Tandem-X satellite data application to four-dimensional of copper mineralization

Abstract

Geological mining detections and identifications in synthetic aperture radar (SAR) images are required standard procedures and accurate algorithms. In fact, the main disadvantage of SAR images is speckle noises. The speckles do not allow any accurate retrieving information from SAR data. The main objective of this work is to design an intelligent system based on Particle Swarm Optimization to detect automatically the four-dimensional of copper mineralization using TanDEM-X satellite data. In this regard, optimization algorithm of Particle Swarm is used with the 4-D phase unwrapping of TanDEM-X satellite data. The study shows that the Particle Swarm Optimization algorithm is used to optimize the 4-D reconstruction of copper mineralization within 7 hours and post 2000 iterations with RMSE of 0.23. The results show that the 4-D of copper mineralization improved morphological feature detection such as the depth of a copper mine and surrounding infrastructures. In conclusion, the integration of PSO with the 4-D phase unwrapping of TanDEM-X satellite data are an excellent promise approach for 4-D reconstruction of copper mineralization.