SPATIOTEMPORAL ANALYSIS OF LODE MINING ACTIVITY AROUND THE MCDERMITT CALDERA, NORTHERN NEVADA, USA

In the U.S., resource managers and agencies involved with planning for future federal-land needs are required to complete an assessment of, and forecast for, future land use every ten years. Predicting mining activities on federal lands is difficult as current regulations do not require disclosure of exploration results. In these cases, historic mining claims may serve as a proxy for determining where future mining-related activities may occur. The utility of Space Time Cube and related analyses is investigated to evaluate and characterize mining claim activities from 1976 to 2010 and 2016 around the McDermitt Caldera. Additional analyses of the Space Time Cube (i.e., Trend, Emerging Hot Spot (EHSA), Hot Spot (HSA), and Cluster and Outlier Analyses (COA)) provide extra insights into the data and may aid in predicting future mining-claim activities. To test how well the EHSA, HSA, COA, and Trend tools detect change patterns in the data, the analyses were conducted at various levels of granularity (full dataset, halved dataset, and trisected dataset).

The most significant advantage of using a Space Time Cube is the ability to visualize and understand the data in terms of spatiotemporal patterns. In general, Trend, EHSA, and HSA adequately detected the major trends in the data. The results of the trend analyses revealed that the full dataset captured big-picture trends and the halved datasets revealed more detail. Trisecting the data and using the trend analyses proved useful for approximating and thereby predicting future mining activities. Unlike the trend analysis, the EHSA was most useful when the data were trisected. HSA was useful in capturing historic trends, but a poor predictor of future mining claim activity. COA provided little information about past or future trends in the mining claim data.