Massachusetts Institute of Technology - Department of Urban Studies and Planning

11.188: Urban Planning and Social Science Laboratory
11.520: A Workshop on Geographic Information Systems

Network Analysis + Project Work

April 21, 2021

Administrative

  • We hope you are healthy and refreshed after the long weekend
    • The break did end with the verdict in the trial for George Floyd's murder
    • That was a sober reminder of both the possibilities and obstacles to seeking racial justice in America
  • Lab #6: Part 1 is due today, Part 2 due next Monday, April 26
  • Project work: After a brief lecture on network analysis, we will focus on project work today
    • Feedback is on Stellar
    • We will use breakouts today and office hours Thursday & Friday
      • for one-on-one discussion of project plan and finding/evaluating data.



Network Analysis - Expand discussion of  Network Analysis tools from previous lecture
  • Encoding proximity using a network (or graph) model, facilitates certain types of connectivity analyses
    • Find shortest path along streets from Point A to Point B
    • Find shortest path through N cities (Traveling Salesman problem)
    • How far can you get in 30 minutes
  • Many transportation analyses use network data models
  • Many hydrological analyses use network data models (runoff, flow, ...)
  • Additional information on Network Analyst below


Network Example: using US Census Bureau, TIGER Line Files

  • Geocoding Strategy using TIGER files (from earlier lecture notes)
    • Encode road network as street centerlines links connecting nodes (usually intersections)
    • Attach address information to each street segment
    • Use 'in reverse' to match street address to street segment to get approximate X,Y location
  • TIGER: Topologically Integrated Geographic Encoding and Referencing system
  • Illustrative Example

    • Street centerline road segments
    Attaching address ranges to road segments

 

How do GIS systems model Networks?

A network is a system of linear features connected at nodes
E.g, nodes might be where three or more street segments intersect.
The linear feature connecting any given pair of nodes is called an arc, or network link.
Each arc on a network is represented as an ordered pair of nodes, from node i to node j, denoted by (i, j), and thus has direction.
A network representation that is good for transportation modeling may differ from a geographically accurate representation of the physical road (e.g., street centerline, handling exit ramps, 3D overpasses, etc.)
Combining two network models can be hard
    -- How do you handle lanes, exit ramps, and overpasses?

    Other basic elements of a network:

A shortest path is the shortest (or least 'cost' path) from a source node (origin) to a destination node.  In practice, pathfinding seeks the shortest or most efficient way to visit a sequence of locations.

A tour is an enclosed path; that is, the first node and the final node on the path are the same node on the network.

A stop is a location visited along a path or a tour.

Events or locations may be viewed as collection points (e.g., 'origins' or 'destinations' ) where certain resources are supplied or consumed.

A turn on a network is the transition from one arc to another arc at a node (there are 16 ways in which two intersecting (one-lane) roads can allow vehicle flow among the 4 links that 'connect' to the one node).

'Location-allocation' models often use network representation of connected places in order to determine the optimal locations for a given number of facilities (e.g., stores, restaurants, banks, factories, warehouses, libraries, hospitals, post offices, and schools) based on some criteria for assigning people to the the 'nearest' facility.

  • For Lab #6, you use the GoogleWay API to run their shortest path algorithm to compute the walking distance from 'home' to each restaurant (obtained using Yelp points of interest). 


Useful tools for 'publishing' project work     


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