Lineament Detection Research Articles

Geological mapping from satellite imagery and lineament detection in the Imilchil-Aghbala region (High Atlas central and Middle Atlas ridges zone, Morocco)

Geological mapping from satellite imagery and lineament detection in the Imilchil-Aghbala region (High Atlas central and Middle Atlas ridges zone, Morocco)

Software implementation of the algorithm for automatic detection of lineaments and their properties on open-pit dumps

The paper presents an algorithm and a description of its software implementation for detecting lineaments (ground erosions or cracks) in aerial photography images of open-pits. The proposed approach is based on the apparatus of convolutional neural networks based on the semantic classification of binarized images of objects (lineaments), as well as graph theory for determining the geometric location of linearized objects, followed by determining their lengths and areas. Three-channel RGB images of high-resolution aerial photography (pixel 10x10 cm) were used as initial data. The software unit of the model is logically divided into three layers: pre-processing, detection and post-processing. The first level includes preprocessing of input data to form a training sample based on successive transformations of an RGB image into a binary one using the OpenCV library. A neural network of the U-Net type, which includes blocks of the convolutional (Encoder) and scanning parts (Decoder), represents the second level of the information model. At this level, automatic lineament detection (washouts) is implemented. The third level of the model is responsible for calculating the areas and lengths of lineaments. The result of the work of the convolutional neural network is transferred to the input. Lineament area is calculated by summing the total number of points multiplied by the pixel size. The length of the lineaments is computed by linearizing a plane object into a line segmental object with nodal points and then calculating the lengths between them, also relying on the resolution of the original image. The software module can work with input images, with their subsequent resulting merging to the size of the original image.

Study of the seismic activity of the Almalyk-Angren industrial zone based on lineament analysis

In this work, an automated lineament analysis was carried out to search for earthquake precursors for the territory of the Almalyk-Angren industrial zone in Uzbekistan. The seven events with a magnitude of about 3 were selected for analysis. The Landsat 8 satellite images were processed using the automated lineament detection method in the LEFA software. The processing steps included detecting line elements in raster images, calculating the characteristics of the spatial distribution of line elements, and combining collinear linear elements into lineaments. The analyses of the cyclicality of precursors before and after earthquakes were based on the study of the distribution of the lineament trend in the study area using rose diagrams and lineament density maps. The results showed a change in the dynamics of the lineament structure. The statistics of the number of lineaments showed that their increase begins almost 20 days before the event, reaches its maximum about 1 – 2 days before the earthquake, decreases starting from 14 days after the earthquake, and has a minimum value of 1 – 2 months. The main trends observed in the lineament map showed the dominant trend in NS, WE, NW-SE directions.

Software Implementation of an Algorithm for Automatic Detection of Lineaments and Their Properties in Open-Pit Dumps

Software Implementation of an Algorithm for Automatic Detection of Lineaments and Their Properties in Open-Pit Dumps

Detection and characterization of lineaments using gravity data in the south-west Cameroon zone: Hydrogeological implications

Abstract In Cameroon, the drying up of wells and boreholes during the dry season is characterized by a lack of knowledge about the surface structures of the subsoil and the spatial distribution of groundwater. In this study, we propose to use gravity data to detect and characterize the surface structures of the south-west (SW) Cameroon and to analyze their hydrogeological implications. The application of the normalized standard deviation method on the data obtained from the stable downward continuation of the Bouguer anomalies led to the detection of 71 lineaments that characterize the tectonic events of the study area. The statistical analysis of the lineament directions shows that the near-surface structures were mainly affected by a tectonic of direction east–west followed by that oriented SW-north-west. These two directions are consistent with the megastructures in the region like the Ngoro-Belabo Shear Zone and the Sanaga Fault stretching from the Gulf of Guinea to the Central African Republic. In addition, the application of the Euler deconvolution method permits us to evaluate the interval in which lies the depth of each lineament hosting Euler solutions. The analyses showed that 12 lineaments, whose roof depths are between zero and 250 m, are very favorable for hydrogeological prospecting.

