Compiled with assistance from Gerald White, California State
University, Sacramento
NOTES
This final unit in the spatial databases module looks at
the complex issue of relationships and how they can be coded.
The important concept of planar enforcement, introduced here,
is referred to several times in later units.
UNIT 12 - RELATIONSHIPS AMONG SPATIAL OBJECTS
Compiled with assistance from Gerald White, California State
University, Sacramento
A. INTRODUCTION
- there are a vast number of possible relationships in
spatial data
- many are important in analysis
- e.g. "is contained in" relationship between a point
and an area is important in relating objects to
their surrounding environment
- e.g. "intersects" between two lines is important in
analyzing routes through networks
- relationships can exist between entities of the same type
or of different types
- e.g. for each shopping center, can find the nearest
shopping center (same type)
- e.g. for each customer, can find the nearest
shopping center (different types)
Three types of relationship
1. relationships which are used to construct complex
objects from simple primitives
- e.g. relationship between a line (chain) and the
ordered set of points which defines it
- e.g. relationship between an area (polygon) and the
ordered set of lines which defines it
2. relationships which can be computed from the
coordinates of the objects
- e.g. two lines can be examined to see if they cross
- the "crosses" relationship can be computed
- e.g. areas can be examined to see which one encloses
a given point - the "is contained in" relationship
can be computed
- e.g. areas can be examined to see if they overlap -
the "overlaps" relationship
3. relationships which cannot be computed from
coordinates - these must be coded in the database during
input
B. EXAMPLES OF SPATIAL RELATIONSHIPS
Point-point
- "is within", e.g. find all of the customer points within
1 km of this retail store point
- "is nearest to", e.g. find the hazardous waste site which
is nearest to this groundwater well
Point-line
- "ends at", e.g. find the intersection at the end of this
street
- "is nearest to", e.g. find the road nearest to this
aircraft crash site
Point-area
- "is contained in", e.g. find all of the customers located
in this ZIP code boundary
- "can be seen from", e.g. determine if any of this lake
can be seen from this viewpoint
Line-line
- "crosses", e.g. determine if this road crosses this river
- "comes within", e.g. find all of the roads which come
within 1 km of this railroad
- "flows into", e.g. find out if this stream flows into
this river
Line-area
- "crosses", e.g. find all of the soil types crossed by
this railroad
- "borders", e.g. find out if this road forms part of the
boundary of this airfield
Area-area
- "overlaps", e.g. identify all overlaps between types of
soil on this map and types of land use on this other map
- "is nearest to", e.g. find the nearest lake to this
forest fire
- "is adjacent to", e.g. find out if these two areas share
a common boundary
C. CODING RELATIONSHIPS AS ATTRIBUTES
- in the database model we can visualize relationships as
additional attributes
Example - "flows into" relationship
overhead - Coding relationships as attributes I
- option A:
- each stream link in a stream network could be given
the ID of the downstream link which it flows into
- flow could be traced from link to link by following
pointers
- option B
- alternatively the network could be coded as two sets
of entities - links and nodes
- the links could "point" to their downstream node
- the nodes could "point" to the next downstream link
Example - "is contained in" relationship
overhead - Coding relationships as attributes II
- given:
- locations of 4 wells, with attributes of depth and
flow
- wells lie in two different counties with attributes
of population
- we wish to determine how much flow is available in each
county:
1. find the containing county of each well (compute the
"is contained in" relationship)
- store the result as a new attribute, County, of each
well
2. using this revised attribute table, total flow by
county and add results to the county table
County Population Flow
A 20,000 4,500
B 35,000 5,500
D. OBJECT PAIRS
- distance is an attribute of a pair of objects
- there are other types of information which are similarly
attributes of pairs of objects
- e.g. flow of commuters between a suburb and downtown
- e.g. trade between two countries
- e.g. flow of groundwater between a sink and a spring
- in some cases these attributes can be attached to an
object linking the origin and destination objects
- e.g. on a map, trade can be an attribute of an arrow
connecting the two countries
- thick arrows indicate strong trade
- however, such maps quickly become impossibly complex
- in general, it is necessary to allow for information
which is not an attribute of any one object but of a pair
of objects, including:
- distance
- connectedness - yes or no
- flow of goods, trade
- number of trips
- such attributes cannot necessarily be ascribed to any
real object
- e.g. commuting flows between a suburb and downtown
are not necessarily attributes of any set of links
in the transport network
- e.g. flow of groundwater between a sink and a spring
does not necessarily follow any aquifer or conduit
- these are attributes of object pairs
- object pairs are important in various kinds of spatial
analysis using GIS
- attributes of object pairs can be thought of as tables
which have one object as rows and the other object as
columns with the values in each cell representing the
value of the interaction between them
- are many different terms for the implementation of
this concept - e.g. interaction matrix, turn table,
Cartesian product
E. CARTOGRAPHIC AND TOPOLOGICAL DATABASES
Strict definition of "topological"
