Automated Lineament Extraction applied to high-resolution imagery Worldview-3 and LiDAR data for pegmatite mineral exploration

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Santos, D (Author) Other; Mendes, A (Author) Other; Azzalini, A (Author) Other; Cardoso Fernandes, J (Author) FCUP; Alexandre Lima (Author) FCUP; Ana Teodoro (Author) FCUP

Conference proceedings International

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

Earth Resources and Environmental Remote Sensing/GIS Applications XIV 2023

Amsterdam, 2023

Indexing

Scopus - 2 Citations

Other information

Authenticus ID: P-00Z-6NZ

DOI: 10.1117/12.2679367

Abstract (EN): Lineament extraction is a commonly used technique in mineral exploration to identify geological structures such as fault scarps, joints, and folds. However, the accuracy of this technique can be limited by factors such as the low spatial resolution of the data. This study aims to address these limitations by exploring the potential of high spatial resolution data for extracting linear structures in Tysfjord, northern Norway. Two types of high-resolution data were utilized for lineament extraction: (i) WorldView-3 (WV3) satellite orbital imagery with a ground sample distance (GSD) of 2 meters, and (ii) Light Detection And Ranging (LiDAR) point cloud data, with a GSD of 1 meter. The LiDAR point cloud was utilized to generate a Digital Terrain Model (DTM), and automated lineament extraction was performed on both WV3 and LiDAR data using the lineament algorithm (LINE) available in PCI Geomatics software. A comparison was conducted using Sentinel 2 images to analyze the impact of utilizing high-resolution images on the final results. The outcomes illustrate that high-resolution images hold substantial potential for extracting lineaments and can aid in identifying mineral deposits and neotectonic activity. In the future, these findings could be integrated with other remote sensing methods to enhance the capabilities of remote sensing for mineral exploration. © 2023 SPIE. All rights reserved.

Language: English

Type (Professor's evaluation): Scientific