“…Using the Rose module in RockWare, the azimuths were then plotted as a rose diagram to organize the lineament association according to their direction of propagation. The resulting rose diagram shows how lineaments repeat at regular intervals (Moore et al, 1991; Reddy, 1991). Figure 3.Digital elevation model (DEM), subsurface lineament, escarpment, and rose diagram for the Pratappura profile area, showing the structurally controlled drainage pattern.…”
Section: Methodsmentioning
confidence: 99%
“…Using the Rose module in RockWare, the azimuths were then plotted as a rose diagram to organize the lineament association according to their direction of propagation. The resulting rose diagram shows how lineaments repeat at regular intervals (Moore et al, 1991;Reddy, 1991).…”
To ascertain weathering, provenance, and paleoclimate of the last ca. 29 ka in mainland Gujarat, western India, a sedimentary profile of ~7.5 m was measured, described, and sampled at Pratappura and a multiproxy analysis was conducted. To determine weathering, silty-sand and sandy-silt facies were analyzed, and log Na2O/K2O versus log SiO2/Al2O3 was plotted, which shows clustering in the quartz arenite and sub-litharenite categories, indicating low to moderate weathering. The chemical index of alteration (CIA) is 55–74, and was plotted versus the index of chemical variability (ICV) of 1.50, with samples clustered mainly between subalkali basalt and picrite, indicating the dominance of a mafic component. While depleted chondrite normalized light rare earth element (REE) (La/Yb <1) levels suggest the prevalence of a mafic source in the catchment, identical chondrite normalized REE patterns indicate that sediments were well homogenized. Using multiple proxies, the measured profile was subdivided into five paleoclimatic zones. Zone-I (29–18 ka) exhibits decreasing moisture, Corg, χlf, Al2O3, TiO2, and Fe2O3 trends, while higher values of CO3−2 and δ13C indicate a change from a warm-humid to semiarid climate. Zone-II (18–11 ka) shows signs of the beginning of aridity ca. 18 ka during the Last Glacial Maximum (LGM). Several proxies in zone-III show wetter climatic conditions from the early Holocene (ca. 11–4 ka) due to the onset of the SW monsoon, with the trend continuing in zone-IV (4–2 ka). In zone-V, the climate appears to have been similar to the modern conditions in the area from 2 ka–present.
“…Using the Rose module in RockWare, the azimuths were then plotted as a rose diagram to organize the lineament association according to their direction of propagation. The resulting rose diagram shows how lineaments repeat at regular intervals (Moore et al, 1991; Reddy, 1991). Figure 3.Digital elevation model (DEM), subsurface lineament, escarpment, and rose diagram for the Pratappura profile area, showing the structurally controlled drainage pattern.…”
Section: Methodsmentioning
confidence: 99%
“…Using the Rose module in RockWare, the azimuths were then plotted as a rose diagram to organize the lineament association according to their direction of propagation. The resulting rose diagram shows how lineaments repeat at regular intervals (Moore et al, 1991;Reddy, 1991).…”
To ascertain weathering, provenance, and paleoclimate of the last ca. 29 ka in mainland Gujarat, western India, a sedimentary profile of ~7.5 m was measured, described, and sampled at Pratappura and a multiproxy analysis was conducted. To determine weathering, silty-sand and sandy-silt facies were analyzed, and log Na2O/K2O versus log SiO2/Al2O3 was plotted, which shows clustering in the quartz arenite and sub-litharenite categories, indicating low to moderate weathering. The chemical index of alteration (CIA) is 55–74, and was plotted versus the index of chemical variability (ICV) of 1.50, with samples clustered mainly between subalkali basalt and picrite, indicating the dominance of a mafic component. While depleted chondrite normalized light rare earth element (REE) (La/Yb <1) levels suggest the prevalence of a mafic source in the catchment, identical chondrite normalized REE patterns indicate that sediments were well homogenized. Using multiple proxies, the measured profile was subdivided into five paleoclimatic zones. Zone-I (29–18 ka) exhibits decreasing moisture, Corg, χlf, Al2O3, TiO2, and Fe2O3 trends, while higher values of CO3−2 and δ13C indicate a change from a warm-humid to semiarid climate. Zone-II (18–11 ka) shows signs of the beginning of aridity ca. 18 ka during the Last Glacial Maximum (LGM). Several proxies in zone-III show wetter climatic conditions from the early Holocene (ca. 11–4 ka) due to the onset of the SW monsoon, with the trend continuing in zone-IV (4–2 ka). In zone-V, the climate appears to have been similar to the modern conditions in the area from 2 ka–present.