The Sub‐Ice Structure of Mt. Melbourne Volcanic Field (Northern Victoria Land, Antarctica) Uncovered by High‐Resolution Aeromagnetic Data

AbstractThe Mt. Melbourne Volcanic Field is a quiescent volcanic complex located in Northern Victoria Land, Antarctica, mostly covered by ice. Its inner structure has remained largely unknown, due to the paucity of outcrops and the lack of detailed multi‐disciplinary investigations. Here we present a novel high‐resolution aeromagnetic dataset, revealing strong long‐wavelength negative anomalies superimposed by short‐wavelength positive ones forming characteristic radial patterns. Automatic lineament detection, through the Hough transform technique applied to the tilt derivative of our magnetic dataset, shows prevailing NW‐SE‐to NNE‐SSW‐trending structural features, which combined with the few structural field observations contribute to define the deformation pattern. Pre‐existing and novel magnetic property measurements, coupled with available geochronological data, are used to constrain a two‐step 3D magnetic inversion. A layer‐structured Oldenburg‐Parker's inversion was utilized to model the deep and long‐wavelength components of the magnetic field, whereas a linear inversion based on a set of shallower prisms was used to model the short‐wavelength components. The final 3D model shows widespread reversely‐polarized volcanics, which are locally intruded and superimposed, respectively by swarms of normally‐polarized dikes and radial lava flows along paleo‐valleys. These results support the onset of volcanic activity in the entire field at least in the Matuyama magnetic epoch, that is, between 2.58 and 0.78 Ma.

A single multi-scale and multi-sourced semi-automated lineament detection technique for detailed structural mapping with applications to geothermal energy exploration

Semi-automated algorithms incorporating multi-sourced datasets into a single analysis are increasingly common, but until now operate at a fixed pixel resolution resulting in multi-sourced methods being limited by the largest input pixel size. Multi-scale lineament detection circumvents this issue and allows increased levels of detail to be captured. We present a semi-automated method using a bottom-up Object-Based Image Analysis approach to map regional lineaments to a high level of detail. The method is applied to onshore light detection and ranging (LiDAR) data and offshore bathymetry around the Land's End Granite (Cornwall, UK). The method uses three different pixel resolutions to extract detailed lineaments across a 700 km 2 area. The granite displays large-scale NW–SE fault zones that are considered analogous to those being targeted as onshore deep geothermal reservoirs (2–5 km in depth). Investigation of the lineaments derived from this study shows along-strike variations from NW–SE orientations within granite to NNW–SSE within slate and reflects structural inheritance of early Variscan structures within Devonian slates. This is furthered by analysing these major structures for reservoir potential. Lineaments proximal to these broadly NW–SE features indicate that a damage zone c. 100–200 m wide is present. These observations provide a preliminary understanding of reservoir characteristics for fault-hosted geothermal systems. Thematic collection: This article is part of the Remote sensing for site investigations on Earth and other planets collection available at: https://www.lyellcollection.org/topic/collections/remote-sensing-for-site-investigations-on-earth-and-other-planets Supplementary material: A description of the OBAI method and additional figures are available at https://doi.org/10.6084/m9.figshare.c.6309629

How a basement fault has controlled Pb- Zn ore deposition within the Zagros Fold-Thrust Belt? a focus on remote sensing approaches

ABSTRACT The Zagros fold and thrust belt as one of the structurally complex areas have been considered chiefly only for hydrocarbon reserves, despite having other mineral deposits like the Surmeh lead and Zinc mine. This study was conducted in the Fars region, one of the structural zones in the Zagros, to detect hydrothermal alteration minerals associated with Pb–Zn mineralization and fracture distribution using ASTER, Landsat 8, and Sentinel 2 satellite imagery. Using different algorithms and approaches, we demonstrate the interesting distribution of Pb-Zn-related mineral deposits controlled by structures on different scales. These methods included the spectral band ratios and spectral angle mapping for alteration detection and manual extraction of structural lineaments (i.e. fault and fractures) from ETM+. Also, an augmented circular scanline method, along with areal sampling, was used to prepare a fracture intensity map of the area. According to the results, the intersection of NW-SE and N-S trending fracture sets are promising areas for Pb-Zn-related mineral exploration. These fracture sets are likely associated with the main Karebas tear fault and its horsetail splay terminal. The findings of this study were validated by field observation of the Pb-Zn deposit and its related mineral associations in the area.

Hydrogeochemical and geophysical investigations to delineate underground water aquifer in arid regions: A case study, Gara oasis, Egypt

The goal of the present study is to investigate, delineate, and evaluate the shallow Miocene groundwater aquifer with vertical and lateral facies variations in the Gara oasis, western desert of Egypt. This oasis represents a typical arid region in North Africa. Through grid texture analysis, lineament detection, edge detection, thresholding, and identifying areas of structural complexity from the filtered residual reduced-to-pole magnetic anomaly map, it is possible to outline the fracture zones that principally control the groundwater aquifers and water flow in the area. The groundwater quality and quantity are examined hydro-geochemically through nine groundwater samples that were gathered from wells and springs distributed throughout the area around Gara Lake. Measurements of physio-chemical parameters (TDS, pH, and EC) are carried out and its spatial distribution is critically studied. The results reveal that the ion-exchange process caused by water-rock interaction is the dominant process. Furthermore, the main ions in the groundwater in the study areas were Na and Cl. This might be due to evaporation or halite dissolution with the upward flow of waters through the fractures from the deep aquifer of the Nubian sandstone to the shallow aquifer of the fractured Miocene limestone.

