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Spatial Information Systems (SIS) COMP 30110 Spatial relations

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Spatial Information Systems (SIS)

COMP 30110

Spatial relations

A

A

B

B

1 Km

A

B

- Topological Relations: containment, overlapping, etc. [Egenhofer et al. 1991]
- Metric Relations: distance between objects, etc. [Gold and Roos 1994]
- Direction Relations: north of, south of, etc.
[Hernandez et al. 1990; Frank et al. 1991]

A

B

- Spatial objects (in a vector-based representation) can be characterised in terms of their spatial relations
- Spatial data in vector format are collections of points, lines, and regions (i.e., subsets of the Euclidean plane). Examples of vector datasets are thematic maps, city maps, digital terrain models (DTMs).
- When stored in a spatial database, usually, lines are approximated by polylines and regions by polygons

- Topological relations are defined using point-set topology concepts, such as boundary and interior
- For example:
- the boundary of a region consists of a set
of curves that separate the region from the

rest of the coordinate space

- The interior of a region consists of all points
in the region that are not on its boundary

- the boundary of a region consists of a set
- Given this, two regions are said to be
adjacent if they share part of a boundary

but do not share any points in their interior

- “Topology matters, metric refines”
- 4-intersection matrix for topological relations between regions (polygons)
- Defined on the basis of intersections between boundary and interior of the two regions A and B involved
b(A) b(B) b(A) i(B)

i(A) b(B) i(A) i(B)

Each entry in the matrix is either empty or non-empty

Example:¬

(

)

(

)

A

B

(

(

(

(

(

)

)

)

)

)

¬

¬ ¬

¬

¬

¬

¬

(

(

(

)

)

)

¬ ¬

¬

¬ ¬ ¬

¬ ¬ ¬ ¬

- Of the 16 (24)configurations we can obtain by assigning values empty/non-empty to each entry in the matrix only 8 are possible for regions without holes

disjoint

contains

inside

equal

covers

coveredBy

overlap

meet

B

B

A

B

A

A

(

)

¬ ¬ ¬ ¬

- Pros:
- simple model
- well accepted

- Cons:
- Does not distinguish between conceptually different situations

- Example:
- All three situations correspond to the same matrix

B

B

A

B

A

A

Use different values for matrix entries

- for example, number of connected components of the intersections can be used to distinguish (1) and (2)

- adding the dimension of each component would distinguish from case (3)

(1)

(2)

(3)

(

)

b(A) b(B) b(A) i(B)b(A) e(B)

i(A) b(B) i(A) i(B) i(A) e(B)

e(A) b(B) e(A) i(B) e(A) e(B)

- 9-intersection matrix for topological relations between generic sets of spatial entities (not just region/region relations): considers interior, boundary, exterior
- NOTE: the boundary of a line consists of its endpoints, the interior of a line consists of all points composing the line excluding its endpoints

(

)

b(A) b(B) b(A) i(B)b(A) e(B)

i(A) b(B) i(A) i(B) i(A) e(B)

e(A) b(B) e(A) i(B) e(A) e(B)

- Entries in the matrix can assume values empty/non-empty or correspond to other properties as seen before
- Several other variations have been defined

- We can consider generic sets of entities (any topological relation allowed) or sets with specific properties/structures
- Overlayed sets: we do not allow for proper intersections among entities
- Non-overlayed set: A and B overlap Overlayed set: the intersection becomes a new polygon and A and B change their shape
- More on overlay operations later

- All relations are possible between pairs of entities
- No specific structure characterises these sets of entities
- Inefficient to maintain topology
- Layered model: use of different levels corresponding to different “meaning”
- Each layer (stored separately) is an overlayed set but different layers can intersect each other
- Example: one layer for road network, one layer for hydrography

intersection (bridge)

- If we consider overlayed sets of entities only disjoint and meet relations are possible between two polygons
- Overlayed sets of entities correspond to plane graphs in which we consider not only nodes (also called vertices) and edges but also the polygons (also called faces) bounded by closed cycles of edges

n1

e1 = (n1,n2)

e2 = …

n8

n2

n9

f1

f2

n3

n10

n7

n6

n5

n4

n11