TecLines: A MATLAB-Based Toolbox for Tectonic Lineament Analysis from Satellite Images and DEMs, Part 1: Line Segment Detection and Extraction

Mehdi Rahnama,Richard Gloaguen

doi:10.3390/rs6075938

Abstract

Geological structures, such as faults and fractures, appear as image discontinuities or lineaments in remote sensing data. Geologic lineament mapping is a very important issue in geo-engineering, especially for construction site selection, seismic, and risk assessment, mineral exploration and hydrogeological research. Classical methods of lineaments extraction are based on semi-automated (or visual) interpretation of optical data and digital elevation models. We developed a freely available Matlab based toolbox TecLines (Tectonic Lineament Analysis) for locating and quantifying lineament patterns using satellite data and digital elevation models. TecLines consists of a set of functions including frequency filtering, spatial filtering, tensor voting, Hough transformation, and polynomial fitting. Due to differences in the mathematical background of the edge detection and edge linking procedure as well as the breadth of the methods, we introduce the approach in two-parts. In this first study, we present the steps that lead to edge detection. We introduce the data pre-processing using selected filters in spatial and frequency domains. We then describe the application of the tensor-voting framework to improve position and length accuracies of the detected lineaments. We demonstrate the robustness of the approach in a complex area in the northeast of Afghanistan using a panchromatic QUICKBIRD-2 image with 1-meter resolution. Finally, we compare the results of TecLines with manual lineament extraction, and other lineament extraction algorithms, as well as a published fault map of the study area.

Highlights

The main goal of this study is to develop a new MATLAB based toolbox (TecLines) for automatic lineaments mapping from satellite images and digital elevation models (DEM)
We demonstrate the performance of the TecLines for edge detection, where validation has been performed on a synthetic and a real dataset
The accuracy assessment shows that 30% of the known lineaments are detected as true positive edge pixels and 70% are detected as false negative edge pixels

Summary

Introduction

Detection and extraction of lineaments are commonly used for construction site selection (dams, bridges, roads, etc.) [1,2,3,4], seismic and risk assessment [5,6,7,8,9,10,11], water resources and hydrogeological investigations [12,13,14,15,16], mineral exploration [17,18,19,20,21,22], and in the study of the structural or tectonic history of a region [23,24,25]. Most of the tectonic features are associated with straight linear elements (further denoted as ―lineaments‖) on satellite images. The use of aerial photographs and satellite images in the regional scale study of linear features such as faults, fracture zones, shears zones, and lithological contacts has greatly reduced the effects of these limitations [17,27]. Lineaments are often extracted manually by digitizing, which is subjective, time consuming, expensive and requires expertise, training and adequate scientific skills. It cannot produce results for large scale areas [28].

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