Geomorphological monitoring of erosion on restored slopes through the integration of drones, GIS, and LiDAR
Abstract. Mining is a strategic driver of economic development, yet it generates substantial impacts on landscape structure, soil integrity, and water systems. During ecological restoration, slope erosion remains a critical challenge for ensuring long-term geomorphological stability and ecosystem recovery. This study evaluates erosion dynamics on restored mining slopes by integrating Geographic Information Systems (GIS) and Unmanned Aerial Systems (UAS) for high-resolution terrain monitoring and quantification of soil loss. Research was conducted at the Lázaro quarry (Tarragona, Spain) using a fixed-wing UAS equipped with a multispectral camera to produce detailed orthophotos and Digital Elevation Models (DEMs), which were compared with historical LiDAR data. Height Difference Models (HDMs) and volumetric calculations were applied to quantify erosion and deposition. Statistical assessment included descriptive indicators, error metrics (ME, MAE, RMSE), distribution parameters (median, IQR, skewness), and spatial autocorrelation (Moran’s I). Three modelling approaches were developed and compared: a ridge-derived DEM (DEMp), a filtered DEM (DEMf), and a LiDAR-based DEM (DEMl). Their performance was evaluated in terms of accuracy, spatial resolution, and capacity to represent erosional microtopography. Results indicate that DEMp provides the most reliable volume estimates and best preserves pre-erosion morphology. In contrast, DEMf smooths surface detail, whereas DEMl provides an overview representation due to its lower spatial resolution. Overall, the integration of UAS photogrammetry and geospatial analysis proves effective for monitoring restored slopes, supporting precise erosion quantification and improved environmental management toward long-term landscape stability.