Segmentation and classification algorithms applied to sentinel-2A images for geological mapping: case of the Al Glo'a sheet (1/50000), Morocco

Abstract

The multispectral image, of Landsat 7 and 8; Aster and Sentinel-2A, has good results in lithological, structural, hydrothermal and mineralogical alteration mapping. Segmentation and image classification are two complementary steps as they are allowed the most important operations in the field of image processing. In this sense, this work aims at evaluating the potential of segmentation and classification algorithms for the generation of surface geological maps, hydrothermal alterations and lineaments. Given the good resolution of the Sentinel 2A (10m), the three images, (11/12; 11/2; 11/8), 12.8.2, main component 1, 2 and 3 (11.12.2), processed by five algorithms (K-means, isodata, watershed, efficient graph-based image segmentation, thresholding) for geological mapping and then mining exploration. The study displayed that 1) Watershed algorithm can be used for topographic and hydraulic studies, it can be very useful in the preparation phase of geological and mining infrastructures; 2) threshold segmentation does not give good results in terms of geological discrimination since it divides each image into two parts; 3) the same thing for the effective thresholding and segmentation of graph-based images; 4) The Isodata and K-means algorithms show good geological discrimination.