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The Size & Distribution
of Cities

Explore how cities vary in population size, why some grow into megacities while others stay small, and the models geographers use to explain urban hierarchies.

AP Human Geography

What Is an Urban Hierarchy?

Cities are not all the same size. In every country, a few large cities sit at the top of the hierarchy, while many smaller cities and towns fill the base. This pattern of size distribution is one of the most consistent findings in geography.

Megacity
A city with more than 10 million people (e.g., Tokyo, Lagos)
Metacities
Urban areas exceeding 20 million, often spanning multiple jurisdictions
World Cities
Global command centers for finance, culture, and politics (e.g., London, New York)

Why City Size Matters

Understanding urban size distribution helps geographers and policymakers predict migration patterns, allocate infrastructure investment, and assess how economic development spreads across a country.

Measuring City Size

City Proper
Population within the official political boundary of a municipality
Metropolitan Area
The urban core plus surrounding suburbs that are economically linked
Megalopolis
A chain of overlapping metro areas (e.g., BosWash corridor: Boston to Washington D.C.)

The Rank-Size Rule

Proposed by George Zipf, the rank-size rule states that in an ideal system, a city's population is inversely proportional to its rank among all cities in a country:

If the largest city has 10 million people, the 2nd city should have about 5 million, the 3rd about 3.33 million, and so on.

Visualizing the Rank-Size Rule

Population (millions) City Rank 10 8 6 4 2 1 2 3 4 5 6 7 10M 5M 3.3M 2.5M 2M Ideal Rank-Size Distribution

The Primate City Concept

Mark Jefferson (1939) observed that in many countries, the largest city is disproportionately larger than the second-largest: at least twice the size and more than twice as significant culturally and economically.

Primate City vs. Rank-Size

Primate City Pattern 10M 3.5M 2.5M 1st 2nd 3rd vs. Rank-Size Pattern 10M 5M 3.3M 1st 2nd 3rd
Primate City Rank-Size
Distribution One city dominates Smooth hierarchy
2nd City Size < half of 1st ≈ half of 1st
Typical Countries UK, France, Thailand USA, Brazil, India
Development Often developing nations Often large/mature economies

Christaller's Central Place Theory

Walter Christaller (1933) proposed that cities exist to provide services to surrounding areas. Larger cities offer more specialized services and serve wider market areas, while smaller towns provide everyday goods to nearby residents.

Threshold
The minimum population needed to support a service or business
Range
The maximum distance consumers will travel to obtain a good or service

Hexagonal Market Areas

Large City Medium Medium Medium Higher-order Medium-order Lower-order

The Gravity Model

Inspired by Newton's law of gravitation, the gravity model predicts the interaction between two cities based on their populations and the distance between them:

Larger Pop. →
More interaction: bigger cities attract more flows of people, goods, and ideas
Greater Dist. →
Less interaction: distance acts as friction, reducing flows between cities

How to Analyze City Distribution

1
Identify the largest city. Find its population and its dominance relative to other cities.
2
Compare 1st and 2nd cities. If the largest is > 2× the second, it may be a primate city.
3
Test the rank-size rule. Calculate \( P_1 / n \) for each rank and compare to actual populations.
4
Consider context. Colonialism, political centralization, and economic history explain why patterns differ.
5
Apply the gravity model. Predict interaction strength between any city pair using \( P_1 \times P_2 / d^2 \).

Example: Rank-Size in Country X

Country X's largest city has a population of 8 million. If the rank-size rule applies, predict the populations of the 2nd through 5th largest cities.

Rank Formula Predicted Population
1st \( 8{,}000{,}000 / 1 \) 8,000,000
2nd \( 8{,}000{,}000 / 2 \) 4,000,000
3rd \( 8{,}000{,}000 / 3 \) 2,667,000
4th \( 8{,}000{,}000 / 4 \) 2,000,000
5th \( 8{,}000{,}000 / 5 \) 1,600,000

Example: Is Bangkok a Primate City?

Thailand's largest cities by population:

10.7M Bangkok 1.2M Nonthaburi 0.8M Pak Kret 0.7M Hat Yai

Example: Gravity Model Calculation

City A has 500,000 people and City B has 200,000 people. They are 100 km apart. City C has 500,000 people and is 200 km from City A. Which pair interacts more?

A ↔ B
\( I = \dfrac{500{,}000 \times 200{,}000}{100^2} = \dfrac{10^{11}}{10^4} = 10{,}000{,}000 \)
A ↔ C
\( I = \dfrac{500{,}000 \times 500{,}000}{200^2} = \dfrac{2.5 \times 10^{11}}{4 \times 10^4} = 6{,}250{,}000 \)

Common Mistakes

✕ Confusing Primate with Largest
A primate city isn't just the biggest city: it must be disproportionately larger (at least 2× the second) and dominate national life.
✕ Rank-Size = Every Country
The rank-size rule is a statistical regularity, not a universal law. Many countries deviate significantly, especially smaller or formerly colonial ones.
✕ Forgetting Distance Is Squared
In the gravity model, distance is in the denominator squared. Doubling distance reduces interaction by 4×, not 2×.

Key Models Summary

Model Key Idea Formula / Rule Best Example
Rank-Size Rule Smooth hierarchy \( P_n = P_1 / n \) USA, Brazil
Primate City One dominant city \( P_1 > 2 \times P_2 \) UK, Thailand
Central Place Service hierarchy Hexagonal markets Flat farmlands
Gravity Model Interaction strength \( P_1 P_2 / d^2 \) Trade flows

Question 1 of 5

According to the rank-size rule, if a country's largest city has 12 million people, what is the expected population of the 4th-largest city?

Question 2 of 5

Which of the following best describes a primate city?

Question 3 of 5

In the gravity model, what happens to the predicted interaction between two cities if the distance between them is tripled?

Question 4 of 5

Christaller's central place theory assumes hexagonal market areas rather than circular ones because:

Question 5 of 5

A country has the following largest cities: Capital (15M), City B (2M), City C (1.5M), City D (1.2M). This pattern most closely reflects: