6360902e969ac9388818091800f997a7 land_a2022v11n2p212.pdf c9b18fe39bccd0d3930df0dde4b2f8572300051c land_a2022v11n2p212.pdf 0e55840c17ae3680bf842164541bbeee110b731ce31052037d8a9ca03500fef5 land_a2022v11n2p212.pdf Title: Drone-Based Identification of Erosive Processes in Open-Pit Mining Restored Areas Subject: 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. Keywords: UAS; Unmanned Aerial Systems; mining; restoration; erosion; digital terrain models; GIS tools Author: Joan-Cristian Padró, Johnsson Cardozo, Pau Montero, Roger Ruiz-Carulla, Josep Maria Alcañiz, Dèlia Serra and Vicenç Carabassa Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Sat Jan 29 10:29:05 2022 CET ModDate: Sat Jan 29 10:47:26 2022 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 13 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 4285491 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- JFQOLP+VnURWPalladioL-Bold Type 1 Custom yes yes no 10 0 RAWBBU+URWPalladioL-Bold Type 1 Custom yes yes no 15 0 PJEXHS+URWPalladioL-Roma Type 1 Custom yes yes no 20 0 TPRWVJ+URWPalladioL-Ital Type 1 Custom yes yes no 24 0 KORLVE+VnURWPalladioL Type 1 Custom yes yes no 28 0 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Item: Title: Study Area Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7b69c6ba Item: Title: Unmanned Aerial Vehicle (UAV), Image Sensor and Flight Planning Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Item: Title: Methodology Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Item: Title: Results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Children: Item: Title: Morphometric Analysis and Drainage Network Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Erosion Estimation Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Item: Title: Slopes and Erosion Identification Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Item: Title: Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@50d0686 Item: Title: Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7a3d45bd Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1e7c7811 Info: Title: Drone-Based Identification of Erosive Processes in Open-Pit Mining Restored Areas Author: Joan-Cristian Padró, Johnsson Cardozo, Pau Montero, Roger Ruiz-Carulla, Josep Maria Alcañiz, Dèlia Serra and Vicenç Carabassa Subject: 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. 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