Published in

MDPI, Land, 2(11), p. 212, 2022

DOI: 10.3390/land11020212

Links

Tools

Export citation

Search in Google Scholar

Drone-Based Identification of Erosive Processes in Open-Pit Mining Restored Areas

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

Unmanned Aerial Systems, or drones, are very helpful tools for managing open-pit mining operations and developing ecological restoration activities. This article presents a method for identifying water erosion processes in active quarries by means of drone imagery remote sensing, in the absence of pre-existing imagery or mapping for comparison. A Digital Elevation Model (DEM) with a spatial resolution (SR) >10 cm and an orthophoto with an SR >2.5 cm were generated from images captured with a drone and their subsequent photogrammetric processing. By using Geographical Information Systems tools to process the DEM, a detailed drainage network was obtained, the areas of detected water erosion were separated, and the watersheds in the gullies identified. Subsequently, an estimated DEM before the erosive processes was reconstructed by interpolating the gully ridges; this DEM serves as a reference for the relief before the erosion. To calculate the volume of eroded material, the DEM of Differences was calculated, which estimates the volume difference between the previously estimated DEM and the current DEM. Additionally, we calculated the material necessary for the geomorphological adaptation of the quarry and the slope map, which are two valuable factors closely related to the monitoring of erosive processes. The results obtained allowed us to identify the erosion factors quickly and accurately in this type of mining. In the case of water-filled quarries, it would be important to characterize the subsurface relief. Essentially, the presented method can be applied with affordable and non-invasive materials to create digital grid maps at 10 cm resolution, obtaining data ready for 3D metrics, being a very practical landscape modelling tool for characterizing the restoration evolution of open-pit mining spaces.