4.2 Fieldwork: Plan, carry out and evaluate geographical investigations.

4.2 Fieldwork – Plan, Carry Out and Evaluate Geographical Investigations

Learning Objective

Students will be able to design, conduct and critically evaluate a geographical field investigation, demonstrating mastery of the scientific method, appropriate data‑collection techniques, statistical analysis, and the limitations of fieldwork as required by the Cambridge 0460 syllabus (Component 3 or Paper 4).

Fieldwork Route (Syllabus Language)

1. Identify an issue and formulate a research question
2. State a testable hypothesis linked to geographical theory
3. Set clear objectives and choose a sampling strategy
4. Collect primary data (and, where appropriate, secondary data)
5. Organise and present data (tables, graphs, maps, GIS)
6. Analyse the data (statistical techniques, interpretation)
7. Conclude and evaluate (reliability, validity, ethical & safety issues, sustainability)

1. Topic‑Selection Guide

All ten content topics in the 0460 syllabus can be investigated with fieldwork. Choose a question that maps onto one of the sub‑points (e.g., 1.1‑1.5 for rivers). The table below gives a quick example for each topic.

Syllabus Topic	Typical Fieldwork Focus	Relevant Sub‑points
Rivers	Measure water velocity and discharge to test the Bradshaw model	1.1, 1.2, 1.3
Coasts	Profile shoreline change and assess long‑shore drift	2.1, 2.2
Ecosystems	Quadrat sampling of species richness in a woodland	3.1, 3.2
Tectonic processes	Map fault scarps and measure vertical displacement	4.1, 4.2
Climate change	Collect temperature and precipitation data to examine trends	5.1, 5.2
Population	Survey household density and age structure in a neighbourhood	6.1, 6.2
Towns & cities	Urban heat‑island study (surface temperature)	7.1, 7.2
Development	Assess access to services in a developing settlement	8.1, 8.2
Economic activity	Map land‑use patterns of a local industry	9.1, 9.2
Resource provision	Measure groundwater depth and quality	10.1, 10.2

2. Identify the Issue & Formulate a Research Question

• Choose a locally observable phenomenon that fits one of the ten topics.
• Write a concise, focused question that can be answered with field data.
  Example (Urban heat‑island): “How does surface temperature differ between built‑up areas and adjacent green spaces in the town centre?”
• Record the relevant syllabus sub‑points beside the question (e.g., 7.1‑7.2).

3. Develop a Testable Hypothesis

• Base it on a recognised geographical theory or model (e.g., Urban Heat Island theory, Bradshaw model, coastal erosion cycle).
• Make it measurable, directional and linked to the chosen sub‑points.
  Example: “If built‑up surfaces absorb more solar radiation than vegetated surfaces, then the mean surface temperature in built‑up sites will be at least 3 °C higher than in green‑space sites measured at the same time of day.”

4. State Objectives & Choose a Sampling Strategy

Component	What to Include
Objectives	Specific, measurable aims (e.g., “Record temperature at three times of day across six sites”).
Sampling strategy	Justify the method (random, systematic, stratified) and sample size (minimum three replicates per category for AO2). Include a sketch or map of site layout.
Control variables	List variables kept constant (time of day, weather, instrument, observer). Explain how they will be controlled.

5. Data‑Collection Methods & Equipment

• Primary data – direct measurements in the field.
• Secondary data – published sources, GIS layers, satellite imagery, climate normals.

Typical equipment checklist (adapt for each investigation)

Item	Purpose
Digital thermometer (±0.1 °C)	Surface temperature
Flow‑meter & ranging pole (30 m)	River velocity & distance
Clinometer	Slope or bank angle
Quadrat frame (1 m²)	Vegetation sampling
GPS unit (≤5 m accuracy)	Site coordinates
Field notebook / tablet	Raw data and observations
Camera	Site documentation
PPE (boots, high‑visibility vest, gloves)	Safety

6. Risk Assessment & Ethical Considerations

Risk‑assessment template (example)

Hazard	Potential consequence	Control measures	Residual risk
Slippery riverbank	Fall & injury	Wear sturdy boots, test footing, work in pairs	Low
Heat stress (summer)	Dehydration, fainting	Carry water, schedule breaks, wear hat	Low
Electronic equipment near water	Electrical shock	Water‑proof cases, keep dry	Very low
Human participants (e.g., interview)	Privacy breach	Written consent, anonymise data	Low

• Attach the completed risk assessment as an appendix.
• For human‑geography components, include a consent form and discuss confidentiality, voluntary participation and data protection (GDPR).
• Consider the **sustainability lens** – does the investigation affect the environment or local community? State any mitigation steps.

