Mapping the Spatial Distribution and Characteristics of Lineaments Using Fractal and Multifractal Models: A Case Study from Northeastern Yunnan Province, China

Abstract

This study describes the fractal dimensions of the spatial distributions of lineaments as an index of the complexity of faults, and the results could provide new insights into the migration of ore-bearing fluid. The Segment Tracing Algorithm method is employed to extract the lineaments in northeast Yunnan Province from a remote sensing image. Box-counting fractal and multifractal models are used to analyze the fractal and multifractal spatial distribution characteristics of the linear structures. The different directions of the linear structure fractal dimensions are similar in the study area. The fractal dimensions of all lineaments, northeast trending lineaments and northwest trending lineaments are 1.98, 1.94 and 1.95, respectively. The dimensions of four large ore deposit fields, Kuangshanchang, Qilinchang, Maozu, and Lemachang, are 1.93, 1.92, 1.95, and 1.93, respectively. The fractal dimensions of these four fields are greater than those of the South China lineaments. The super-large and large ore deposits are consistent with fractal dimensions with high values. The scale index and the singular index show nonlinear relationships with any real number, and the fractal dimension spectrum has a unimodal curve. This study provides a useful reference for deposit exploration in areas with topographies similar to that in northeastern Yunnan.

Fractal and Multifractal Characteristics of Lineaments in the Qianhe Graben and Its Tectonic Significance Using Remote Sensing Images

“…Unlike D(q) and α(q), the fractal spectrum (f (α)) is a convex function of an approximate parabola [81], and its symmetry is generally expressed as shown in Equation (15). Previous studies have shown that a grid number with large probability is larger than a grid number with small probability when f (α) is a left-hook curve [3]. By contrast, a grid with a small probability has a higher number when f (α) is a right-hook curve [82].…”

“…Geological lineaments are defined as the straight linear elements visible at the Earth's surface, such as bedrock faults and joints, stratification, linear sand dunes, and drumlins [1], and they can be a brighter or darker line or structure than background pixels on remote sensing images, representing some geological or geomorphological phenomena, such as a trace of intersection between a planar or sub-planar structural inhomogeneity [2]. The existence of lineaments has been proven to be closely related to unexposed faults [3], reflecting patterns and anomalies (e.g., alteration) in the crust and the favorable zone for mineral deposits and processes [4,5], and controlling the position of deposit and the migration and accumulation of minerals (e.g., [4,[6][7][8][9][10]). In an active fault system, lineaments are indicative for locating the faults and determining the general structural parameters [11], and they can indirectly reflect the spatial distribution of groundwater [12], hydrothermal alteration zones [13,14], and geo-hazards [15].…”

“…Therefore, to obtain a more accurate spatial distribution of lineaments in the geological system, previous studies mainly focused on the extraction of lineaments from ridge and valley lines across gully areas [11]. Owing to the characteristics of remote sensing images and Digital Elevation Models (DEMs), such as convenient acquisition, rich visual expression information, long-term estimation, and limits of anthropogenic interference [3], a large number of algorithms, such as the segment tracing algorithm (STA) [16], Hough transform (HT) [17], and hydrological analysis [18], were designed and effectively implemented in various regions. However, due to the noise in the images and the complexities of algorithms, the connectivity and lengths of lineaments vary and increase or decrease the size and density of the faults [19].…”

“…Specifically, the scale of the fractal dimension is proportional to the frequency and growth of the tectonic movement; that is, a larger fractal dimension denotes more favorable movement of the bottom mineral deposits and a greater likelihood of mineralization [14]. As a result, the fractal dimension of lineaments has become a widespread method for estimating the potential range of the metallogenic zone (e.g., [3,4,8,35]), and it has been shown to be an effective instrument for mineral exploration and analysis of migration conditions [36][37][38]. However, in some locations, the faults were covered by thick soil, such as the Qianhe Graben in China [11,39], and they could not provide a reliable quantitative prediction for active faults from the field measurements.…”

“…Furthermore, previous studies showed that the single-fractal dimension (e.g., box dimension) [4] may be not enough when only considering the number of lineaments [5], resulting in the other local patterns and distribution of faults (e.g., length, density) being ignored. Therefore, to address this challenge, the multifractal dimension of lineaments was also defined using the generalized multifractal dimensions (Dq), the singularity (α), and the multifractal spectrum f(α) [3,5,37,40,41]. These parameters provide additional support for metallogenic information and ore deposition [42,43].…”