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Geographical Entities
Topology
• The spatial relationships between points,
lines, and polygons
• Determines
– Distance between points
– Whether lines intersect
– Whether points, lines, or polygons are within the
extent of a polygon
Figure 2.22. Examples of adjacency, connectivity, and containment.
Adjacent polygons Connected stream
network
One polygon contained inside
another polygon
Spatial Measurement Levels
• Nominal Scale
• Ordinal Scale
• Interval/Ratio Scale
• NOMINAL SCALE
• The system allows us to make statements about what to call the object, but it does not
allow direct comparisons between one named object and another .
• Ex. Church is better than fire station
• apples and banana
• ORDINAL SCALE
• Ordinal variables are those variables which are lists in discrete classes but with an
inherent order .
• Ex. Classes of Streams ,like I order and II order
• Ordinal Data can give us some insights into logical comparisons of spatial objects
,but comparisons are limited to the specific spectrum that serves as the basis of the
questions we are asking .
• INTERVAL /RATIO SCALE
• The numbers are assigned to the items measured .Data measured can be compared as
in the case of ordinal scale of measurement
• Ex. Soil Temperatures across a study area containing widely different soil types
• The Ratio variables have the same characteristic as interval variables but they have
natural Zero or a straight point .
• Ex. Rainfall per a month
•
Geographical entities,Topology

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Geographical entities,Topology

  • 1.
  • 3. Topology • The spatial relationships between points, lines, and polygons • Determines – Distance between points – Whether lines intersect – Whether points, lines, or polygons are within the extent of a polygon
  • 4. Figure 2.22. Examples of adjacency, connectivity, and containment. Adjacent polygons Connected stream network One polygon contained inside another polygon
  • 5.
  • 6. Spatial Measurement Levels • Nominal Scale • Ordinal Scale • Interval/Ratio Scale
  • 7.
  • 8. • NOMINAL SCALE • The system allows us to make statements about what to call the object, but it does not allow direct comparisons between one named object and another . • Ex. Church is better than fire station • apples and banana • ORDINAL SCALE • Ordinal variables are those variables which are lists in discrete classes but with an inherent order . • Ex. Classes of Streams ,like I order and II order • Ordinal Data can give us some insights into logical comparisons of spatial objects ,but comparisons are limited to the specific spectrum that serves as the basis of the questions we are asking . • INTERVAL /RATIO SCALE • The numbers are assigned to the items measured .Data measured can be compared as in the case of ordinal scale of measurement • Ex. Soil Temperatures across a study area containing widely different soil types • The Ratio variables have the same characteristic as interval variables but they have natural Zero or a straight point . • Ex. Rainfall per a month •