Landsat TM analysis of fracture patterns: a case study from the Coastal Cordillera of northern Chile

Leech, Desmond P.; Treloar, Peter J.; Lucas, Neil; Grocott, John

doi:10.1080/0143116031000102520

Cited by 46 publications

(27 citation statements)

References 36 publications

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“…The identification lineaments in the automatic technique is more efficient, more accurate, and much faster than in the manual process, which is always influenced by subjective parameters (Muhammad and Awdal, 2012). A major impediment facing automatic extraction is the inability to distinguish geological lineaments from non-geological lineaments, thus the resultant maps may contain lineament features derived from other sources besides geological structures, such as railway, power, and fence lines (Leech et al, 2003;Sarp, 2005). Although there are many studies describing the geological setting of the DSFZ, we are still lacking a clear detailed map of the distribution, extent and orientation of lineaments and their tectonic origin is not clear.…”

Section: Introductionmentioning

confidence: 99%

Detection and analysis of morphotectonic features utilizing satellite remote sensing and GIS: An example in SW Jordan

et al. 2016

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This study investigates the dominant orientations of morphological features and the relationship between these trends and the spatial orientation of tectonic structures in SW Jordan. Landsat 8 and hill-shaded images, constructed from 30 m-resolution ASTER-GDEM data, were used for automatically extracting and mapping geological lineaments. The ASTER-GDEM was further utilized to automatically identify and extract drainage network. Morphological features were analyzed by means of azimuth frequency and length density distributions. Tectonic controls on the land surface were evaluated using longitudinal profiles of many westerly flowing streams. The profiles were taken directly across the northerly trending faults within a strong topographic transition between the low-gradient uplands and the deeply incised mountain front on the east side of the Dead Sea Fault Zone. Streams of the area are widely divergent, and show numerous anomalies along their profiles when they transect faults and lineaments. Five types of drainage patterns were identified: dendritic, parallel, rectangular, trellis, and modified dendritic/trellis. Interpretation and analysis of the lineaments indicate the presence of four main lineament populations that trend ~E-W, ~N-S, NE-SW, and NW-SE. Azimuthal distribution analysis of both the measured structures and drainage channels shows similar trends, except for very few differences in the prevailing directions. The similarity in orientation of lineaments, drainage system, and subsurface structural trends highlights the degree of control exerted by underlying structure on the surface geomorphological features. Faults and lineaments serve as a preferential conduit for surface running waters. The extracted lineaments were divided into five populations based on the main age of host rocks outcropping in the study area to obtain information about the temporal evolution of the lineament trends through geologic time. A general consistency in lineament trends over the different lithological units was observed, most probably because repeated reactivation of tectonism along preexisting deep structural discontinuities which are apparently crustal weakness zones. The reactivation along such inherited discontinuities under the present-day stress field is the most probable explanation of the complicated pattern and style of present-day landscape features in SW Jordan.

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Section: Introductionmentioning

confidence: 99%

Detection and analysis of morphotectonic features utilizing satellite remote sensing and GIS: An example in SW Jordan

et al. 2016

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“…Previously, many workers (Mah et al, 1995;Leech et al, 2003;Nama, 2004, to mention a few) used one or a combination of these methods to enhance the interpretability of the images for the ultimate extraction of lineaments. In this study, two image enhancement techniquesdirectional filtering and color composite were adapted.…”

Section: Methodsmentioning

confidence: 99%

“…Aerial photography has been the most widely used form of remote sensing, and lineament interpretations from them were common; however, as the resolution of satellite images continued to improve, they replaced aerial photographs for a variety of remote sensing applications (Lillesand et al, 2008). Image processing techniques have previously been used to extract lineaments from satellite images as a means of identifying linear surface traces of geologic structures such as faults and joints (Mah et al, 1995;Henderson et al, 1996;Süzen & Toprak, 1998;Arlegui & Soriano, 1998;Leech et al 2003;Nama, 2004). As geological structures serve as good path ways for subsurface water circulation, the recognition of lineaments on satellite images has proved to be very useful for the exploration of groundwater (Sander et al, 1997;Tam et al, 2004;Galanos et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Identifying the link between lineament and cave passage trends to comprehend fractures continuity and influence on the Kinta Valley karst system, Peninsular Malaysia

Kassa¹,

Pierson²,

Chow³

et al. 2012

IJS

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The Kinta Valley karst landscape is characterised by residual limestone hills scattered all over the valley. The aim of this study is to ascertain the link between lineament and cave passage orientations, and to identify the main fracture controlling the karst features. To achieve that, standard cave surveying and direct lineament extraction techniques, from a 2.5m resolution spot image, were employed. Six trends of lineaments were obtained from the remnant limestone hills, and their main orientation appears to be in the NNW-SSE. Similarly, various caves were surveyed and mapped; their passage orientation analyses reveal that NNW-SSE is the prominent direction. The similarity of the lineaments orientation and caves passage trend attests that the karst formation is controlled by the geological structures. Such a similar trend observed in all hills enabled to infer the orientation of the primary structure responsible for the formation of the extant karst features. The multi-fracturing episodes rendered the Kinta Valley to be structurally complex and the karst features unravelled this effect, as evidenced by features such as circular and sinuous cave passage morphology, which developed ensuing fractures oriented in different directions.

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“…In practice, researchers have preferred to use the spatial domain filtering techniques in order to get ride of the artificial lineaments and to verify disjoint lineament pixels in satellite data (Süzen and Toprak 1998). Further, Leech et al, (2003) implemented the band-rationing, linear and Gaussian nonlinear stretching enhancement techniques to determine lineament populations. Won-In and Charusiri (2003) found that High Pass Filter enhancement technique provides accurate geological map.…”

Section: Satellite Remote Sensing and Image Processing For Lineament mentioning

confidence: 99%

Three-Dimensional Lineament Visualization Using Fuzzy B-Spline Algorithm from Multispectral Satellite Data

Marghany¹

2012

Remote Sensing - Advanced Techniques and Platforms

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Landsat TM analysis of fracture patterns: a case study from the Coastal Cordillera of northern Chile

Cited by 46 publications

References 36 publications

Detection and analysis of morphotectonic features utilizing satellite remote sensing and GIS: An example in SW Jordan

Detection and analysis of morphotectonic features utilizing satellite remote sensing and GIS: An example in SW Jordan

Identifying the link between lineament and cave passage trends to comprehend fractures continuity and influence on the Kinta Valley karst system, Peninsular Malaysia

Three-Dimensional Lineament Visualization Using Fuzzy B-Spline Algorithm from Multispectral Satellite Data

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