Fuzzy B-spline algorithm for 3-D lineament reconstruction

Abstract

Lineaments are vital geological features that play the role of a key indicator for ground water and petroleum searching. At present, there is no study that has utilised remote sensing satellite data to reconstruct three dimensional (3-D) lineament visualization in the Uinted Arab Emirates (UAE). This work aimed at reconstructing a (3-D) lineament visualization from multispectral remote sensing such as LANDSAT TM. In doing so, the fuzzy B-spline algorithm was used to reconstruct 3-D from two dimensional (2-D) LANDSAT TM 7 satellite data. Prior to the fuzzy B-spline algorithm, image enhancement contrast, stretching and linear enhancements were applied to acquire an excellent visualization. In addition, automatic detection algorithm of Canny was performed to extract linear features in multispectral remote sensing data, that is, lineaments, fractures. Uncertainty digital elevation model (DEM) was performed by using fuzzy B-spline algorithm to map spatial lineament variation in 3-D. Further, a fuzzy B-spline algorithm was used to reconstruct 3-D visualization of lieament with standard error of mean of 0.12 and bias of 0.23. In conclusion, fuzzy B-spline provides excellent promising for 3-D geological features reconstruction from two dimensional (2-D) remote sensing satellite data.

Effectiveness of 2-D Resistivity Survey to Identify Lineament (Fault) from Photolineament Interpretation – Case Study at Kampung Dato’ Mufti, Ampang, Selangor

“…Every method has the advantages and disadvantages of its own. Identification of lineament is vital in various field such as construction, oil and gas exploration, mining, ground water exploration and landform studies (Marghany, 2012;Omosanya et. al, 2012;Rida, 2012).…”