AP Syllabus focus:
‘The gravity model estimates interaction between places based on population size and distance, helping predict travel, trade, and service use.’
The gravity model helps geographers predict how strongly cities interact by examining how population size increases connection potential while distance reduces it, shaping movement, trade, and spatial behavior.
Gravity Model: Predicting Interaction Between Cities
The gravity model is a fundamental tool in urban geography for explaining why some urban areas interact more intensely than others. It draws on the idea that larger cities generate stronger economic, social, and transportation connections, while greater distance weakens these interactions. The model is widely used because it simplifies complex urban interactions into measurable components.
Gravity Model: A spatial model that predicts the level of interaction between two places based on their population sizes and the distance between them.
The model helps explain why individuals may commute to a large metropolitan center for work, why goods often move along specific corridors, or why certain cities emerge as regional hubs. Interactions are not randomly distributed; instead, they follow systematic patterns that reflect demographic and spatial conditions.
Foundations of the Gravity Model
The gravity model is based on an analogy with Newtonian physics, applying the idea that larger masses exert stronger gravitational pull. In human geography, the “mass” corresponds to population size or, in some cases, economic strength, while distance acts as friction that discourages movement.
This inverse relationship between distance and interaction is known as distance decay, a core idea built into the gravity model.
This diagram illustrates distance decay, showing that nearby points interact and resemble one another more than far-away points. The yellow arrows emphasize how similarity and interaction diminish as distance increases. Although not specific to cities, the principle applies directly to urban spatial interaction in the gravity model. Source.
Distance Decay: The principle that interaction between two places decreases as the distance between them increases.
Core Components of the Gravity Model
The gravity model relies on two critical variables emphasized in the AP specification: population size and distance. To use the model effectively, students must understand how each variable shapes spatial interaction.
Population
Larger populations create greater demand for goods and services.
Large cities also generate more economic, cultural, and social opportunities that attract flows of people and resources.
When two large cities are paired, their combined “pull” is significantly stronger.
Distance
Distance operates as a frictional force.
Longer distances increase travel time, shipping costs, and communication barriers.
As distance increases, interaction decreases, even between large cities.
= Population of City 1 (people)
= Population of City 2 (people)
= Distance between the cities (miles or kilometers)
= Distance decay exponent representing how strongly distance reduces interaction
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How the Gravity Model Predicts Urban Interaction
The gravity model is used to interpret a range of urban processes. Its predictive power comes from its ability to translate demographic and spatial characteristics into meaningful measures of connectivity. By comparing predicted interaction values across cities, geographers can identify which urban centers will likely dominate regional systems.
Key Predictive Applications
Travel flows
Predicting commuting patterns between suburbs and core cities.
Estimating passenger flows between airports and regional transit hubs.
Trade patterns
Identifying likely trade partners within a regional or national economy.
Forecasting freight movement along transportation corridors.
Service use
Estimating how far people will travel to access hospitals, universities, or major retail centers.
Assessing the geographic reach of professional services concentrated in major cities.
Urban hierarchy and dominance
Demonstrating why primate cities concentrate interactions.
Explaining how mid-sized cities compete within national systems.
Factors That Strengthen or Weaken Interaction Predictions
While the gravity model identifies general patterns, several conditions modify how strongly cities interact. These factors help refine the model and improve its real-world accuracy.
When we compare one city’s interaction with several other cities at different distances, we typically observe strong flows to nearby places and much weaker flows to far-away places.
This diagram displays how a single origin (A) interacts with three locations (B, C, and D) at increasing distances. The arrows in the upper panel show how interaction weakens as distance grows, and the lower curve visually represents this declining relationship. The graphic is slightly broader than the AP requirement since it can represent passenger, freight, or other flows, but the same logic applies directly to interactions between cities. Source.
Factors that increase predicted interaction
Efficient transportation networks that reduce travel time and cost.
Cultural or linguistic ties that encourage migration and communication.
Shared economic specialization, such as technology clusters or manufacturing supply chains.
Government policies that promote regional integration or cross-border travel.
Factors that decrease predicted interaction
Physical barriers, including mountains, oceans, or deserts.
Limited infrastructure, such as poor roads or inadequate transit.
Political tensions or border restrictions that impede movement.
Economic disparities that weaken demand for exchange.
The Gravity Model in Contemporary Urban Geography
The gravity model remains relevant as global connectivity evolves. Although digital communication reduces some friction of distance, physical movement of people and goods continues to follow gravity-based patterns. Larger urban regions with diversified economies and strong transportation systems attract the most intense interactions. At the same time, improved mobility technologies and communication networks can slightly weaken traditional distance decay.
In metropolitan planning, the gravity model guides decisions about transportation investments, service locations, and regional development strategies. By revealing which cities exert the strongest pull, planners can anticipate growth corridors, identify underserved areas, and prepare for future demographic shifts.
FAQ
Distance can be measured in several ways, depending on what type of interaction is being studied.
Common measures include:
• Straight-line (Euclidean) distance
• Travel distance along roads or railways
• Travel time or cost
• Friction-of-distance estimates that factor in terrain or transport quality
The choice affects the predicted interaction level, so geographers select the measure that best reflects how people or goods actually move between cities.
Regions with well-developed transport and communication systems tend to reduce friction of distance, meaning the model’s assumptions align more closely with real behaviour.
High connectivity produces clearer patterns in flows of people, goods, and information, so population and distance become stronger predictors.
Conversely, in regions with poor infrastructure or major physical barriers, interaction may not follow the neat decline assumed by the model.
Yes. Although the basic model uses only population and distance, modified versions can include additional variables.
These may account for:
• Cultural or linguistic ties
• Trade agreements or political alliances
• Economic complementarity (cities offering different but compatible functions)
• Barriers such as international borders
Such adjustments produce more realistic predictions when human decision-making shapes interaction.
Technological improvements reduce the effective distance between places.
This includes:
• Faster transport modes such as high-speed rail
• More efficient logistics networks
• Digital communication that substitutes for physical travel
As technology improves, distance becomes a weaker predictor of interaction, although population generally remains a strong positive influence.
The model assumes that the only barriers to interaction are size and distance. In reality, very large cities often compete rather than interact.
Interaction may be lower because:
• Cities specialise in similar industries, creating rivalry instead of exchange
• Congestion increases travel time despite short physical distance
• Institutional or policy differences reduce economic integration
These factors can cause actual interaction to fall below the level the gravity model would predict.
Practice Questions
Question 1 (1–3 marks)
Describe how distance influences interaction between two cities according to the gravity model.
Mark scheme (3 marks total)
• 1 mark for stating that interaction decreases as distance increases.
• 1 mark for identifying that distance acts as a frictional force or barrier.
• 1 mark for noting that greater distance reduces flows such as travel, trade, or communication.
Question 2 (4–6 marks)
Using the gravity model, explain why two large cities located relatively close to each other are likely to have stronger interactions than a large city and a smaller, more distant settlement. Refer to both population and distance in your answer.
Mark scheme (6 marks total)
• 1 mark for recognising that larger populations generate greater potential for interaction.
• 1 mark for correctly stating that two large cities combined create a high level of interaction.
• 1 mark for explaining that shorter distance increases the likelihood of interaction.
• 1 mark for linking shorter distance to reduced travel time or cost.
• 1 mark for contrasting this with weaker interaction between a large city and a smaller, distant settlement.
• 1 mark for explicitly referencing both population size and distance as joint determinants of interaction in the gravity model.
