Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Advanced Geoscience Remote Sensing

Nowadays, advanced remote sensing technology plays tremendous roles to build a quantitative and comprehensive understanding of how the Earth system operates. The advanced remote sensing technology is also used widely to monitor and survey the natural disasters and man-made pollution. Besides, telecommunication is considered as precise advanced remote sensing technology tool. Indeed precise usages of remote sensing and telecommunication without a comprehensive understanding of mathematics and physics. This book has three parts (i) microwave remote sensing applications, (ii) nuclear, geophysics and telecommunication; and (iii) environment remote sensing investigations

3-D visualizations of coastal bathymetry by utilization of airborne TOPSAR polarized data

Multi-frequency C and L bands in the TOPSAR data have been utilized to reconstruct three-dimensional (3-D) bathymetry pattern. The main objective of this study is to utilize fuzzy arithmetic to reduce the errors arising from speckle in synthetic aperture radar (SAR) data when constructing ocean bathymetry from polarized SAR data. In doing so, two 3-D surface models, the Volterra algorithm and a fuzzy B-spline (FBS) algorithm, which construct a global topological structure between the data points, were used to support an approximation to the real surface. Volterra algorithm was used to express the non-linearity of TOPSAR data intensity gradient based on the action balance equation (ABC). In this context, a first-order kernel of Volterra algorithm was used to express ABC equation. The inverse of Volterra algorithm then performed to simulate 2-D current velocities from CVV and LHH band. Furthermore, the 2-D continuity equation then used to estimate the water depth. In order to reconstruct 3-D bathymetry pattern, the FBS has been performed to water depth information which was estimated from 2-D continuity equation. The best reconstruction of coastal bathymetry of the test site in Kuala Terengganu, Malaysia, was obtained with polarized L and C bands SAR acquired with HH and VV polarizations, respectively. With 10 m spatial resolution of TOPSAR data, bias of –0.004 m, the standard error mean of 0.023 m, r 2 value of 0.95, and 90% confidence intervals in depth determination was obtained with LHH band