LITHIUM (LI) PEGMATITE MAPPING USING ARTIFICIAL NEURAL NETWORKS (ANNS): PRELIMINARY RESULTS

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Cardoso Fernandes, J (Author) Other; Ana Teodoro (Author) FCUP; Alexandre Lima (Author) FCUP; Roda Robles, E (Author) Other

Conference proceedings International

Title: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium

Pages: 557-560

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00T-FF3

DOI: 10.1109/igarss39084.2020.9323852

Abstract (EN): Satellite-based mineral exploration will be increasingly relevant in the future to achieve more conscious exploration models. Therefore, new applications to high-demand mineral commodities such as lithium (Li) are emerging. Previous applications to the study area of Fregeneda (Spain) - Almendra (Portugal) showed a high number of false positives despite their ability to identify Li pegmatites. So, the objective of the present work is to improve the classification results using Artificial Neural Networks (ANNs). For that, the same Sentinel-2A images were used and a three-layer feedforward network was computed using the backpropagation method. The ANN created was able to identify all the open-pit mines exploiting Li pegmatites in the area. However, the high number of Li false positives persisted. Future applications may include Convolutional Neural Networks (CNNs) to improve these results.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4