Fuzzy b-spline algorithm for 3-d lineament reconstruction

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 lineament 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

Simulation of shoreline change using AIRSAR and POLSAR C-band data

This paper presents a new approach for modeling shoreline change due to wave energy effects from remotely sensed data. The airborne AIRSAR and POLSAR data were employed to extract wave spectra information and integrate them with historical remotely sensed data such as aerial photography data to model the rate of change of the shoreline. A partial differential equation (PDE) of the wave conversion model was applied to investigate the wave refraction patterns. The volume of sediment transport at several locations was estimated based on the wave refraction patterns. The shoreline change model developed was designed to cover a 14-km stretch of shoreline of Kuala Terengganu in Peninsular Malaysia. The model utilized data from aerial photographs, AIRSAR, POLSAR, ERS-2, and in situ wave data. The results show that the shoreline rate of change modeled from the quasi-linear wave spectra algorithm has a significant relationship with one estimated from historical vector layers of aerial photography, AIRSAR, and POLSAR data. With the quasi-linear algorithm, an error of ±0.18 m/year in shoreline rate of change determination was obtained with Cvv band