Full text: Proceedings, XXth congress (Part 7)

  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
two-dimensional in general. Today’s technology development 
enabled GIS users to render very complicated and rich 
detailed simulations of various environments over the internet 
in an easy way of interaction and understanding that is not 
currently present in many simulation models. Exceptional than 
others, GeoServNet, provides this ease. GeoServNet, is a 
2D/3D web-based GIS package developed by York University, 
GeoICT Lab. It generates 3D models that can be used as a 
comprehensible interface for querying features, hyper-linking 
web-based information, for analyzing and visualizing model 
results, and accessing different simulation models. 
Furthermore, the addition of a third dimension to our 
knowledge base of modeled features allowed GeoServNet to 
greatly enrich the simulation capacity of predictive models, 
which are very crucial for emergency preparedness 
applications. 
2. 3D VISUALIZATION FOR EMERGENCY 
PREPARDNESS 
2.1 Types of Visualization 
Much of GIS contribution to Infrastructure Protection and 
Emergency Preparedness could be addressed at different levels 
and in various interconnected applications. GIS visualization 
mainly focuses on two domains: computer graphics and GIS 
data. Because of interconnections between the two domains, it 
is not difficult to integrate techniques exploiting the two 
respective domains in terms of 3D application. However, by 
reviewing the recent advances in GIS technology, particularly, 
web-based GIS, it is found that visualization and rendering 
techniques have the largest usage. These developments in 
visualization models are in the following areas: a) interpretive: 
where the user is basically a “reader” who is attempting to 
extract the meaning of the data by visualization. b) Expressive: 
In expressive modeling, the user is an “author” who is 
attempting to convey the meaning of the data through 
visualization, and c) Interactive: where the user integrates both 
interpretive and expressive models to generate and extract the 
meaning. Interestingly, GIS modeling combines the three; 
nevertheless it always depends on the perspective of the 
recipient. 
2.2 3D Web-based GIS Visualization requirements 
Van Driel (1989) recognized that the advantage of 3D lies in 
the way we see the information. The real contribution that 3D 
web-based GIS present for Emergency Preparedness comes 
from its special characteristics. Simply, the purpose of 
interactive web-based visualization is to provide smooth 
navigation through large 3D GIS models. There are basic 
requirements of the visualization process in order for it to be 
used as the basis of the GIS client's user interface. It is very 
necessary for us to have 1) Display quality 2) Stable network 
and system performance 3) Modeling Efficiency 4) 
Interoperability that allow for data and system capabilities 
share with others 5) Reliability to the level that permits of 
having continued analysis. 6) Security, that prevents from 
undesired intrusions. 
Some of the 3D web-based GIS visual models for users 
Infrastructure Protection and Emergency Preparedness include, 
Governmental/municipal authorities require tools to perform 
administrative tasks (including traffic planning, disaster 
preparedness etc.) more efficiently. 3D models also help to 
improve public participation in a decision making process. 
  
  
  
             
  
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Figure 1 showing some applications of 3D Visualization 
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3. CASE STUDY 
Santa Barbara lies on the West Coast of the United States, 148 
km north of Los Angeles and 534 km south of San Francisco. It 
is the largest city in Santa Barbara County. Santa Barbara gains 
special importance due to the distinguished topography of its 
region. It as well falls in a seismic active zone, which puts it 
under earthquake risks. 
  
  
  
  
  
  
Figure 2 showing study area 
3.1 Datasets and Scenario 
Vector datasets represented by obstruction layers. Raster data 
sets in the form of LIDAR imagery and a Digital Elevation 
Model (DEM) were used for conducting this analysis. 
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