Multi-sensor Assessment of Geological Lineament Detection

Abstract

The advances in remote sensing technologies and geographical information sciences are applicable in various branches of geosciences. The high availability of remote sensing data provides a wide range of spatial and spectral resolutions that can be utilized for lineament mapping purposes, especially in detecting geological linear features in remote areas. The aim of this study is to compare multi-sensors active and passive remote sensing technologies in lineament mapping, based on automatic image processing tools. Landsat 8, Sentinel 1 and Sentinel 2 satellite data will be processed to detect lineaments between the state boundaries of Selangor and Pahang in the Peninsular Malaysia, with reference to the published geological map. In detail, lineaments will be automatically extracted after image enhancement processes. Then, the output will be imported in a geo-graphical information system to further analyze the extracted lineaments. Overall, statistics descriptions, density, and orientations analysis indicate a correlation between the extracted lineaments and the geology of the area. Furthermore, lineaments extracted from Sentinel 1 radar images show the most significant result. Sentinel 1 data indicated about 6396 extracted of lineaments with 2465.93km total length as compared to Sentinel 2 with only 2637 lineaments extracted and total length of 1045.92km. The accuracy assessment of matching lineaments provides the Sentinel 1 as the best sensor compared to both the Sentinel 2 and the Landsat 8, with root mean square errors (RMSE) equal to 1.660, 1.743 and 2.757, respectively. Therefore, both remote sensing technologies and geographical information sciences can be effectively integrated within the field of the structural geology, thus allowing the mapping of lineaments in a more practical, cost and time effective way.