Using logistic regression to merge mineral resource databases |
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Authors: | Deborah J Shields Stella W Todd |
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Institution: | (1) Rocky Mountain Research Station, U.S.D.A. Forest Service, 3825 E. Mulberry St., 80524 Fort Collins, Colorado;(2) Management Assistance Corporation of America, Fort Collins, Colorado |
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Abstract: | The purpose of this project was to develop and test a methodology for determining the likelihood that mineral resource location
records from two nationwide mineral resource information databases represent the same site. The long-term goal is to create
a comprehensive database by merging the Mineral Resource Data System (MRDS) of the U.S. Geological Survey, and the Mineral
Availability System/Mineral Industry Location System (MAS/MILS) of the U.S. Bureau of Mines (now part of the Geological Survey).
Part of that process involves linking records for the same site from each database. Match probabilities were estimated using
a logistic regression of mineral resource location attributes, derived from known matched (cross-referenced) and known unmatched
randomly sampled mineral site pairs from within the conterminous United States (n=10,000). Model accuracy was assessed using a randomly sampled test dataset, not used in logistic model development (n=4,000). Probability distributions were similar between the development and test datasets. The overall agreement beyond chance
was good for the test data set
using the kappa statistic. Classification accuracy was 89.6% for known matched site pairs and 84.0% for known unmatched site
pairs based on a probability threshold of 0.50 for a match. Distributions of attributes were similar between the development
and test datasets. This classification method is a viable approach for estimating match probabilities between database records. |
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Keywords: | Mining GIS classification mineral deposit mineral location database |
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