Visualizing Patterns in a Global Terrorism Incident Database

10.1068/b3305 ◽  
2007 ◽  
Vol 34 (5) ◽  
pp. 767-784 ◽  
Author(s):  
Diansheng Guo ◽  
Ke Liao ◽  
Michael Morgan

The terrorism database includes more than 27000 terrorism incidents between 1968 and 2006. Each incident record has spatial information (country names for all records and city names for some records), a time stamp (ie year, month, and day), and several other fields (eg tactics, weapon types, target types, fatalities, and injuries). We introduce a unified visualization environment that is able to present various types of patterns and thus to facilitate explorations of the incident data from different perspectives. With the visualization environment one can visualize either spatiomultivariate, spatiotemporal, temporal - multivariate, or spatiotemporal - multivariate patterns. For example, the analyst can examine the characteristics (in terms of target types, tactics, or other multivariate vectors) of aggregated incidents and at the same time perceive how multivariate characteristics change over time and vary spatially. Special attention is devoted to the application-specific data analysis process, from data compilation, geocoding, preprocessing, and transformation, through customization and configuration of visualization components, to the interpretation and presentation of discovered patterns.

Author(s):  
Divya Mishra ◽  

In recent years, road collisions have become a global problem and have been classified as the 10th leading cause of death in the world. Due to the large number of road losses consistently, it has become a major problem in Bangladesh. It is totally unacceptable and sad to allow a citizen to kill in a road accident. The purpose is to show you how to extract logical data from a raw database and visualize it. The results show that hourly planning, day-to-day intelligence, lunar intelligence and year-round planning allow you to look at how road accidents change over time. Two types of road accidents have occurred in particular, and data analysis of road accidents have led to conclusions that will help reduce the number of accidents.


Author(s):  
J. Gehrung ◽  
M. Hebel ◽  
M. Arens ◽  
U. Stilla

<p><strong>Abstract.</strong> Recording an ever-changing urban environment in a structured manner requires sensor deployment planning. In case of mobile sensor platforms, this also includes verifying the terrain navigability. Solving both tasks would usually require different application-specific data structures and tools. In this work, we propose a theoretical framework that provides a uniform representation for spatial information as well as the tools required to combine, manipulate and visualize it. We provide an efficient implementation of the framework utilizing octree-based evidence grids. Our approach can be used to solve complex tasks by combining simple spatial information sources, which we demonstrate by providing simple solutions to the aforementioned applications. Despite the use of a volumetric approach, our runtimes are within the range of minutes.</p>


2009 ◽  
Author(s):  
Brian Garbarini ◽  
Hung-Bin Sheu ◽  
Dana Weber

2010 ◽  
Author(s):  
Sam Nordberg ◽  
Louis G. Castonguay ◽  
Benjamin Locke

2003 ◽  
Author(s):  
M. Spano ◽  
P. Toro ◽  
M. Goldstein
Keyword(s):  
The Cost ◽  

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