AP Human Geography

Models & Theories
Master Guide

Recognize, define, apply, and critique the 30 highest-frequency models — with real examples and limitations.

FRQ Super-Rule: Always (1) define the model, (2) apply it to the prompt's specific place, (3) state a limitation or exception. Points hide in step 3.

The 30 High-Frequency Models

Master Checklist
#Model / TheoryCore IdeaWhat AP Questions Ask
1Central Place Theory (Christaller)How settlements space out to provide goods/servicesIdentify hexagon market areas, range/threshold, predict higher-order service location
2Rank-Size RuleCity sizes follow a predictable rank patternCompute/compare expected sizes; spot deviations
3Primate City RuleOne city dominates (often >2× the #2 city)Explain colonial legacy, primacy effects on migration and investment
4Concentric Zone Model (Burgess)US industrial city land use in ringsLabel rings; connect to invasion/succession, filtering, disamenities
5Sector Model (Hoyt)Land use in wedges/sectors along transport routesExplain why high-rent sector extends along corridors
6Multiple Nuclei Model (Harris–Ullman)Cities develop multiple centers (nodes)Match land uses to nodes (airport, university, port)
7Latin American City Model (Griffin–Ford)Elite spine; CBD + peripheral squatter areasIdentify spine/elite sector, in situ accretion, periferico
8Southeast Asian City Model (McGee)Mix of colonial CBD + port zone + ethnic zonesIdentify commercial spine, old port, mixed land use
9Bid-Rent Theory (Alonso)Land value/rent declines with distance from centerExplain competition for accessible land (retail vs housing)
10Demographic Transition Model (DTM)How birth/death rates change with developmentPlace a country in a stage, predict growth, explain causes
11Epidemiological Transition Model (ETM)Causes of death shift with developmentMatch stages to disease patterns; discuss disease diffusion
12Malthusian TheoryPopulation grows faster than food → checksApply to famine/poverty debates; critique with tech/trade
13Boserup ThesisPopulation pressure drives agricultural intensificationExplain innovations (terracing, irrigation) as a response
14Population Pyramid + Dependency RatioAge/sex structure and economic burdenInterpret momentum, aging, youth bulge; compute dependency
15Push–Pull Migration Model (Lee)Migration driven by pushes/pulls + obstaclesCategorize factors; include intervening obstacles
16Ravenstein's Laws of MigrationCommon migration patterns (short moves, step, urban pull)Use "laws" to justify observed flows
17Zelinsky Mobility Transition ModelMigration patterns change by development stagePredict rural→urban vs international migration trends
18Gravity ModelInteraction increases with size, decreases with distanceCalculate relative interaction; compare city pairs
19Distance Decay / Friction of DistanceEffects weaken with distance or cost/timeExplain trade, diffusion, commuting, service areas
20Environmental Determinism vs PossibilismEnvironment controls vs humans adapt/modifyCritique deterministic claims; show cultural/tech mediation
21Sequent OccupancePlaces have layers of cultural landscape over timeExplain mixed toponyms, land use layers, architecture
22Hägerstrand Innovation Diffusion (S-curve)Diffusion: slow → rapid → levelingSketch/interpret adoption curve; connect to networks
23Language Diffusion Models (Tree vs Wave)Tree = divergence; Wave = spread via contactChoose model that fits (isolation vs contact)
24Geopolitical Theories: Heartland vs RimlandWho controls "pivot" land or coastal rim controls powerApply historically and critique modern relevance
25Shatterbelt TheoryConflict-prone region between stronger powersIdentify examples; explain external pressure + internal division
26von Thünen ModelAgricultural land use rings around a marketPredict crop placement by transport cost/perishability
27Weber Least-Cost TheoryIndustry locates to minimize transport + labor costsChoose site near inputs/market; note agglomeration
28Rostow Stages of Economic GrowthLinear development: traditional → mass consumptionPlace countries; critique Eurocentric/linear assumptions
29Wallerstein World-Systems TheoryCore exploits periphery; semiperiphery mediatesClassify countries; explain dependency/unequal exchange
30Clark–Fisher Sector ModelEconomy shifts: primary → secondary → tertiaryLink to development, jobs, urbanization patterns

Step-by-Step Workflow

Any MCQ or FRQ
1

Identify the Theme

  • Urban land use → Burgess / Hoyt / MNM / Bid-rent
  • Population → DTM / ETM / Pyramids
  • Migration → Push-Pull / Ravenstein / Zelinsky
  • Development → Rostow / Wallerstein / Weber / von Thünen
2

Name + Define

Define the model in one sentence. Example: "The DTM explains how birth/death rates shift as a country industrializes."

