11 Geospatial Modeling and Management of our Minerals and other Natural Resources: New Developments and Interdisciplinary Applications

Wednesday, 9 June 2010
8:00 AM - 2:45 PM
Interlocken D

SPATIAL MODELING OF CONSTRUCTION AGGREGATE RESOURCES AND PRODUCTION FOR LAND MANAGEMENT AND PLANNING

Paper number: 11-2
Program: Special Sessions
Time: 8:15 AM – 8:40 AM

Authors

Abstract

Aggregate, consisting of crushed stone, sand, and gravel, is used extensively in construction. Suppliers of aggregate tend to be located near transportation corridors in the urban and developing areas where aggregate is dominantly used because transportation costs to move aggregate from the mine site to point of use is expensive. Transportation costs are often the largest fraction of the cost of aggregate to the user. The increasing demand for construction aggregate and the difficulty of developing and permitting new sites of production that meet aggregate quality standards requires that aggregate must be supplied from sources yet to be developed or delineated in many areas. Site development and permitting for aggregate production is difficult because of high land costs, public opposition to quarry development in many areas, and because many government agency land management plans and zoning actions fail to anticipate future construction aggregate demand patterns that integrate the aggregate quality, transportation, and socioeconomic factors that define the economic viability of the industry. A spatial model has been developed to forecast areas most suitable for production of construction aggregate based on regional geology, transportation, population, and socioeconomic factors (Robinson and Larkins, 2007). Modeling examples applied to the development of crushed stone aggregate quarries in New England and the Carolinas will be presented. The results of these regional models can identify areas for more detailed site evaluation. In addition, as transportation or population features change because of actual, anticipated, or planned development, the models can be updated easily to reflect these changes.

Robinson, G.R., Jr., and Larkins, P.M., 2007, Probabilistic Prediction Models for Aggregate Quarry Siting: Natural Resources Research, v. 16, no. 2, June 2007, p. 135-146