1_Readme

Title: Assessment method for epithermal gold deposits in northeast Washington 
State using weights-of-evidence GIS modeling

By D.E. Boleneus, G.L. Raines, J.D. Causey, A.A. Bookstrom, T.P. Frost, 
and P.C. Hyndman

Open-File Report 01-501

Manuscript approved December 31, 2001

Prepared in cooperation with the USDA Forest Service, Pacific Northwest Region, 
Okanogan and Colville National Forests

This report is preliminary and has not been reviewed for conformity with U.S. 
Geological Survey editorial standards.  Any use of trade, product, or firm names 
is for descriptive purposes only and does not imply endorsement by the U.S. 
Government. Although these programs have been used by the US Geological Survey, 
no warranty, expressed or implied, is made by the USGS as to the accuracy and 
functioning of the programs and related program material, nor shall the fact of 
distribution constitute any such warranty, and no responsibility is assumed by 
the USGS in connection therewith.

U.S. DEPARTMENT OF THE INTERIOR
U.S. GEOLOGICAL SURVEY
 
Contents:
Abstract
Introduction
Weights of Evidence
Training sites     
Analysis of geologic patterns for epithermal model
Measures of mineral activity
Assessment of future mineral industry activity
Conclusions
References Cited
Appendix
  I.  Databases
  II.  Glossary

12 Figures
9 Tables

Digital data and files:

Text and data from this report can be found on the internet at the USGS website:   
http://pubs.usgs.gov/of/2001/of01-501/

Text and other files accompanying this report are listed below: 

[txt -- ascii text document, PDF -- Adobe Acrobat Portable Document Format, doc 
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Name of file            Name of folder                Type     Description     

1_readme.txt             root                         txt     General 
                                                                 information     
of01-501                 root                         doc     Report text 
                                                                 and tables 
fig1, fig4ab, fig6, fig9, fig10, fig12     jpg        JPEG
Figures 1, 4, 6, 9, 10, 12      

fig1, fig4ab, fig6, fig9, fig10, fig12     pdf        PDF
Figures 1, 4, 6, 9, 10, 12  (600 dpi)     

JPEG and PDF files--These files are provided in event that user has need for the 
figures in different formats.

ArcView shapefiles may be obtained from the author on an informal basis, but are 
not a part of this publication.

ABSTRACT--The weights-of-evidence analysis, a quantitative mineral resource 
mapping tool, is used to delineate favorable  areas for epithermal gold deposits 
and to predict future exploration activity of the mineral industry for similar 
deposits  in a four-county area (222 km x 277 km), including the Okanogan and 
Colville National Forests of northeastern Washington.  Modeling is applied in 
six steps: (1) building a spatial digital database, (2) extracting predictive 
evidence for a  particular deposit, based on an exploration model, (3) 
calculating relative weights for each predictive map, (4) combining  the 
geologic evidence maps to predict the location of undiscovered mineral resources 
and (5) measuring the intensity of  recent exploration activity by use of mining 
claims on federal lands, and (6) combining mineral resource and exploration  
activity into an assessment model of future mining activity. 

The analysis is accomplished on a personal computer using ArcView GIS platform 
with Spatial Analyst and Weights-of-Evidence  software. In accord with the 
descriptive model for epithermal gold deposits, digital geologic evidential 
themes assembled include lithologic map units, thrust faults, normal faults, and 
igneous dikes. Similarly, geochemical evidential themes include placer gold 
deposits and gold and silver analyses from stream sediment (silt) samples from 
National Forest lands.  Fifty mines, prospects, or occurrences of epithermal 
gold deposits, the training set, define the appropriate  areally-associated 
terrane. The areal (or spatial) correlation of each evidential theme with the 
training set yield  predictor theme maps for lithology, placer sites and normal 
faults. The weights-of-evidence analysis disqualified the thrust fault, dike, 
and gold and silver silt analyses evidential themes because they lacked spatial 
correlation with  the training set. The decision to accept or reject evidential 
themes as predictors is assisted by considering probabilistic  data consisting 
of weights and contrast values calculated for themes according to areal 
correlation with the training sites. Predictor themes having acceptable weights 
and contrast values are combined into a preliminary model to predict the  
locations of undiscovered epithermal gold deposits. This model facilitates 
ranking of tracts as non-permissive, permissive  or favorable categories based 
on exclusionary, passive, and active criteria through evaluation of 
probabilistic data  provided by interaction of predictor themes. The method is 
very similar to the visual inspection method of drawing conclusions from 
anomalies on a manually overlain system of maps. This method serves as a model 
for future mineral  assessment procedures because of its objective nature.

To develop a model to predict future exploration activity, the locations of lode 
mining claims were summarized for 1980, 1985, 1990, and 1996. Land parcels 
containing historic claims were identified either as those with mining claims 
present in 1980 or valid claims present in 1985. Current claim parcels were 
identified as those containing valid lode claims in either 1990 or 1996. A 
consistent parcel contains both historic and current claims. 

The epithermal gold and mining claim activity models were combined into an 
assessment (or mineral resource-activity) model to assist in land use decisions 
by providing a prediction of mineral exploration activity on federal land in the 
next decade. Ranks in the assessment model are: (1) no activity, (2) low 
activity, (3) low to moderate activity, (4) moderate  activity and (5) high 
activity.

Primary author current address:
U.S. Bureau of Land Management
email David _Boleneus@blm.gov