define gis, transportation and type

1. Presented by :
Chinmoy maji
Supervised by :
Department of Geography,
Ranchi College,
Ranchi, Jharkhand

3. Outline
Introduction: What is GIS-T?
Differences between GIS and other Systems
Unique Properties of Geographic Information
GIS Models Used in Transportation
Challenges for GIS-T
Conclusions

4. What is GIS-T
Geographic information systems for transportation (GIS-
T) are interconnected hardware, software, data, people,
organizations, and institutional arrangements for
collecting, storing, analyzing, and communicating
particular types of information about the Earth.
These particular types of information are transportation systems
and geographic regions.

5. What is GIS-T
GIS-T as the merger of an enhanced GIS and enhanced
transportation information system (TIS)
(Reference:Vonderhoe et al., 1993)
GIS TIS
GIS-T

6. Some applications:
infrastructure planning, design and management
traffic safety analysis
transportation impact analysis
public transit planning and operations
intelligent transportation systems (ITS)
 Advanced Traveller Information Systems (ATIS)
 Commercial Vehicle Operations (CVO)
 Incident Detection Management

8. Differences between GIS and other Systems
Multi-functionality
Geo-visualization capability
 makes GIS different from a usual database management
engine;
Analytical capability
 makes GIS different from an automated mapping application;
Database management features
 enables GIS to capture spatial and topological relationship
between geo-referenced entities if these relationships were not
pre-defined.

9. Differences between GIS and other Systems
The major difference between GIS and other database
management systems (DBMS) is mainly in the way
information is referenced rather than the nature of
information handled
 both systems may contain exactly the same information!

10. Road Map

12. Unique Properties of Geographic Information
Spatial dependency
The tendency for things closer in geographic space to
be more related
i.e., it is meaningful to record, organize and analyze
data by geographic location.
Spatial heterogeneity
The tendency of each location in geographic space to
show some degree of uniqueness
i.e., it is valuable to consider local geographic context
rather than just global generalities

13. GIS Models Used in Transportation
Field models of the continuous variation of a phenomenon over
space (e.g., land elevation)
 Discrete models, depending on which discrete entities (points, lines
or polygons) populate space (e.g., toll barriers, urbanized areas)
Network models to represent topologically-connected linear entities
(e.g., roads, rail lines) that are fixed in the continuous reference
surface

14. GIS Models Used in Transportation
All of these three models are useful in transportation
The network model built around the concept of arc and
node plays the key role in this application domain
because single- and multi-modal infrastructure networks
are vital in enabling and supporting passenger and
freight movement.
In fact, many transportation applications only require a
network model to represent data.

15. GIS Models Used in Transportation
The need for these and other extensions to the
base network model is not universal and is
dependent to the type of the project.
There are several data modelling, data
manipulation, and data analysis that were not
supported by conventional GIS and currently are
fulfilled by GIS-T software.

16. Challenges for GIS-T
Legacy data management system
Transportation agencies keep comprehensive inventories of the
transportation infrastructure, and its condition and usage by the
public.
Each TIS handles a single type of information (e.g., highway
planning network, pavement management system) with its own data
and its own hardware and software platform.
Shortcomings
 Data integration, i.e. to transfer disparate data into a unified data
management system.
Some of the options available
 generic relational data models, new dynamic segmentation data standards, and
object-oriented data models.

17. Challenges for GIS-T
Transportation data are maintained by different agencies and
private data providers
Each data source has its own data model
Accuracy across data sets is varied
Typical errors
 Data position, topology, naming and attributing
Shortcomings
 Algorithms for map matching
 Models of error and error spread in transportation data
 Data quality standards and data exchange standards
Typical applications
 Commercial Vehicle Operations (CVO)
 Advanced Traveller Information Systems (ATIS)

18. Challenges for GIS-T
Real-time GIS-T
Real-time traffic data is currently available in many areas
It can be a primary input of world-wide-web applications
However, it does not meet the needs of society when it comes to geo-
referenced data
Shortcomings
 Quicker access data models
 More powerful spatial data combination techniques
 More powerful dynamic routing algorithms

19. Challenges for GIS-T
Large data sets
Transportation problems are complex due to
 Large amounts of geo-referenced data
 Large networks
The complexity combines with difficulty to visualize information on
the single dimension of a network
Shortcomings
 pioneering system designs in order to optimizing
 speed and accuracy of the display of information
 the run time of algorithms and analytical tools of network analysis

20. Challenges for GIS-T
Distributed computing
Advances in Internet technology have made computing mobile,
distributed and widespread.
Internet GIS applications are currently accessible and common
 Real-time transit route and schedule information
 Traffic information
Shortcomings
 More powerful analytical tools to fit
 the limited distributed computing resources, and
 limited bandwidth on communication networks
 Novel design of system architectures to make efficient use of local and
remote computing resources
 Geo-referencing of remote service users and real-time tracking of their
movements

21. Conclusions
GIS-T provides the core technology for planning, deploying,
operating, and optimizing transportation systems.
It has opened up new horizons in transportation planning and
engineering.
It has developed an essential tool for the most effective use of spatial
data.
It provides a means of communication for an interactive
understanding between the public and transportation professionals.
Still, this technology is facing a lot of challenges to adjust itself with
the complexity of transportation data analyses.

22. Thank You!