Abstract
Lineament mapping, which is an important part of any structural geological investigation, is made more efficient and easier by the availability of optical as well as radar remote sensing data, such as Landsat and Sentinel with medium and high spatial resolutions. However, the results from these multi-resolution data vary due to their difference in spatial resolution and sensitivity to soil occupation. The accuracy and quality of extracted lineaments depend strongly on the spatial resolution of the imagery. Therefore, the aim of this study was to compare the optical Landsat-8, Sentinel-2A, and radar Sentinel-1A satellite data for automatic lineament extraction. The framework of automatic approach includes defining the optimal parameters for automatic lineament extraction with a combination of edge detection and line-linking algorithms and determining suitable bands from optical data suited for lineament mapping in the study area. For the result validation, the extracted lineaments are compared against the manually obtained lineaments through the application of directional filtering and edge enhancement as well as to the lineaments digitized from the existing geological maps of the study area. In addition, a digital elevation model (DEM) has been utilized for an accuracy assessment followed by the field verification. The obtained results show that the best correlation between automatically extracted lineaments, manual interpretation, and the preexisting lineament map is achieved from the radar Sentinel-1A images. The tests indicate that the radar data used in this study, with 5872 and 5865 lineaments extracted from VH and VV polarizations respectively, is more efficient for structural lineament mapping than the Landsat-8 and Sentinel-2A optical imagery, from which 2338 and 4745 lineaments were extracted respectively.
Highlights
The mapping of the linear structural segments, which are called “lineaments”, on the Earth’s surface has always been an important part of any structural geological investigation
The main objective of the study was to compare the performance of optical Landsat-8 (L8) and Sentinel-2A (S2A) in addition to the Sentinel-1A (S1A) radar data in structural lineament extraction
A comparison between the different bands of optical data is performed to select the best bands for automatic lineament extraction
Summary
The mapping of the linear structural segments, which are called “lineaments”, on the Earth’s surface has always been an important part of any structural geological investigation. One can conclude that lineaments usually occur as edges with tonal differences in satellite images and that most of the detection approaches are based on edge enhancement and filtering techniques [3,4,5] These studies proposed two principal techniques for lineament identification and extraction from remotely sensed data. The program aims to replace the past remote sensing missions in order to ensure data continuity for applications in the areas of atmosphere, ocean, and land monitoring For this purpose, six different satellite missions focusing on different Earth observation aspects are being operated. 1-Coastal aerosol 2-Blue 3-Green 4-Red 5-Red Edge 1 6-Red Edge 2 7-Red Edge 3 8-NIR 8a-NIR narrow 9-Water vapour 10-SWIR/Cirrus 11-SWIR 1 12-SWIR 2
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
