Extraction and analysis of geological lineaments combining a DEM and remote sensing images from the northern Baoji loess area

Geological lineaments are important reactant of geological structure on the surface, and control the distribution of regional ground-water, geohazards, geothermal and earthquakes. The technology of geological lineaments extraction is of great significance for the analysis of regional plate movement and ore forming prognosis. However, the traditional methods are mainly based on the semi-automatic or manual visual interpretation, which consuming time and labor for the dependence on the rich professional experience and knowledge of the interpreter experts, and involving less in the special geomorphological regions. Taking Loess areas in northern Baoji as an example, this paper proposed a lineaments extraction algorithm based on tensor voting coupled Hough Transform, with the help of DEM and Landsat 8 OLI remote sensing images. Firstly, the best independent band combination of Landsat 8 OLI images for lineaments extraction were selected by using principal component analysis. Secondly, Gaussian high-pass filter was applied to sharpen the edge in the DEM and composite Landsat 8 OLI images. Linear boundary was extracted by tensor voting according to the conspicuousness of the vector sum superposition feature based on edge points. Finally, the Hough Transform was employed to search the edges and extracted the geological lineaments in this region. The experimental results showed that the orientation of lineaments was dominated by NW-SE and NE-SW, supplemented by NNW-SSE. Under the influence of the uplift of the eastern foot of Liupan Mountains and the southern margin of Ordos, the lineaments were mainly distributed over linear landforms, which were better consistent with previous studies about the direction of tectonics in this region. Compared with the segment tracing algorithm, this method has more applicability, efficiency, high practical value and scientific significance in the analysis of tectonic movement and evolution in special landform area. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.