Knowledge Organiser: Human Geography Fieldwork
Data Collection Methods
- EQS: Rate 8–12 criteria on a 1–5 scale at each site along a transect. Quasi-quantitative. Photographic benchmarks + multiple observers reduce subjectivity.
- Pedestrian count: Count people past a fixed point for 5 minutes × 3. Calculate mean. Same time of day at all sites. Genuinely quantitative.
- Land use survey: Record building function along transect. Proportional bar charts. Tests shift from commercial to residential.
- Questionnaire: Random sampling (every 5th person). Mix of Likert scales and open questions. Ethical: consent, anonymity, voluntary.
- Traffic count: Count vehicles by type for 5 minutes × 3. Mean. Same time at all sites.
Burgess Concentric Zone Model
- Zone 1: CBD — highest land values, offices, retail, highest pedestrian flow
- Zone 2: Inner city — oldest housing, most deprived, lowest EQS typically
- Zone 3: Inner suburbs — improving housing, moderate EQS
- Zone 4: Outer suburbs — newer housing, gardens, highest EQS
- Zone 5: Rural-urban fringe — edge of city, out-of-town retail/business parks
- Limitation: Based on 1920s Chicago; UK cities show variations due to gentrification, council estates, historic cores
Risk Assessment
- Traffic: Cross at crossings; high-vis vests
- Getting separated: Meeting points; teacher's number; buddy system
- Public confrontation: Work in pairs; open public spaces only
- Heat/sun: Water; sunscreen; shade breaks
- Photography: Public spaces only; no identifiable faces without consent
- Slips/trips: Look up when moving; appropriate footwear
Evaluation Points
- EQS weakness → Use photographic benchmarks + multiple observers + mean
- One time of day → Survey at multiple times; note time on all sheets
- Small questionnaire sample → Increase to 50+; stratify by time of day/day of week
- One transect line → Use multiple parallel transects; compare results
- One-day survey → Repeat in different weather; different days of week
- URBAN mnemonic: Urban land use, Rating (EQS), Bipolar chart, Ask (questionnaire), Number (count)
Common Mistakes
- Describing method without explaining why it suits the hypothesis: Always link your chosen data collection method to the specific human geography hypothesis it tests (e.g. EQS measures environmental quality change across zones)
- Treating EQS scores as fully objective: EQS is quasi-quantitative — always acknowledge it involves subjective judgement and explain how photographic benchmarks and multiple observers reduce this
- Forgetting to state sample size and timing in questionnaires: Examiners expect you to say how many people were surveyed, at what times, and using what sampling strategy (random, systematic, stratified)
- Applying Burgess model without noting its limitations: Always state that the model is based on 1920s Chicago and UK cities vary due to gentrification, historic cores, and planned council estates
- Vague risk assessment answers: Name the specific risk AND the specific control measure — "be careful near traffic" scores nothing; "wear high-vis vests and cross only at designated crossings" scores the mark
Memory Aid
- U — Urban land use survey: Record the function of each building along the transect. Show how land use shifts from commercial (CBD) to residential (suburbs). Present as proportional divided bar charts.
- R — Rating (EQS/Bipolar survey): Score the environment against 8–12 criteria on a 1–5 scale. Use photographic benchmarks. Multiple observers. Mean scores. Plot against distance on a scatter graph.
- B — Bipolar/spider diagram: The presentation of EQS data in a radar chart format, with one axis per criterion. Makes it easy to compare overall quality profiles between sites and to identify which specific criteria differ most.
- A — Ask (questionnaire / interview): Survey residents and visitors about their perceptions. Use Likert scales for quantitative comparison. Use open questions for qualitative depth. Random sampling. Ethical guidelines always apply.
- N — Number (pedestrian / traffic count): Count people or vehicles at a fixed point for 5 minutes. Repeat 3× and mean. Same time of day at all sites. Genuinely quantitative — no subjectivity.