Geographic Information System (GIS) Applications in Transportation Systems Engineering / Planning training course is set to deliver a comprehensive understanding of the fundamentals of Geographic Information System (GIS) and introduce transportation infrastructure and road safety-related data collection, and analytical methodologies and techniques utilizing Geographic Information System (GIS).
Authorities in many developed countries now actively use Geographic Information Systems (GIS) for highways and transport management, mainly due to the benefits of falling costs and increasing ease in planning, monitoring, and managing complex systems involved in transportation planning and management, accident analysis, and route planning.
The Geographic Information System (GIS) tools and techniques significantly aid in determining capacity enhancements, improving operations, and identifying the most strategic investments for keeping the transportation system in any country running optimally. This training course is designed not only to cover the technical aspects of how to use a Geographic Information System (GIS) but also to develop critical spatial thinking and spatial decision-making skills.
- Traffic & Transportation Engineers and Professionals.
- Professionals in Urban Planning and Development.
- Project Managers in Infrastructure Solutions Consulting.
- Data Analysts, Technicians in Traffic Management Centers.
- Researchers and Consultants.
- Practitioners in Traffic and Transport Engineering.
- Traffic Safety Professionals.
- Highway and Roadway Design Engineers.
At the end of this course the participants will be able to:
- Have a thorough understanding of how Geographic Information System (GIS) can help in transportation studies.
- Identify trends in traffic operations and safety performance measures, leading to improvement in transportation safety.
- Detect root causes of traffic incidents and determine effective countermeasures.
- Evaluate the performance of segments, corridors, networks, or regions.
- Pinpoint hot and cold spots via density estimation heat mapping.
- Conduct complex spatial analysis required to plan the transportation systems of the future.
- Build dynamic and rich mapping applications.
- Gain critical spatial thinking skills and become confident in spatial decision making.
- Fundamentals and Major Functions of Geographic Information System (GIS).
- Geospatial Data, Database, and Geo-Referencing Techniques.
- Visualization and Geographic Information System (GIS) Data Query.
- Spatial Analysis and Modeling.
- Multilayer Mapping and Overlay Analysis.
- Heat Maps and Hotspot Analysis.
Unit 1: Geographical Information Systems (GIS) Fundamentals:
- Geographic Information System (GIS) Applications in General
- Geographic Information System (GIS) Applications in Transportation Studies
- Major Functions of Geographic Information System (GIS)
- Relating Information from Multiple Sources
- Geographic Data and the Database
- Data Acquisition
- Data Integration
- Data Structure
- Data Modeling
- ArcMap Practice
Unit 2: Understanding Geographic Information System (GIS) Maps:
- Data Information
- Spatial data
- Geographic Information System (GIS) Database
- Raster vs. Vector Data
- GIS Shapefiles
- ESRI Shapefile format
- Displaying and Navigating Geographic Information System (GIS) Maps
- Feature Attributes
- Census Units
- The Point, Line, Polygon Data
Unit 3: Data Collection:
- Global Positioning System (GPS)
- Geographic Data Library
- Census Data
- Transportation Data and Analytics with Geographic Information System (GIS)
- Geospatial Crash Analysis
Unit 4: Visualization and Data Processing:
- Symbolizing and Labeling Geographic Information System (GIS) Data
- Continuous and Categorical Data
- Classification Methods
- Geographic Information System (GIS) Data Query
- Identify, Select, Find
- Select Features by Attributes
- Joining and Relating Tables
- Spatial Joining
- Dissolving and Clipping layers
Unit 5: Geospatial Analysis and Hotspot Analysis:
- Introduction to Spatial Analysis
- Buffering Features
- Overlaying Data
- Spatial Analysis Methods to Identify Hotspots
- Fishnet-based Analysis
- Kernel Density Estimation