7. Organising & Presenting Data (AO2 Requirements)

Produce **at least two** of the following, each clearly labelled with units, titles and source notes.

• Tables – raw data and calculated statistics (mean, range, variance, standard deviation).
• Bar or column charts – compare categories; include error bars (±1 SD).
• Scatter plot with line of best fit – show relationship between two quantitative variables.
• GIS‑derived thematic map – heat‑map, choropleth, or interpolated surface.
• Profile or cross‑section diagram – for river or coastal investigations.
• Photographic evidence – annotated images of the site.

8. Skill‑Checklist (AO2 Cross‑Reference)

Skill	Relevant syllabus topics	Typical use in fieldwork
4‑figure & 6‑figure grid references	All topics	Locate and record sites accurately.
Construction of a cross‑section/profile	Rivers, Coasts, Ecosystems	Show vertical change in river channel or coastal cliff.
Use of a clinometer & ranging pole	Coasts, Rivers, Tectonics	Measure slope, bank angle, fault displacement.
Quadrat sampling & species identification	Ecosystems, Resource provision	Calculate species richness, diversity indices.
Flow‑meter operation	Rivers, Coastal processes	Record water velocity & discharge.
GIS mapping & spatial interpolation	All topics (especially Climate change, Towns & cities)	Produce heat‑maps, land‑use maps, hazard zones.
Statistical tests (t‑test, chi‑square, correlation)	All topics where quantitative comparison is required	Assess significance of differences or relationships.
Interpretation of secondary sources (satellite images, charts)	All topics	Contextualise primary data, identify trends.

9. Example Investigation – Urban Heat Island (Human Geography)

Research Question

How does surface temperature vary between built‑up areas and nearby green spaces in the town centre?

Hypothesis

Built‑up sites will be on average ≥ 3 °C warmer than green‑space sites measured at the same time of day.

Objectives

• Record temperature at 10 am, 12 pm and 2 pm on a clear day.
• Take three replicates per site and calculate the mean temperature.
• Compare the means of the two land‑use categories using an independent‑samples t‑test (α = 0.05).

Sampling Strategy

• Systematic sampling: three built‑up sites (A‑C) and three green‑space sites (D‑F) along a north‑south transect, each ≈200 m apart.
• All sites have similar altitude, aspect and exposure to minimise confounding variables.

Data‑Collection Procedure

1. Calibrate the digital thermometer against a known standard before departure.
2. At each site, record temperature three times (10 am, 12 pm, 2 pm). Take three readings per time and note the mean immediately.
3. Record GPS coordinates, cloud cover (eighths), and any anomalous observations (e.g., passing vehicle shade).
4. Collect secondary data: 10‑year climate normals (Met Office) and a satellite‑derived land‑cover map to confirm land‑use classification.

Raw & Calculated Data Table

Site	Land‑use	10 am (°C)	12 pm (°C)	2 pm (°C)	Mean (°C)	Range (°C)	SD (°C)
A	Built‑up	22.5	27.1	29.3	26.3	6.8	3.4
B	Built‑up	22.8	27.4	29.6	26.6	6.8	3.4
C	Built‑up	22.6	27.2	29.5	26.4	6.9	3.5
D	Green Space	20.1	24.3	26.0	23.5	5.9	2.9
E	Green Space	20.3	24.5	26.2	23.7	5.9	2.9
F	Green Space	20.2	24.4	26.1	23.6	5.9	2.9

Statistical Analysis

• Overall means (3 sf):
  \(\bar{x}_{BU}=26.4\;^{\circ}\!C\)  \(\bar{x}_{GS}=23.6\;^{\circ}\!C\)
• Independent‑samples t‑test (α = 0.05):
  t = 5.12, p < 0.01 → significant difference, hypothesis supported.
• Effect size (Cohen’s d) ≈ 1.2 (large).

