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Rank Size Rule
Settlement
Learning outcomes
 To

understand what the rank Size
rule is and the pattern that it tries to
outline
Rank Size Rule
 This

is an attempt to find a numerical
relationship between population size
of settlements within an area such as
a country or county
 Settlements are ranked in
descending order of population size,
with the largest city first
Assumptions
 The

2nd ranked city will have 1/2 the
population of the 1st
 The 3rd ranked city will have 1/3
population of the 1st
 The 4th ranked city will have a ¼
population of the 1st ranked city
Example
 The

largest city has a population of
1,000,000
 The 2nd largest city: 1,000,000/2=
500,000
 The 3rd city: 1,000,000/3= 333,333
 The 4th city: 1,000,000/4= 250,000
 And so on….
Formula
This allows us to express the rank size rule
as:
 Pn= Pl /n (or R)


Pn= The population of the City
 Pl= The population of the largest city
 N (or R)= The rank size of the city




See graph Page 404/405 Brazil e.g.
Variations from the Rank Size Rule
 It

is rare to find a close correlation
between the city size of a country
and the rank size rule
Primate City
 This

is found where the largest city
(often the capital) completely
dominates a country or region
 The population size will be many
times greater than that of the 2nd or
3rd city
Example of Primate City: Buenos
Aires
 Populations

in thousands:
 Buenos Aires: 10,990
 Cordoba:
1198
 Rosario:
1096
 Mendoza:
775
 La Plata:
640
 San Miguel de Tucuman: 622
Binary Distribution
 Occurs

where there are 2 very large
cities of almost equal size within the
same country. One may be the
capital and the other a major port or
industrial centre
 Examples: Spain- Barcelona and
Madrid
Exceptions to the rule
Rank size rule is more likely to operate in
a country that is developed or urbanised
for a long time
 Large in size
 Stable economic and political organisation
 Primate distribution is likely to occur in
countries that are small, less developed
and only recently urbanised

Understanding the Rank Size Rule of Settlement

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Understanding the Rank Size Rule of Settlement

  • 2. Learning outcomes  To understand what the rank Size rule is and the pattern that it tries to outline
  • 3. Rank Size Rule  This is an attempt to find a numerical relationship between population size of settlements within an area such as a country or county  Settlements are ranked in descending order of population size, with the largest city first
  • 4. Assumptions  The 2nd ranked city will have 1/2 the population of the 1st  The 3rd ranked city will have 1/3 population of the 1st  The 4th ranked city will have a ¼ population of the 1st ranked city
  • 5. Example  The largest city has a population of 1,000,000  The 2nd largest city: 1,000,000/2= 500,000  The 3rd city: 1,000,000/3= 333,333  The 4th city: 1,000,000/4= 250,000  And so on….
  • 6. Formula This allows us to express the rank size rule as:  Pn= Pl /n (or R)  Pn= The population of the City  Pl= The population of the largest city  N (or R)= The rank size of the city   See graph Page 404/405 Brazil e.g.
  • 7. Variations from the Rank Size Rule  It is rare to find a close correlation between the city size of a country and the rank size rule
  • 8. Primate City  This is found where the largest city (often the capital) completely dominates a country or region  The population size will be many times greater than that of the 2nd or 3rd city
  • 9. Example of Primate City: Buenos Aires  Populations in thousands:  Buenos Aires: 10,990  Cordoba: 1198  Rosario: 1096  Mendoza: 775  La Plata: 640  San Miguel de Tucuman: 622
  • 10. Binary Distribution  Occurs where there are 2 very large cities of almost equal size within the same country. One may be the capital and the other a major port or industrial centre  Examples: Spain- Barcelona and Madrid
  • 11. Exceptions to the rule Rank size rule is more likely to operate in a country that is developed or urbanised for a long time  Large in size  Stable economic and political organisation  Primate distribution is likely to occur in countries that are small, less developed and only recently urbanised 