One of the key missions of the USGS Mineral Resources Program is the collection and dissemination of mineral resources information. This information is used by the USGS, other government agencies (State and Federal), private industry and the general public. An accurate, up-to-date mineral deposit database utilizing current geospatial technologies is needed to meet the needs of USGS research, state and federal land management agencies, private industry, and the general public.
In the 1960's, the USGS and the U.S. Bureau of Mines developed national-scale mine and mineral deposit databases. After the Bureau of Mine's 1996 closure, the USGS acquired custody of their Minerals Availability System (MAS) and Minerals Industry Location System (MILS) databases. In 2000, the MAS/MILS was merged with the USGS Mineral Resource Data System (MRDS) to form a single database. Much of the data initially captured in the Mineral Resource Data System was recorded prior to the development and widespread use of modern geospatial technologies. Additionally, differing data entry procedures of both Bureau of Mines and USGS resulted in different outcomes. Due to these issues, it was decided that the mineral resources database of the U.S. needed to be modernized.
Our goals are to update the national mineral deposit database with accurate and current information on mineral occurrences and mines in a format readily usable for geospatial analysis, in order to meet the needs of potential users of mineral resources information. The geospatial database will include information on geology, production, resources, history, and development status. The initial focus has been on the western states, with plans to eventually collect data for all of the U.S.
The project consists of two core activities proceeding in parallel: 1) database design and 2) data acquisition.
Design of the mineral deposit database and selection of the database platform was a major decision so considerable time was devoted to this task. A significant part of the design process consisted of determining the needs of various users so that the content and structure of the database will meet those needs. It was eventually decided that the “database” would be ArcGIS, although the data would be published in a variety of formats in accordance with USGS publication guidelines.
The data itself consists of three feature groups which represent the major kinds of features comprising mineral resources. These are:
The geospatial nature of the database means that in addition to the classical point locations of features their areal extent can also be captures and incorporated into the database.
In the early stages of our work, we focused on the development of procedures and workflows to capture accurate locations and names of mine features. Our concept was to focus on one data type and to develop data structures, and collection procedures that would be applicable to other data types. In order to ensure we collected data in a consistent and reproducible way, we developed extensive QA/QC protocol and concise data capture procedures. During the data capture process the majority of the data is captured in flat file form which can then be imported into the GIS database. In the mine feature data capture process we focused on acquiring three types of data:
The procedures developed in this process were then applied to the other data feature groups.
Fernette, G.L., Bellora, J.D., Bartels, M. P., Gallegos, S.M., Jordan, J.K., Tureck, K.R., and Chapman, A.L., 2016, USMIN Mineral Resource Data for the U.S. Geological Survey Sagebrush Mineral-Resource Assessment Project: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7J964GW.
Fernette, G.L., Horton, J.D., King, Zachary, San Juan, C.A., and Schweitzer, P.N., 2016, Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the Western United States: U.S. Geological Survey data release, http://dx.doi.org/10.5066/F7JD4TWT.
Rockwell, B.W., 2013, Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data: U.S. Geological Survey Scientific Investigations Map 3256, 8 p. pamphlet, 1 map sheet, scale 1:150,000, http://pubs.usgs.gov/sim/3256/.
Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, 25 p. pamphlet, 1 map sheet, scale 1:325,000, http://pubs.usgs.gov/sim/3252/.
Central Mineral and Environmental Resources Science Center