“…The epicenters of earthquakes are not random, but rather associated with lineaments and their connecting segments. According to the modern understanding of seismic processes, high tectonic stresses that cause earthquakes usually concentrate at the intersections or bends of linear boundaries separating blocks of the Earth's crust [14][15]. Research on stress pattern changes around earthquake epicenters has shown significant changes in the lineaments and observable anomalies before impending earthquakes.…”
The main purpose of this work is to study earthquake precursors using lineament analysis for an earthquake of magnitude Mw3.0 that occurred in 2019 on the territory of the Almalyk-Angren industrial zone in Uzbekistan. The Landsat 8 satellite images were processed using the automated lineament detection method in the LEFA software. The processing steps included to detect line elements in raster images, calculate the characteristics of the spatial distribution of line elements, combining collinear linear elements into lineaments. The analysis of the cyclicality of precursors before and after earthquakes were 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 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, and decreases starting from 14 days after the earthquake, and has a minimum value in 1 – 2 months. The main trends observed in the lineament map showed dominant trend in NS, WE, NW-SE directions.
“…Conventional techniques utilised in lineament evaluation includes frequency or length against azimuth histograms (Mostafa and Zakir, 1996), rose-diagrams (Nalbant and Alptekin, 1995), and lineament density maps (Zakir et al, 1999). Additionally, spatial distributions of lineaments are also characterised by studying lineament density and intersection density of lineaments (Kumar and Reddy, 1991).…”
Abuja and environs usually experiences water shortage during the dry season as a result of rapid population growth, due to the fact that the water from Lower Usuma Dam used for domestic and industrial purposes are no longer sufficient to cater for its teeming population. The shortage can be minimized through better understanding of lineament configurations of the area. Regional groundwater studies using high-resolution aeromagnetic data in Abuja and environs, North-Central Nigeria were carried out to address water shortages in Abuja and its surroundings. The aim of the study was to identify groundwater targets/potential zones for the purpose of providing sufficient water to the communities in the area. The study area is situated in the North-Central part of Nigeria and lies between latitudes 8° 00’- 9°30’ N and longitudes 6°30’- 8°00’ E. First vertical derivative (1VD) technique was applied to the residual magnetic data of the study area using Oasis Montaj software version 8.3 and thereafter extracted lineaments from 1VD map using ArcGIS software version 10.4.1. Result of 1VD technique indicates that polyphase deformation was pervasive throughout the area as joints, fractures, faults, as well as folds in the map. Major lineament trends identified in the study area are NNE-SSW 27.47%, NE-SW 25.54%, ENE-WSW 18% and N-S 9.57%, the magnitudes and orientations of the lineaments are essential for groundwater movement. The study indicates that Dogon-Kurmi, Gitata, Rafin, Gurku, Karshi, Keffi, Paiko, Farindoki, Takuti, Lambata, Izom, Tudun Wada, Safon Lapai, Mayaki, Gwagwalada, Gidan Ali, Takura, Dafa, Dangara, Abaji, Kwali, Zuba, Madalla, Gauraka, Suleja, Kuje, Abuja, Bwari, Udegi, Zango-Daji, eastern part of Katakwa, Gadabuke, Buga, Koton-Karfe, Bibirako, Kworaki, Toto, Dagoshi and Umaisha have good groundwater prospect. Fieldwork conducted in the area confirmed the existence of lineaments/fractures in the area and as such are targets for groundwater exploration.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
