Overcoming Data Gaps in Abandoned Mining Areas Through High-Resolution UAV Surveys

Abandoned mining areas often constitute complex environmental systems, with large volumes of waste materials remaining exposed and poorly documented. In many historical mining districts, the lack of reliable information regarding the amount and spatial distribution of these wastes makes it difficult to properly assess environmental impacts and to define adequate remediation strategies. Recent developments in unmanned aerial vehicle (UAV) technology offer practical solutions to overcome these limitations, particularly in difficult-to-access areas where conventional surveying methods may be limited.

This study presents a UAV-based photogrammetric methodology for the quantitative assessment of mining waste deposits in data-scarce environments, with the primary objective of demonstrating the applicability of high-resolution aerial surveys as a general tool for environmental characterization and decision support. The approach integrates UAV-acquired imagery with photogrammetric processing to generate detailed orthophotos and digital surface models (DSMs), enabling accurate three-dimensional reconstruction and volume estimation of waste materials.

The methodology is applied to an abandoned mining area within the Iberian Pyrite Belt, a region historically affected by intensive sulfide mining and associated environmental impacts, which is used here as a representative case study. High-resolution, georeferenced imagery was acquired using a DJI Phantom 4 RTK UAV and processed to delineate waste accumulation zones, analyze surface morphology, and calculate waste volumes in the absence of detailed archival records.

The results demonstrate that UAV-derived products provide a robust representation of waste deposit geometry, supporting quantitative assessments relevant to environmental risk evaluation and management planning. Beyond volume estimation, the generated datasets provide a valuable spatial baseline for future monitoring of geomorphological changes driven by erosion, instability, or remediation actions.

Overall, the study highlights the potential of UAV-based photogrammetry as a versatile and transferable approach for addressing data limitations in abandoned mining areas and other environmental contexts where legacy waste characterization is required. The proposed framework supports informed decision-making and contributes to more effective environmental management and restoration strategies.