed ESRI Grid

Format_Version_Date: 2004

Format_Specification: ESRI Grid

File_Decompression_Technique: ESRI Interchange File Format

Digital_Transfer_Option:

Online_Option:

Computer_Contact_Information:

Network_Address:

Network_Resource_Name: <http://pubs.usgs.gov/of/2004/1245>

Offline_Option:

Offline_Media: CD-ROM

Recording_Format: ISO 9660 Level 2 standard

Compatibility_Information:

All platform compatibility, Intel Pentium or equivalent processor.

Fees: Subject to change

Custom_Order_Process:

CD-ROM of Open-File Report 2004-1245 can be purchased through the USGS Information Services (Open-File Report Sales).

Technical_Prerequisites:

The CD-ROM was produced in accordance with the ISO 9660 Level 2 standard. The data can be accessed using any software capable of reading an ESRI grid (raster) or image file.

Metadata_Reference_Information:

Metadata_Date: 20040518

Metadata_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Author: Mark J. Mihalasky; Contact: Alan R. Wallace

Contact_Organization: U. S. Geological Survey

Contact_Position: Research Geologist

Contact_Address:

Address_Type: mailing address

Address: C/O Mackay School of Mines

Address: MS-176 University of Nevada

City: Reno

State_or_Province: NV

Postal_Code: 89557

Country: USA

Contact_Voice_Telephone: 1-775-784-5789

Contact_Facsimile_Telephone: 1-775-784-5079

Contact_Electronic_Mail_Address: alan@usgs.gov

Contact_Instructions:

The originator of the dataset, Mark Mihalasky, is no longer with U. S. Geological Survey. Contact Alan Wallace (alan@usgs.gov) or Mark Mihalasky at mihalasky@hotmail.com.

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001-1998

Metadata_Time_Convention: local time

Metadata_Access_Constraints: None

Metadata_Use_Constraints: None

Metadata_Extensions:

Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>

Profile_Name: ESRI Metadata Profile

Generated by mp version 2.7.33 on Tue May 18 10:58:43 2004
updated October 2, 2006 (mfd)