RT Journal Article
T1 Application of Spatial Data Mining to national mines inventories for exploration and land planning of high place-value mineral resources. The case of aggregates in Spain
A1 López-Acevedo Cornejo, María Victoria
A1 Escavy Fernández, José Ignacio
A1 Herrero Fernández, María Josefa
AB Countries' mine inventories usually include information related to exploited rock type or mineral, amount of resources, owner, location, mining rights associated, etc. All this information is a vast dataset that in the last couple of decades has been included in digital cartography in official websites, some of them freely available. This information is usually exploited as individual registers classified by substance, location, etc., but when analyzed as a whole and combined with other economic, social, and environmental variables, valuable information can be obtained. If the variable time is included in the study, these databases can reveal the evolution of mining activity in recent decades.This study analyzes the distribution of aggregates quarries in Spain, as a case study, relating their location to different socio-geographical features such as urban areas, environmentally protected areas, or population density, by means of Spatial Data Mining (SDM) tools. Aggregates are used as construction materials and are the largest non-energy extractive industry, being the second most consumed product by human beings after water. Due to the low unit value and high volume of consumption, aggregates are considered a high place-value commodity. By combining the information of aggregates in the Spanish mines inventory with geological, social, demographic, environmental, and administrative information, and using SDM techniques, relevant conclusions can be obtained such as the delineation of areas in the land use planning to be dedicated to aggregates exploitation, or the identification of priority zones for exploration for mining companies. This information could serve policy makers and land use planners in making data-driven decisions and mining companies in determining areas with the highest profit potential to develop their operations.
PB Elsevier
SN 0301-4207
YR 2025
FD 2025-12
LK https://hdl.handle.net/20.500.14352/124508
UL https://hdl.handle.net/20.500.14352/124508
LA eng
NO López-Acevedo, F.J., et al. «Application of Spatial Data Mining to National Mines Inventories for Exploration and Land Planning of High Place-Value Mineral Resources. The Case of Aggregates in Spain». Resources Policy, vol. 79, diciembre de 2022, p. 103096. DOI.org (Crossref), https://doi.org/10.1016/j.resourpol.2022.103096.
NO Fundacion Agustín de Betancourt
NO Fundacion General U.C.M.
DS Docta Complutense
RD 18 mar 2026