Data Presentation (required techniques)

1. Bar chart – mean temperature for built‑up vs. green space with ±1 SD error bars.
2. GIS heat‑map – interpolated temperature surface over the study area, overlaid on an OS map.
3. Scatter plot (optional extension) – temperature vs. distance from town centre.

Evaluation Checklist (AO3)

Evaluation Aspect	Guiding Questions (link to sustainability)
Reliability	Were repeated measurements consistent? Does the low p‑value indicate low random error?
Validity	Do the sites accurately represent “built‑up” and “green‑space” categories? Were control variables truly constant?
Sampling	Was n = 3 per category sufficient for statistical significance? Would a larger sample improve confidence and representativeness?
Instrumental error	Was the thermometer calibrated before each session? Any drift observed during the day?
Environmental bias	Did cloud cover or passing traffic affect readings? Were these recorded and accounted for?
Secondary data integration	How did climate normals compare with field measurements? Did GIS land‑cover data reveal micro‑climatic influences?
Ethical & safety	Were risk‑assessment measures followed? Was consent obtained for any interviews?
Sustainability lens	Does the urban heat‑island effect have implications for energy use or public health? Could the investigation inform mitigation (e.g., planting trees)?
Improvements	Increase sample size, extend data collection over several days, add humidity & wind speed, use infrared thermography, incorporate citizen‑science temperature logs.

10. Report Structure (Cambridge Recommended)

1. Title page – title, candidate name, date, subject.
2. Abstract (≈150 words) – purpose, methods, key results, conclusion.
3. Introduction
   • Background & relevant geographical theory.
   • Research question, hypothesis, and syllabus sub‑points.
   • Clear objectives.
4. Methodology
   • Site selection & sampling strategy (include a 1 km² map with grid references).
   • Equipment list, calibration procedure.
   • Step‑by‑step field procedure.
   • Risk assessment (appendix) and ethical considerations.
5. Results
   • Raw data tables (appendix for full data).
   • Processed tables (means, range, SD, variance).
   • Graphs, GIS map, any additional diagrams.
   • Statistical test outcomes (t‑value, p‑value, effect size).
6. Discussion
   • Interpretation of results in relation to hypothesis & theory.
   • Comparison with secondary data or published literature.
   • Evaluation of reliability, validity, limitations, and sustainability implications.
   • Link findings to the wider geographical context (e.g., climate‑change mitigation).
7. Conclusion – concise answer to the research question, summary of key findings, and suggestion for further work.
8. References – Harvard or APA style.
9. Appendices – full raw data, risk assessment, consent forms, calibration certificates, GIS layers, additional maps.

11. Component 3 vs Paper 4 – What to Remember

• Component 3 (Coursework): 1800‑2200 words, deeper analysis, larger data set, formal risk‑assessment appendix required.
• Paper 4 (Geographical Investigations): 45‑minute exam; you must plan, analyse and evaluate a pre‑set investigation. Use the same route, but answers are concise (≈800‑1000 words) and you rely on the provided data set.
• Scale the depth of evaluation and the number of data‑presentation techniques to match the assessment type.

Key Exam Tips (AO1‑AO3)

• Label every diagram, table and graph clearly; include units, titles and source notes.
• Use LaTeX‑style notation for calculations (e.g., \(\sigma = \sqrt{\frac{\sum (x_i-\bar{x})^2}{n-1}}\)).
• When evaluating, address the three AO3 strands explicitly:
  1. Evaluate the importance of factors influencing your results.
  2. Recognise the limitations of your data, methods or models.
  3. Evaluate options/strategies for improvement, linking to sustainability where relevant.
• Link every finding back to the underlying geographical concept or theory.
• For Paper 4, practice interpreting supplied secondary sources (satellite images, charts) – this is a required AO2 skill.