Lecture 7: Introduction to Network Analysis

I. Basics of a Network

• Network

  • Interconnected set of points (nodes) and lines (edges)

  • Examples:

    • Information networks

    • Social networks

    • Stream networks

    • Transportation networks

  • Connectivity allows for analysis / problem solving

  • Types of Networks:

    • Utility Networks

      • including water mains, sewage lines, and and electrical circuits. These networks are generally directed.

    • Transportation Networks

      • including roads, railroads, and flight paths. These networks are generally undirected

    • Networks based on social connections

    • 3D Network Datasets

      • Three-dimensional network datasets enable you to model the interior pathways of buildings, mines, caves, and so on.

• Network in GIS

  • GIS networks consist of interconnected lines (known as edges) and intersections (known as junctions) that represent routes upon which people, goods, etc. can travel

  • The object traversing the network follows the edges, and junctions appear when at least two edges intersect

II. Network Dataset in GIS

• Network Dataset

  • Set of nodes connected by lines

  • Represent some type of flow

  • Incorporate flow rules (e.g. time, distance)

  • Rules determine cost and dictate how objects can move through the network

    • Types of rules:

      • Direction - one-way street

      • Barriers

      • Time of day

      • Node restrictions - stroke centers

      • Sequence - stop 1 then stop 2

      • Cost: What is the impact of an object flowing through the network?

• Network Elements

  • Edges

    • connect to other elements (junctions) and are the links over which agents travel

  • Junctions

    • connect edges and facilitate navigation from one edge to another

  • Turns

    • store information that can affect movement between two or more edges

• Network Attributes

  • Properties of the network elements that control traversability over the network

    • the time to travel a given length of road

    • which streets are restricted for which vehicles

    • the speeds along a given road

    • which are one-way streets

    • Cost

      • work as impedances, which penalize traversal over an element in the network. Network datasets must have at least one cost attribute.

    • Descriptor

      • contain general information to calculate the values for other three attributes. For example: Number of lanes, speed limit

    • Restriction

      • prohibit traversing certain edges (roads) in certain directions.

      • Example: One-way Street, closures, etc.

    • Hierarchy

      • differentiates among road types to help network analysis, and it allows a network dataset to assign priority.

      • Example: Highway, Primary road, etc.

    • Connectivity

      • based on geometric coincidences of line endpoints, line vertices, and points and applying connectivity rules that you set as properties of the network dataset

      • if they do not share any coincident endpoints or vertices, no connectivity policy will create a junction at the point of intersection

      • Multimodal network example:

        • street and subway with separate connectivity that joins only at metro entrance

• Network Locations

  • Finding network locations (i.e. stops, barrier)

  • Search tolerance

    

  • Snapping environment

    

III. Network Analysis

• Network Analysis

  • based on the mathematical sub-disciplines of graph theory and topology

  • a set of analysis techniques used with networks (features that are topologically structured, e.g. roads, river, pipeline, cables, etc.)

• Topological Relationship

  • Topology is the arrangement of how point, line, and polygon features share geometry

  • Topology is used for the following:

    • Constrain how features share geometry. For example, adjacent polygons such as parcels have shared edges, street centerlines, and census blocks share geometry, and adjacent soil polygons share edges.

    • Define and enforce data integrity rules: no gaps between polygons, no overlapping features, and so on.

    • Support topological relationship queries and navigation, such as identifying feature adjacency and connectivity.

    • Support editing tools that enforce the topological constraints of the data model.

    • Construct features from unstructured geometry, such as creating polygons from lines

• Network Analysis Workflow

  1. Organize the Network Analysis Settings

  2. Add a dataset in your GIS project working file

  3. Create the Network Analysis Layer

  4. Input Network Analysis Features and Records

     • Add network locations

     • Set analysis properties

  5. Perform analysis and display results

IV. Examples

• Types of Network Analysis

  • Shortest Path / Best Route

    • One common type of network analysis is finding the shortest path between two points

    • In a network of streets, the “shortest” route can either refer to different variables, such as: distance, time, and monetary cost (such as purchasing a plane ticket)

  • Traveling Salesman

    • The traveling salesman is defined as reaching every point in a network in the most efficient way possible

    • It is derived from the idea of a salesperson trying to reach a planned set of cities to sell his or her product in the quickest, most efficient way possible, either through money made, or time

  • Network Partition (Service Area)

    • Network partition is a dividing up of regions in a network to zones or subcategories

    • These regions are sized based on proximity to specific points in a network. This is common for fire stations in metropolitan areas.

  • Closest facility

    • Calculate the nearest X number of facilities to an incident or point of interest

    • Closest can be based on network distance or time

    • Set up a cutoff

      • Find all the hospitals within 5 minutes of an accident

      • Find all the clinics within 2 miles of a home address

  • Origin-destination (OD) cost matrix

    • Creates a cost matrix from multiple origins to multiple destinations

    • Good for calculating distance or time between multiple start and end points

  • Location-Allocation

    • Helps you choose which facilities from a set of facilities to operate based on their potential interaction with demand points

• Other Applications:

  • Transportation Modeling

  • Utility and Infrastructure Management

    • Power Grids - Identifying the shortest path for electricity distribution and detecting power outages

    • Water Supply Networks - Optimizing pipe layouts to ensure efficient water distribution

    • Telecommunications - Finding the best locations for cell towers and routing fiber optic cables

  • Emergency Response and Public Safety

    • Ambulance & Fire Station Coverage - Determining the fastest routes for emergency vehicles

    • Disaster Management - Identifying safe evacuation routes during floods, wildfires, or earthquakes

    • Crime Analysis - Studying movement patterns to predict and prevent criminal activities

  • Environmental Management & Ecology

    • Wildfire Corridors - Identifying safe pathways for animal migration.

    • River & Watershed Networks - Analyzing water flow to predict flooding or pollution spread

    • Deforestation Monitoring - Studying connectivity between forest patches to predict biodiversity

  • Social Network & Human Mobility Analysis

    • Urban Mobility Studies - Understanding how people move through cities to improve public transport

    • Epidemiology (Disease Spread) - Mapping virus transmission pathways (e.g. COVID-19 contact tracing)

    • Market Analysis - Finding the best locations for new businesses based on customer movement patterns

  • Maritime & Aviation Navigation

    • Ship Route Optimization - Avoiding obstacles like reefs, icebergs, and high-traffic zones

    • Air Traffic Control - Managing flight paths to reduce delays and improve safety

    • Search and Rescue Operations - Identifying the most probable locations of missing ships or aircraft