- if a map is stretched and distorted, some of its
properties change, including:
- distances
- angles
- relative proximities
- other properties remain constant, including:
- adjacencies
- most other relationships, such as "is contained in",
"crosses"
- types of spatial objects - areas remain areas, lines
remain lines, points remain points
- strictly, topological properties are those which remain
unchanged after distortion
Usage of "topological" in GIS
- a spatial database is often called "topological" if one
or more of the following relationships have been computed
and stored
- connectedness of links at intersections
- ordered set of lines (chains) forming each polygon
boundary
- adjacency relationships between areas
- unfortunately the precise meaning of the term has become
distorted by use
- in general, "topological" implies that certain
relationships are stored, making the data more useful for
various kinds of spatial analysis
- by contrast, a database is called "cartographic" if the
above conditions are absent
- objects can be manipulated individually
- relationships between them are unavailable or are
considered unimportant
- cartographic databases are less useful for analysis of
spatial data
- however they are satisfactory for simple mapping of
data
- many packages designed for mapping only use
cartographic database models
- a cartographic database can usually be converted to
a topological database by computing relationships -
the process of "building topology" through planar
enforcement
F. PLANAR ENFORCEMENT
- objects and their attributes are capable of describing
the conditions existing on a map or in reality
- variation of a single property like soil type or
elevation over a mapped area is achieved by including
appropriate attributes for entity types
- e.g. elevation described by giving attributes to
elevation points
- e.g. soil type described by giving attributes to
areas
- in cases like soil type, the objects used to describe
spatial variation must obey certain simple rules
- e.g. two areas cannot overlap
- e.g. every place must be within exactly one area, or
on a boundary
- these rules are collectively referred to as planar
enforcement
- a set of objects obeying these rules is said to be
planar enforced
- planar enforcement is a very important operation in a
vector GIS
Process
- begin with a number of unrelated line segments
- imagine a number of limp spaghetti noodles lying on
a table
- the following elements are now defined (terminology from
the US Census Bureau for development of digital spatial
database concepts):
overhead - Planar enforcement
- a 0-cell (or node) is identified wherever two
noodles cross or a noodle terminates
- i.e. all intersections are calculated
- 1-cell (or link, also "chain", "arc", "edge") is
identified for each length of noodle between two
consecutive 0-cells (nodes)
- a 2-cell (or area, also "face", "polygon") is
defined for each group of consecutive 1-cells
forming an enclosed area that does not contain any
1-cells that are not part of the boundary
- note that these definitions relate directly to the
ordinary concept of dimensionality
- the results are:
- 0-cells are either isolated ("points") or adjacent
to one or more 1-cells ("nodes")
- all 1-cells end in exactly two 0-cells
- each line segment (chain) between adjacent 0-cells
is assigned to exactly one 1-cell
- all 1-cells lie between exactly two 2-cells
- every place on the "map" between noodles is assigned
to a single 2-cell (the rest of the world is a 2-
cell as well, often given the ID zero)
Objective
- planar enforcement is used to build objects out of
digitized lines (hence the phrase "building topology")
- it is a consistent and precise approach to the
problem of making meaningful objects out of groups
of lines
- simple rules can be used to correct some digitizing
errors:
- a very short 1-cell terminating in a 1-valent 0-cell
indicates an overshoot
diagram
- a long 1-cell terminating in a 1-valent 0-cell very
close to another 1-cell indicates an undershoot
diagram
- planar enforcement is often needed when a set of data is
being imported from another system
- e.g. if the source is a cartographic database and
needs to have relationships computed
- e.g. if the database models of the two systems are
incompatible, data is transferred as unrelated
noodles, then objects are rebuilt
- planar enforcement must be applied one layer at a time
- planar enforcement concepts are built into many systems
G. RELATIONSHIPS IN RASTER SYSTEMS
REFERENCES
Burrough, P.A., 1986. Principles of Geographical Information
Systems for Land Resources Assessment. Clarendon,
Oxford. Chapter 2 describes objects, attribute tables
and relationships.
Goodchild, M.F., 1988. "Towards an enumeration and
classification of GIS functions," Proceedings, IGIS '87.
NASA, Washington DC 2:67-77. Defines and discusses
object pairs.
Keating, T., W. Phillips and K. Ingram, 1987. "An integrated
topologic database design for geographic information
systems," Photogrammetric Engineering and Remote Sensing
Vol. 53. Good discussion of topological and cartographic
database models.
EXAM AND DISCUSSION QUESTIONS
1. Discuss the use of planar enforcement for street
networks, and the problems presented by overpasses and
underpasses. Can you modify the basic rules to maintain
consistency but allow for such instances?
2. What additional examples of relationships can you devise
in each of the six categories used in section B?
3. Why have designers of raster GIS not commonly devised
ways of coding spatial relationships between objects in
their systems? Is this likely to change in the future, and
if so, why?
4. "Topology is what distinguishes GIS from automated
cartography". Discuss.
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Last Updated: August 30, 1997.