Lineament analysis as a seismic precursor: The El Mayor Cucapah earthquake of April 4, 2010 (MW7.2), Baja California, Mexico

An earthquake called the MW7.2 “El Mayor Cucapah” earthquake on April 4, 2010 has been analyzed for seismic precursor. The changes in the lineament system concerning its pattern and time intervals were analyzed during the earthquake preparation period and occurrence using the automated lineament detection method. The Landsat 5 TM images were processed using LESSA and ADALGEO software obtaining similar results. The statistical analysis revealed the stress accumulation due to plate interaction during earthquake formation. The study shows that the number of extracted lineaments changes rapidly about 23 months before the earthquake, and the systems return to the initial stage after 23 months. Most lineaments coincide with the extension of the San Andreas Fault as NW direction is the dominant trend. Thus, it can be concluded that the featural changes within the Rose diagram corresponding to the different strokes direction along with oriented elongation lines as disclosed in the present study using satellite images could be identified as a mid-term and/or short-term precursors of the earthquake. However, even though the dynamism of the El Mayor Cucapah earthquake is found in the extracted lineaments, it is possible to isolate more significant earthquakes even if new ones appear near the zone. Moreover, using two algorithms for lineament detection allows for the tectonics to corroborate the obtained lineaments and dynamism.

Automatic detection of geological lineaments in central Turkey based on test image analysis using satellite data

The Hamurcu and Başdere study areas, part of the Central Anatolian Volcanic Provence (CAVP), are associated with metalliferous ore deposits. The assumption that hydrothermal alterations might be related to faults and fractures makes mapping the lineaments around the study areas vital. Accordingly, geological lineaments in the vicinity of the studied areas in Central Anatolia (Turkey) were delineated using Landsat-8 and Phased Array type L-band Synthetic Aperture Radar (PALSAR) data. We adopted a new methodology for determining the optimal values of six parameters used in a fully automated extraction of lineaments. The lineaments identified in the region including the study areas strike mainly the NW-SE direction in the PALSAR data. Moreover, hydrothermal alterations around the towns of Hamurcu and Başdere are directly related to the NW-SE oriented faults, indicating that the lineations in the region might be carefully scrutinized in the exploration of mineralization zones. As a result, it was demonstrated in this study that the most appropriate parameter values specified for automatic lineament extraction successfully map geological structures around both study areas and can confidently be employed in different geographical locations.

Study of Active and Fossil Hydrothermal Systems in Ijen Caldera Complex and Merubetiri Mountains, East Java

Ore deposits formed at subduction zone are associated with magmatism activities that are represented by volcanic activities at the surface. In the Eastern Sunda Arc, one of active volcanic activity can be found in Ijen Caldera Complex. The complex has hydrothermal volcanic manifestations with a very acidic pH. Meanwhile in the south of Ijen Complex, there is ancient volcanic complex called Merubetiri Mountains that is proven to be well-mineralized at Tumpangpitu as high sulfidation and porphyry-style mineralizations. An understanding of hydrothermal activity and volcanic landforms in active volcanic systems can be used as a powerful tool to understanding hydrothermal systems. This paper presents the distinction between active hydrothermal systems and fossil hydrothermal systems as an exploration’s tool in ancient volcanic systems. The method used in this study is remote sensing with focus on volcanic landforms, geological structures, and distribution of alteration minerals. ASTER satellite imagery, Landsat 8 satellite imagery, and DEMNAS are used in this study. ASTER and Landsat 8 images are processed with Principle Component Analysis (PCA) and Direct Principle Component (DPC) methods to determine the distribution of alteration minerals that are associated with propylithic, argillic, advanced argillic, and silisic alterations. Semi-quantitative method is used to identify geological structures by automatic lineament detection. Meanwhile, qualitative method is used by manual lineaments delineation on the DEM imagery. Delineations of volcanic landforms in active and ancient volcanic complex use semi-quantitative methods include ridge lineaments and flow pattern. Then, volcanic landform is manually delineated by determining the distribution pattern of ridges, flow pattern, morphological texture, and cross-cutting relationship of volcanic products as a key in determine the eruption centers. The results show a relationship between volcanic distribution and the main stresses in the Ijen Caldera Complex with NE-SW direction, which is represented by the elliptic and elongation of volcanic depression zone, monogenetic volcano, and intrusion distribution. Geological structures that are found in the Ijen Caldera Complex show E-W and NE-SW directions. Meanwhile, Merubetiri complex shows E-W, NW-SE, and N-S structural direction patterns. The distribution of alteration minerals associated with silisic, argillic, and advance argillic in the Ijen Caldera Complex are found in the central zone of stratovolcano, intra-caldera zone, and structural zone that intersects the caldera. This shows that active hydrothermal system is related to volcanic activity and geological structures. Meanwhile, in the Merubetiri complex, alteration minerals are associated with the eruption centers, diorite/granodiorite intrusions, and NW-SE strike slip fault. The understandings of volcanic setting and volcanic landforms are very important in the early stages of exploration to determine the prospect of mineral deposits related to hydrothermal system.

