Digital Elevation Modeling of Inaccessible Slope by Using Close-range Photogrammetric Data

Digital Elevation Model (DEM) currently is extensively used extensively in various applications such as for natural hazard assessment and monitoring of high risk areas. DEM data source of inaccessible areas can be collected by using several methods, but mostly are costly and requires sophisticated instruments. Due to these conditions, close-range photogrammetry offers a low cost alternative solution. Materials presented in this thesis are based on the experiments to explain the application of close-range photogrammetry with the aid of commercial digital pocket camera as DEM data collection tools, applied on inaccessible slope areas. The analysis covers calibration of the camera and surveying instruments, DEM data collections, data processing and visualization, together with DEM quality measures. The data collections are accomplished on several study areas with different topographical characteristics by using close-range photogrammetry technique. The sampling points were selected on stereo model, by using three types of sampling methods. The DEM quality measures are assessed by following elevation interpolation error and volumetric difference error analyses. The representation of the DEM is generated using TIN-based (Triangular Irregular Network) approach. The result shows that the method is able to be applied for three dimensional (3D) modeling of potentially unstable slope areas, with accuracy of less than 15 cm in RMS for elevation error and is less than 1% in volume error. The result has indicated that topographical condition has not affected the accuracy of generated DEM. Improvement of point density radically enhances the DEM’s quality, up to a certain level of point density beyond which the increment of the accuracy is not significant. The difference setting of focal length has also influences the quality of captured images, and drastically affects the accuracy of the DEM. If the accuracy of the DEM is a matter of concern, the preferred sampling method is selective sampling, while if accuracy and DEM’s time generation are the concern the most effective sampling method is regular sampling method. Since there was no permanent points on the observed slope surface, velocity and direction of landslide could not be accurately determined. However the distribution of massmovement and elevation changed on the slope surfaces can be modeled through spatialcalculation of overlaying DEMs together with profiling of cross-section and longitudinalsection of the generated DEMs

Case-Based Reasoning of Man-Made Geohazards Induced by Rainfall on Transportation Systems

Due to global warming and environmental change, disastrous natural events have increased in scale and impact, e.g., Typhoon Morakot, in 2009 and 2011 Tōhoku earthquake and resulting tsunami in Japan. Hazard management is becoming increasingly important, making it a necessity to manage risk and fully understand critical scenarios. For example, the National Infrastructure Protection Plan of the United States emphasizes on lessons learned from past disasters. In this chapter, several selected cases of accidents caused by man-made geohazards in Taiwan are studied

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing