GIS-T
GIS and Transportation
• In general, topics related to GIS-T studies
can be grouped into three categories:
– GIS-T data representations,
– GIS-T analysis and modeling, and
– GIS-T applications.
GIS-T data representations
• The most common representation used is
comprised of:
– Traditional arc-node (point, line, polygon)
layers with topology
– A 1-D offset measurement system known as a
linear referencing system
– Dynamic segmentation as an enabling tool for
assigning multiple attribute sets over a single
linear feature
GIS-T Data Layers
Source: http://www.dot.state.ia.us/gis/info_page.htm
GIS Topology and
Planar Enforcement
• Mathematical topology assumes that geographic features occur on a
two-dimensional plane. Through planar enforcement, spatial
features can be represented through nodes (0-dimensional cells);
edges, sometimes called arcs (one-dimensional cells); or polygons
(two-dimensional cells). Because features can exist only on a plane,
lines that cross are broken into separate lines that terminate at
nodes representing intersections rather than simple vertices.
• In GIS, topology is implemented through data structure. An ArcGIS
coverage is a familiar topological data structure. A coverage
explicitly stores topological relationships among neighboring
polygons in the Arc Attribute Table (AAT) by storing the adjacent
polygon IDs in the LPoly and RPoly fields. Adjacent lines are
connected through nodes, and this information is stored in the arcnode table. The ArcTools commands, CLEAN and BUILD, enforce
planar topology on data and update topology tables.
Why topology is important in GIS:
Source: http://www.esri.com/news/arcuser/0401/topo.html
• Location Referencing System (LRS) – A location
referencing system is a set of automated procedures
used to manage the collection, storage and access of
location referencing information. The system includes
the integration of location referencing methods, such as
mileposts, milepoints, stationing, and geographic
positioning. When the location takes place along a road,
railroad or river, location referencing is often referred to
as linear referencing. The development of linear
referencing systems continues to be a primary effort at
DOTs around the world.
One of the weaknesses of linear referencing is that the spatial description of the
event data is based on a dynamic linear network. Suppose that there is a
realignment on a road that reduces the length of the road by a half mile. If the
measurement attributes of the road are updated to reflect this new length, all of
the ‘measure-referenced’ event data that occurs on segments “downstream” from
the realignment will mysteriously move “downstream” by a half mile. This is not
the desired result! If an event, such as a traffic accident, happened at a certain
spot, you want it to stay there!
• Most every organization that captures and analyzes
transportation information uses more than one Linear
Referencing Method (LRM). Examples of LRMs
commonly used are County Milepost, Engineering
Stationing, and Street Addresses. In a County Milepost
LRM, the LRS keyset may consist of County and Route
number attributes, and the measurements are in miles.
In an Engineering Stationing LRM, the LRS keyset may
consist of Project number and Route number attributes,
and the measurements are in feet. In a Street Address
LRM, the LRS keyset may consist of Street Prefix, Street
Name, Street Type, and Street Suffix attributes, and the
measurements are unitless.
• There are a number of approaches that are commonly
used for handling a multiple LRM system, most of which
have major disadvantages. One is to use one set of
geometry, but to carry as attributes on that geometry all
of the keyset and measurement attributes needed for all
of the supported LRMs. This necessitates that the
geometry be segmented at every change in attribution
for every LRM. This makes maintenance of the LRS
quite a chore. Another way is to have separate geometry
for each LRM. This increases the storage needs, but,
more importantly, it necessitates that any geometry
change be made multiple times, once for each LRM.
“Pathological transportation segments”
• What to do with overpasses? Planar enforcement explicitly “forbids”
such features, yet they are common in transportation networks.
• A discontinuous route occurs when designated or logical routes stop
and start, creating gaps.
• Dog-leg routes occur when designated or logical routes share
common sections of a physical transportation facility. A decision
must be made with respect to the assignment of events to individual
routes along the shared sections unless there is some administrative
reason to assign the event to only one of the traversals.
• The split road problem occurs when divided highways have two
roadways of unequal length.
• Cul-de sacs (i.e., a street closed at one end with a circular feature;
these are often found in residential areas) can create problems
since offset measurements can be arbitrary or nonunique.
• Ramps are often transitions among routes and therefore must be
dealt with in a special manner.
• Dynamic Segmentation (dynseg) is a classic GIS
tool for analysis of roads, pipelines and railroads
used in transportation and utility network
applications. The dynamic segmentation process
generates point or linear geometry for database
record events referenced by their position along
a linear feature. Using dynseg, information
originally stored in a tabular report can be
visualized on a map and displayed, queried and
analyzed in a GIS.
Source: Intergraph’s White Paper on GeoTrans: Transportation Data Model
Dynamic segmentation uses a linear referencing system to define a common datum for
referencing the linear lines that the DOT would call roads. The DOT may use the
mileposts to reference that system
Here, the mileposts are not shown, but each data type (speed limit, AADT, pavement type, and skid value)
is stored independently and only merged when queried upon. Notice that the resulting segments from the query
are new lengths of road that do not exist anywhere else in the data.
Source: http://www.dot.state.ia.us/gis/info_page.htm
GIS-T analysis and modeling
• GIS-T applications have benefited from many of the standard GIS
functions (query, geocoding, buffer, overlay, etc.) to support data
management, analysis, and visualization needs. Like many other
fields, transportation has developed its own unique analysis
methods and models. Examples include
– shortest path and routing algorithms (e.g., traveling salesman problem, vehicle
routing problem),
– spatial interaction models (e.g., gravity model), network flow problems (e.g., user
optimal equilibrium, system optimal equilibrium, dynamic equilibrium), (PPT)
– facility location problems (e.g., p-median problem, set covering problem, maximal
covering problem, p-centers problem),
– travel demand models (e.g., the 4-step trip generation model: Trip Generation
Model, Trip Distribution Model, Mode Split Model, Trip Assignment Model, and
– land use-transportation interaction models.
• While the basic transportation analysis procedures (e.g., shortest
path finding) can be found in most commercial GIS software, other
transportation analysis procedures and models (e.g., facility location
problems) are available only selectively in some commercial
software packages.
GIS-T applications
• Many GIS-T applications were implemented at
various transportation agencies in the past two
decades:
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infrastructure planning, design and management,
transportation safety analysis,
travel demand analysis,
traffic monitoring and control,
public transit planning and operations,
environmental impacts assessment,
hazards mitigation, and
intelligent transportation systems (ITS).
• Each of these applications tends to have its
specific data and analysis requirements. For
example, representing a street network as
centerlines and major intersections may be
sufficient for a transportation planning
application. A traffic engineering application,
however, may require a detailed representation
of individual traffic lanes. Turn movements at
intersections also could be critical to a traffic
engineering study, but not to a region-wide travel
demand study.
• Examples of GIS-T applications:
• http://www.ctre.iastate.edu/educweb/ce352/lec24/gista.htm
• Intelligent Transportation Systems
There is obviously lots to learn about GIS-T,
and we have only touched upon a very
limited selection of topics. We could
dedicate an entire course to the subject
(and many people do!).