Multi-temporal LiDAR-based Terrain Anomaly Detection of Karstic Environments in the Asturian Central Massif (Cantabrian Mountains, Northwest Spain)

• Type: Article in International Conference Proceedings Book
• Date: 2024

Authors

Azzalini, A (Author) Other; Cardoso Fernandes, J (Author) FCUP; Carvalho, M (Author) Other; Williams, V (Author) Other; Alexandre Lima (Author) FCUP; Ana Teodoro (Author) FCUP

Conference proceedings International

Title: Proceedings of SPIE - The International Society for Optical Engineering

Final page: 55

Earth Resources and Environmental Remote Sensing/GIS Applications XV 2024

Edinburgh, 16 September 2024 through 19 September 2024

Indexing

Scopus - 1 Citation

Other information

Authenticus ID: P-017-CA8

DOI: 10.1117/12.3031535

Abstract (EN): Light Detection and Ranging (LiDAR) data plays a major role in detecting terrain anomalies related to morphogenetic processes. In this study, a multi-temporal LiDAR analysis was carried out to identify structurally controlled alteration zones related to karstification within carbonate rocks that may be related to Copper-Cobalt-Nickel mineralisation within a study area located in Asturias, Northwest Spain. The style of alteration can cause nivo-karst dolines and niches, which can be accelerated by the annual accumulation and melting of snow on the Aramo Plateau, which forms the core of the study area. Three LiDAR datasets were used to compare terrain alterations during an 11-year period (2012-2023). The first two campaigns were conducted by the Spanish National Geographic Institute (IGN). The third campaign was performed for a geological exploration survey within the scope of the S34I Horizon Europe Project - Secure and Sustainable Supply of Raw Materials for EU Industry. The original point cloud datasets were processed in order to generate a Digital Terrain Model (DTM) with one-meter spatial resolution. A raster math operation was then carried out on the products to detect anomalous height differences, considering the vertical root-mean-square-error (RMSE) of each product. Several height differences were identified, which require validation in the field to check and verify the nature of these anomalous occurrences. In the future, further studies are being developed based on the Copernicus Sentinel-1 mission data, using the Differential Interferometry Synthetic Aperture Radar (DInSAR) technique to detect more subtle subsidence of the terrain. © 2024 SPIE.

Language: English

Type (Professor's evaluation): Scientific