2002/04/04
Traditionally, in studying the effect of hazards on roads, a hazard map is prepared based on the hazard in question, the contributing factors and then overlaid with a road map. If the road or a buffer around its vicinity intersects hazard areas, these areas constitute a potential threat.
In the approach used in this procedure, imagine traveling along the road and looking to either side for hazards. The neighborhood that needs to be examined is dependent on the hazard and its contributing factors. This neighborhood search then produces a hazard map that is directly related to the road.
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2002/04/03
Current research work into establishing a performance efficiency hierarchy between Java, C++ and ArcView is described and experimentation is performed in order to statistically compare shortest path query execution time, response time and implementation issues.
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2002/03/22
The primary hazards included in this study are avalanches, landslides, flooding, earthquakes, wildfires, and rockfall. Although the primary focus of this research is roads, it is equally applicable to other transportation lifelines, such as railways, canals/waterways, or transmission lines for power, gas or oil. This presentation provides an overview of the spatial framework, current results and limitations, and directions for further research. MFworks was used as a GIS tool, along with a self-developed Java application.
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2002/01/27
If you are into network analysis of any kind, this book teaches you the basics. As the name implies, Networks and Algorithms by Alan Dolan is an introductory book. It tells you the difference between the various forms and types of graphs, trees and networksand shows you step by step calculations on how to solve them by hand (they didn’t have that many computers in 1993). It doesn’t get any better than that. If ypu’re a programming wiz, you can get your own algorithm running in no time. It’s also step-by step illustrated, so you cannot go wrong. It contains exercises and solutions. Solid!
2001/10/31
Risk analysis tends to be a highly mathematically, statistically, and let alone probabilistically oriented science. Risk maps derived from risk analysis often portray only one possible scenario and do not leave much room for personal interpretation. Data on risks and hazards often tend to be heterogeneous, complex, inter-dependent, not directly comparable, and correlated in ways that are not immediately apparent. Visualization technology has emerged as a form of exploratory cartography, which can help explain, analyze and communicate risk. Because the risk analyst and the public in general may differ on what constitutes a risk or what not, visualization techniques can help the risk assessor better understand underlying factors and generate better risk maps, thus communicating a clearer message to the public. Examples of how risk should be communicated are presented and discussed along with current visualizations.
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