Geographical Theory and Analysis: Models and Evaluation
Geographical Theory and Analysis asks you to apply models, explain spatial patterns and evaluate explanations rather than only describe them.
Core rules
- Models are simplifications: Burgess (concentric zones), Hoyt (sectors), Harris–Ullman (multiple nuclei), von Thünen (land use), Weber (industrial location), Christaller (central places) and Rostow (stages of growth).
- Evaluate each model by its assumptions, its scale and its fit to low- and high-income contexts. Burgess assumes free competition and concentric growth; many cities grow along transport corridors.
- Cause–effect reasoning needs a mechanism, evidence and acknowledgement of feedback. Spatial patterns often have multiple causes: physical, economic, political and cultural.
- Evaluation requires criteria: accuracy, generality, predictive power, and ethical or policy implications.
Worked example
A city shows high-income housing on the western edge, industry along the river and a decaying inner ring. The concentric model predicts outer high-class housing, but the sector model better explains the western wedge because prevailing winds and the main road favoured affluent expansion there. Use the model that fits the evidence and state its limitation.
Traps
Do not present a model as a law. Do not describe a pattern without explaining the process. Do not evaluate by saying “it is good” or “it is bad”-use explicit criteria. Do not ignore scale: a model that fits a national pattern may fail locally.
Key points
- Burgess = concentric zones; Hoyt = sectors; Harris–Ullman = multiple nuclei.
- Evaluate models by assumptions, scale, accuracy and predictive power.
- Cause–effect explanations need a mechanism and evidence.
- Spatial patterns usually have multiple causes.
- A model may fit one scale or region and fail at another.