A New Application of CurvaTool Semi-Automatic Approach to Qualitatively Detect Geological Lineaments

被引:19
作者
Bonetto, Sabrina [1 ]
Facello, Anna [2 ]
Umili, Gessica [1 ]
机构
[1] Univ Turin, Dept Earth Sci, Valperga Caluso 35, I-10125 Turin, Italy
[2] CNR, IRPI, Str Cacce 73, I-10135 Turin, Italy
关键词
Geological Structure; Lineament Extraction; DTM; Semi-Automatic Survey; Argentera Massif; DIGITAL ELEVATION MODELS; MASSIF WESTERN ALPS; ARGENTERA MASSIF; SATELLITE IMAGES; TERRAIN MODELS; FAULT; ALPINE; DEMS; NEOTECTONICS; CONSTRAINTS;
D O I
10.2113/gseegeosci.23.3.179
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the past years, lineament analysis has become an important analytical technique for delineation of major structural units in mineral prospecting, hydrogeology, and tectonic studies. The use of remote sensing, with progressive development of image enhancement techniques, provides an opportunity to produce more reliable and comprehensive lineament maps. In this paper, we propose the application of a semi-automatic approach based on digital terrain models (DTMs) for the extraction of potential lineaments and their detailed validation. We selected an area belonging to the Bagni di Vinadio municipality (Cuneo, NW Italy), which is part of the Argentera Massif (western Alps), as a test site. Data obtained from the code CurvaTool, developed by the authors, are successfully compared with literature information and with lineaments obtained from visual interpretation of remote sensing imagery. The CurvaTool code permits the extraction and classification of a greater number of linear features compared to visual interpretation techniques. The ability to detect features that are not perceptible by visual observation is a strong point of CurvaTool processing. In the test area, CurvaTool output data correlate with visually detected linear features and show a good correlation with regional tectonics and iso-kinematic maps from the literature.
引用
收藏
页码:179 / 190
页数:12
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