3

Apply to the Prompt

Use 2 concrete real indicators — TFR, CBR/CDR, informal settlements, corridors, coal/iron, labor cost, etc.

4

State a Limitation ⚡

Points hide here. Common assumptions: isotropic plain, closed economy, stable politics, no colonial legacy, universal linear path.

Key Formulas

Compute These
Gravity Model
I = (P₁ × P₂) / d²
Use when: Comparing likely interaction between two places. Bigger populations → more interaction; distance reduces it.
Rank-Size Rule
Pₙ = P₁ / n
Use when: Estimating the nth city's size given the largest. Strong fit = integrated urban system.
Dependency Ratio
DR = [(0–14) + (65+)] / (15–64) × 100
Use when: Measuring pressure on working-age population. High DR can come from a youth bulge or aging population.

Urban Models — Must-Know Labels

Sketch These
Burgess — Concentric Zones

Rings (Inside → Out)

CBD Zone of Transition Working-Class Middle-Class Commuter/Suburbs
Hoyt — Sector Model

"Pie Slices"

High-rent and industry form wedges along rail, roads, and water. Sectors radiate out from the CBD.

Harris–Ullman — Multiple Nuclei

"Many Downtowns"

Separate nodes like airports, universities, and ports each create their own center and surrounding land uses.

Griffin–Ford — Latin American

Elite Spine + Periphery

CBD Commercial Spine Elite Sector In Situ Accretion Periferico
McGee — Southeast Asian

Colonial + Port Mix

Colonial CBD + old port/city, with a commercial spine and strong ethnic quarters. Mixed land uses throughout.

Alonso — Bid-Rent

Competing for Access

Different users bid for land. Retail bids highest near the center. Value declines with distance from CBD.

DTM — Stage Clues

High-Yield
Stage 1

High / High

High CBR, high CDR. Little to no net growth.

Stage 2

CDR Drops Fast

Sanitation/medicine causes CDR to plummet → population boom.

Stage 3

CBR Starts Falling

Urbanization, contraception, and women's education cause CBR to drop.

Stage 4

Low / Low

Both CBR and CDR are low. Stable or very slow growth.

Stage 5

Natural Decrease

CBR falls below CDR. Aging population, population shrinks.

ETM — Stage Clues

Disease Patterns
Stage 1

Pestilence & Famine

Infectious disease and famine dominate mortality.

Stage 2

Receding Pandemics

Improved medicine and sanitation reduce infectious disease deaths.

Stage 3

Degenerative Disease

Heart disease, cancer, and chronic illness become dominant causes of death.

Stage 4/5

Delayed + Re-emerging

Delayed degenerative diseases plus re-emerging infections (e.g., antibiotic resistance).

Mini Worked Examples

Apply + Limit Fast
Model

von Thünen — Agricultural Rings

Apply

A city market encourages dairy and market gardening close in because they're perishable and costly to ship. Grains and ranching move further out.

Limit

Refrigeration, highways, and global trade break the neat ring pattern. Modern supply chains mean dairy can ship thousands of miles.

Model

Demographic Transition Model (DTM)

Apply

Country X has a high CBR and rapidly falling CDR due to improved sanitation → Stage 2 rapid population growth.

Limit

War, HIV/AIDS, or state policies can interrupt or distort the expected progression through stages.

Model

Central Place Theory (Christaller)

Apply

A specialty hospital locates in a regional city because it needs a larger threshold population and people will travel farther (greater range) for specialized care.

Limit

Physical barriers, online services, and uneven wealth distort the neat hexagonal spacing the model assumes.