Mapping subsurface structural lineaments using the edge filters of gravity data

The subsurface structures can be extracted from geophysical studies. This study deals with the detection of lineaments from gravity data that are related to the boundaries of the subsurface structures. The methods used in this study such as the horizontal gradient, total gradient, enhanced horizontal gradient, and improved logistic are tested on synthetic model prior to application to real gravity data. The results indicate that the improved logistic filter can be an effective method for boundary detection of gravity data.

The lineaments as one of the precursors of earthquakes: A case study of Tashkent geodynamical polygon in Uzbekistan

This work is to study earthquake precursors using lineament analysis of five MW3 earthquakes that occurred in 2018 on the territory of the Tashkent geodynamic polygon in Uzbekistan. The Landsat 8 satellite images were processed using the automated lineament detection method in the LEFA software. The processing steps included image preprocessing with graphic filters, edge detection using Canny's algorithm, the definition of a vector of linear elements based on the probabilistic Hough transform and combining collinear linear elements into lineaments. The analysis of the cyclicity of precursors before and after earthquakes was based on the study of the distribution of the lineaments trend in the study area using rose diagrams and lineaments density maps. The results showed a change in the dynamics of the lineament structure. The statistical analysis of lineaments revealed that the number and orientation of lineaments changed significantly about 2–4 months before an earthquake, and after 2–3 months, the system gradually returned to its initial state. The rapid increase in lineaments density began almost 20 days before the event, reaching a maximum about 4 days before the earthquake, and its decrease began 16 days after the earthquake. The main trends observed in the lineament map showed dominant trends in NS, EW, and the subdominant directions were in NW–SE, NE–SW, which coincided with main directions of the faults.

Multi-sensor Assessment of Geological Lineament Detection

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.

Fault-Based Geological Lineaments Extraction Using Remote Sensing and GIS—A Review

Geological lineaments are the earth’s linear features indicating significant tectonic units in the crust associated with the formation of minerals, active faults, groundwater controls, earthquakes, and geomorphology. This study aims to provide a systematic review of the state-of-the-art remote sensing techniques and data sets employed for geological lineament analysis. The critical challenges of this approach and the diverse data verification and validation techniques will be presented. Thus, this review spanned academic articles published since 1975, including expert reports and theses. Landsat series, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Sentinel 2 are the prevalent optical remote sensing data widely used for lineament detection. Moreover, Shuttle Radar Topography Mission (SRTM) derived Digital Elevation Model (DEM), Synthetic-aperture radar (SAR), Interferometric synthetic aperture radar (InSAR), and Sentinel 1 are the typical radar remotely sensed data which are widely used for the detection of geological lineaments. The geological lineaments acquired via GIS techniques are not consistent even though a variety of manual, semi-automated, and automated techniques are applied. Therefore, a single method may not provide an accurate lineament distribution and may include artifacts requiring integration of multiple algorithms, e.g., manual and automated algorithms.

A convolutional neural network for semi-automated lineament detection and vectorisation of remote sensing data using probabilistic clustering: A method and a challenge

In this paper we present the framework and open-source software code to train and apply Deep Learning Convolutional Neural Networks (CNNs) to the prediction of geological lineaments using topographic, magnetic, and gravity raster data. Many important applications relate to the recognition of linear geological structures from remote sensing data, such as thrust faults, bedrock fault and shear zones, lithological contacts, fractures and fold structures. The digitization of fault lineaments is conventionally performed by geologists or geophysicists with working knowledge of the relevant data, e.g., topographic Digital Elevation Model, magnetic data, and gravity data. Visual inspection and extraction is simple but subjective; the process is also time-expensive with efficiency and accuracy depending on the individual's knowledge, experience, and skill. For decades there has been interest in ways to automate this process. Our CNN approach is trained using publicly available lineament GIS data from the Quest BC project in British Columbia, Canada, and the Loch Lilly-Kars area of New South Wales, Australia. The datasets used to train the prediction models resulted in interesting predictions proximal to the training areas: some major lineaments are indicated, some are missed, and potential new (valid) lineaments are indicated. The results indicate potential for use as a semi-automated lineament detection solution. In contrast, but as anticipated, application of the model to the blind-test area of the Swayze greenstone belt, Ontario, produced poor lineament prediction results (as compared to publicly available interpretations). We interpret this result as related to insufficiently large training data inputs. However, it is inferred that results could be improved through feature engineering (e.g., use of topographic slope, rather than simply elevation) without the need to simply create larger training datasets. We hope that, by making the code open-source, the geoscience community will use this platform to gradually improve an open source fault prediction model.