Model

Gravity Model

Setup

City A: pop. 2,000,000 | City B: pop. 500,000 | Distance: 100 km

Insight

Because distance is squared, doubling the distance cuts interaction to one quarter. If populations are similar, distance decides; if distance is similar, population decides.

Model

Weber Least-Cost Theory

Setup

A steel mill needs bulky inputs (iron ore + coal) and sells to a major metro market.

Apply

If inputs lose weight during processing, the plant locates near raw material sources to cut bulk transport costs.

Limit

Modern firms may prioritize skilled labor, just-in-time logistics, or tax incentives. Agglomeration economies can override transport logic.

Model

Latin American City Model (Griffin–Ford)

Apply

Elite high-rise development along one corridor from the CBD = commercial spine/elite sector. Large informal settlements on the periphery match the periferico zone.

Limit

Rapid globalization can produce edge cities and polycentric patterns not captured by the model's single-spine structure.

Common Mistakes & Traps

Don't Lose Points Here

DTM Stage Mix-Ups

Why Wrong

Calling a country "Stage 3" just because it's growing. Stage 3 is defined by a falling CBR, not just population growth.

Fix

Look for why CBR is dropping — contraception, women's education, and urbanization are the key indicators.

Treating Models as Universal Laws

Why Wrong

Force-fitting Burgess or von Thünen to every city. Models assume flat land, single center, no planning, older industrial context.

Fix

Always add a limitation — topography, zoning, highways, globalization, or colonial history all distort model predictions.

Confusing Rank-Size with Primate

Why Wrong

Rank-size is a distribution pattern across many cities; primate is one-city dominance. They are not the same thing.

Fix

Rank-size: use Pₙ = P₁/n. Primate: check if the largest city is >2× the size of the #2 city.

Diffusion Type Confusion

Why Wrong

Describing "spread through social media influencers" as contagious diffusion.

Fix

Influencer → others = hierarchical. Neighborhood to neighborhood = contagious. Remember: C-H-S-R (Contagious, Hierarchical, Stimulus, Relocation).

Misreading Population Pyramids

Why Wrong

Seeing a wide base and saying "aging population." A wide base means high youth dependency and a high CBR.

Fix

Aging shows as a wide top — a rectangular or top-heavy structure with high old-age dependency.

Weber Without Agglomeration

Why Wrong

Only mentioning transport costs misses a major component of Weber's own theory.

Fix

Add: "Agglomeration economies can pull firms into clusters even if individual transport costs rise slightly."

Memory Aids & Quick Tricks

Memorize These
DTM: High/High → Death drops → Birth drops → Low/Low → Below replacement
Remembers: DTM stage logic
Use for: any population-growth prompt
Burgess: "CBD – Transition – Working – Middle – Commuter"
Remembers: Order of concentric zones
Use for: urban land-use MCQ/FRQ
Hoyt = "pie slices"
Remembers: Sector wedges along transport
Use for: distinguishing from Burgess
Multiple Nuclei = "many downtowns"
Remembers: Nodes like airports create centers
Use for: modern/polycentric city questions
CPT: "Range = how far; Threshold = how many"
Remembers: The two most-tested CPT terms
Use for: service distribution questions
Malthus vs Boserup: "Limits vs Innovation"
Remembers: Opposing population-food theories
Use for: food security questions
Primate = "primary city" dominates
Remembers: Quick primate check
Use for: comparing city sizes
Diffusion: C-H-S-R
Remembers: Contagious, Hierarchical, Stimulus, Relocation
Use for: culture/language/religion diffusion

Quick Review Checklist

Before Exam Day
I can name + define each of the 30 models in one sentence.
I can sketch and label: Burgess, Hoyt, Multiple Nuclei, Latin American, Southeast Asian, and CPT hexagons.
I know the 3 key computations: Gravity (P₁×P₂/d²), Rank-Size (P₁/n), Dependency Ratio ((0–14 + 65+) / (15–64) × 100).
I can match DTM/ETM stages to real indicators — CBR/CDR, aging, disease types.
I can apply Weber (inputs/market/labor/agglomeration) and von Thünen (perishability/transport rings).
I can contrast Rostow (linear development path) vs Wallerstein (structural core–periphery dependency).
I always add one limitation or assumption when applying any model on the FRQ.