Application of the tilt derivative transform to bathymetric data for structural lineament mapping

High-resolution bathymetry surveys provide an opportunity to analyse local geological structure where onshore areas afford limited exposure. Semi-automated lineament detection methods are necessary for areas of large coverage where a manual analysis would be subjective and time-consuming. However, semi-automated approaches are dependent on effective feature extraction methods to identify genuine lineaments. This study offers solutions to common problems that can impede processing methods where sharp steps in the seafloor (e.g. palaeocoastlines) are present. Directional gradient, Sobel and Laplacian filters are explored as well as the hillshade and tilt derivative transform for feature extraction prior to applying an object-based image analysis lineament detection approach. The filtered datasets generally perform poorly with a marked improvement when using the hillshade transform. However, we find the azimuth-invariant tilt derivative, which incorporates a convolved vertical derivative, to be the most successful, identifying lineaments in a range of orientations and across a sharp step in the seafloor.

A geomagnetic analysis for lineament detection and lithologic characterization impacting groundwater prospecting; a case study of Buffalo catchment, Eastern Cape, South Africa

A lithostratigraphy analysis commonly adopted for subsurface structures exploration in oil prospecting is deployed for groundwater prognosis, due to the need to address the prevailing water shortage. In this study, the lithology characterization was based on a clustered approach of geomagnetic analysis, geomorphometric analysis, and sequence stratigraphy correlation across the Buffalo catchment, Eastern Cape, South Africa. The result showed the existence of a spatial correlation between the tectonic stress field and the surficial lineaments. Similarly, a significant azimuthal correlation (WNW-ESE) was found between surficial lineaments (203 m–6249 m), subsurface lineaments, and the neotectonic structures. The depth-slicing analysis enables the estimation of the depth of the tectonic stress field, at 382 m, 577 m, 913 m, 1.49 km, and 10.7 km in the subsurface. The sequence stratigraphy correlation based on borehole lithology data enables the identification of the fault system at the contact zones, heterolithic bedding, and the characterization of the hydrostratigraphic domain of the catchment. The study shows that Buffalo hydrostratigraphic structures are dominated by fracture networks, whereby the shallow groundwater resources are possibly hosted by the dolerite-host rock contact zones in the north of the Buffalo catchment. Specific recommendations concerning groundwater management are made to water and environment stakeholders considering the vulnerability of the shallow groundwater system to pollution in the permeable contact zones of dolerite-host rock. The study also recommends the adaptation of surficial lineaments as a morpho-tectonic aid and a hydrostratigraphic analysis tool. The clustered approach demonstrated in this study has important prospects for groundwater exploration in environments with similar geology.

The Hough transform algorithm coupled with spatial filtering for the study of geological structuring control on the drainage network: application to the North Oulmes region, Morocco

In a changing climate, the more we understand the drainage networks distribution and structuration, the more we can better predict flood risks, and ensure better water resource management. The identification of geological lineaments is a basic approach for the study and analysis of surficial geological structuring that potentially controls the drainage networks distribution and subsurface water resources. Taking the North Oulmes region in Morocco as an example, an automatic lineament detection algorithm based on the Hough transform has been applied to the Landsat 8 OLI and Sentinel-1 SAR data. This technique was coupled with spatial filtering and field data with the aim of identifying surface geological structures that may control the drainage network. This study also presents an analysis of the drainage network which concerns the identification of similarities between its structuring and geological lineaments, through the analysis of rose diagrams and the identification of the different drainage network patterns. The results show that the geological lineaments identified by the algorithm are very satisfactory, geologically significant, and represent continuity toward the surface of the underlying structures. The findings of this study also show that the conformation of the drainage network characteristics with the geological structures and the rectangular and trellis drainage patterns observed in the study area indicate that the distribution and structuring of the drainage network is mainly controlled by the geological structures trending NE-SW resulting from the Hercynian tectonic event.