What you'll learn
- The difference between qualitative and quantitative data.
- How primary and secondary sources are used in Geography.
- How maps, GIS, satellite images, fieldwork and statistics help you investigate places.
- How to interpret, analyse and evaluate data rather than just describe it.
Why geographers use data
Geographers use data: recorded observations, measurements, images or words. Data helps you move from “I think…” to “The evidence suggests…”.
A variable is something that can change, such as rainfall, house prices, river width, traffic flow or people’s opinions. In GCSE Geography, you often use data to investigate how variables differ between places, change over time, or connect to each other.
Geographical skills are assessed across all three papers, including your fieldwork.
Data becomes geography when it answers a question
A good geographical answer links evidence to a place, a scale such as local, regional, national or global, and a process such as erosion, urbanisation, migration or climate change.
The diagram below shows the whole data journey: collecting evidence, presenting it clearly, interpreting patterns, then judging how trustworthy it is.
Qualitative and quantitative data
Qualitative and quantitative data
- Qualitative data describes qualities, opinions, experiences or visual evidence. It is usually words or images, such as interview comments, field sketches and photographs.
- Quantitative data records numbers, counts or measurements, such as rainfall in mm, population in millions, traffic counts, percentages or river velocity.
Both types are valuable. Quantitative data is useful for comparison and calculation. Qualitative data helps explain people’s views, decision-making and the “feel” of a place.
Some data sits between the two. An environmental quality survey uses human judgement, but converts it into a score, so it is quantitative but partly subjective.
Numbers are not automatically better
A percentage, index or score can look precise even when it is based on a weak method, a biased question or a tiny sample. Strong geographers use numbers and words together.
Choosing data for an urban regeneration enquiry
Imagine your question is: “How successful has regeneration been in Stratford, east London?”
- Identify what “successful” could mean geographically: improved environment, more jobs, better housing, higher footfall, or local people feeling positive.
- Choose quantitative data for measurable change, such as pedestrian counts, land-use counts, house price data, employment data or environmental quality scores.
- Choose qualitative data for lived experience, such as interview comments from residents, annotated photographs of public space, or planning report extracts.
- Combine them: if footfall has increased but interviews show some long-term residents feel excluded, your conclusion becomes more balanced and evaluative.
Primary and secondary sources
A source is where your data comes from.
Primary and secondary sources
- Primary data is collected first-hand by you or your class for a specific enquiry, such as field measurements, questionnaires, interviews or traffic counts.
- Secondary data has already been collected by someone else, such as Census data, Ordnance Survey maps, Met Office climate data, Environment Agency flood maps or satellite images.
A source can be both primary/secondary and qualitative/quantitative. For example, a photo you take during fieldwork is primary qualitative data. UK Census population figures are secondary quantitative data.
Combining sources for a river enquiry
Suppose you are investigating how a river changes downstream.
- Collect primary quantitative data at several sites, such as width, depth, velocity and bedload size. This gives evidence directly linked to your enquiry.
- Add secondary data, such as an OS map for height and land use, a geology map, or recent rainfall data from the Met Office. This helps explain why your results vary.
- Compare the sources. If velocity is unusually low at one site, secondary evidence might show a weir, confluence or recent heavy rainfall that affected the result.
Main types of geographical data
Maps
A map represents part of the Earth’s surface. Maps can show location, height, land use, transport, political borders, population density or hazard risk.
Common examples include:
- OS maps for local detail, grid references, contours and land use.
- Atlas maps for national and global patterns.
- Thematic maps, which focus on one theme, such as rainfall, migration or deprivation.
Fieldwork data
Fieldwork data is collected outside the classroom. It can include river measurements, beach profiles, pedestrian counts, questionnaires, interviews, noise readings, bipolar surveys and annotated sketches.
A sample is a smaller set of people, places or measurements used to represent a wider group. A representative sample reflects the wider population or area fairly.
Geo-spatial data and GIS
GIS
A Geographical Information System, or GIS, is a digital system for storing, layering, analysing and displaying geo-spatial data: data linked to a real location.
GIS lets you layer data, such as roads, rivers, population density, flood risk, land use and satellite imagery. You can zoom, filter, measure distance and identify patterns.
Using GIS to investigate flood risk
- Add map layers for rivers, height, land use, housing and Environment Agency flood zones.
- Overlay the layers to find where homes, roads or schools are located within areas of higher flood risk.
- Use the pattern to make a geographical judgement, such as which neighbourhoods may need flood defences or evacuation planning most urgently.
Satellite imagery
Satellite imagery is data collected by sensors on satellites orbiting Earth. It is useful for large-scale monitoring, such as tropical storms, deforestation in the Amazon, sea ice change, urban growth in Lagos, or flooding after a storm.
Satellite images are powerful because they cover wide areas and can be repeated over time. However, they still need interpretation: cloud cover, image resolution and the date of the image matter.
Written, digital, visual and statistical sources
Geographers also use:
- Written sources, such as newspaper articles, planning documents, textbooks and government reports.
- Digital sources, such as websites, online databases, interactive maps and dashboards.
- Visual sources, such as photographs, field sketches, climate graphs, hydrographs and population pyramids.
- Numerical and statistical information, such as means, ranges, percentages, rates and totals.
From raw data to geographical information
1. Obtain the data
To obtain data means to collect or access it. Before gathering data, you need a clear enquiry question, a suitable location, and a method that matches the question.
For example, if you are investigating quality of life in a city, a questionnaire might be useful. If you are investigating coastal erosion, beach profiles, annotated photographs and historical maps may be more suitable.
Record the source details
For any data you use, note the place, date, method, units and source. This makes your work easier to evaluate later.
2. Illustrate and communicate the data
To illustrate data means to show it visually. To communicate data means to make the message clear to someone else.
Different data needs different presentation methods:
| What you want to show | Good method | Why it works |
|---|---|---|
| Location or distribution | Map or GIS layer | Shows where things are |
| Change over time | Line graph | Shows trends clearly |
| Comparing categories or places | Bar chart | Makes differences easy to see |
| Relationship between two variables | Scattergraph with a line of best fit | Shows whether variables are connected |
| Movement between places | Flow-line map | Shows direction and size of movement |
| Opinions or visual evidence | Quotes, photographs, annotated sketches | Keeps detail and human experience |
A line of best fit is a line drawn through a scattergraph to show the overall relationship between two variables.
Choosing how to present high street data
- If your data is footfall at different points along a high street, use a located bar chart or proportional symbols on a map, because location matters.
- If your data is the number of vacant shops in different zones, use a land-use map or choropleth map, because it shows spatial pattern.
- If your data is interview comments about safety or cleanliness, use short selected quotes beside annotated photographs, because the words explain the numbers.
3. Interpret and analyse the data
To interpret data means to explain what it shows. To analyse data means to break it down, compare parts, identify patterns and suggest reasons.
Useful words include:
- Pattern: where data is clustered, spread out or uneven.
- Trend: the overall direction of change, such as increasing or decreasing.
- Anomaly: a result that does not fit the general pattern.
- Relationship: a connection between variables.
- Central tendency: a typical value, such as the mean, median or mode.
- Spread: how varied the data is, such as the range.
Calculating percentage increase in footfall
A class counts 125 pedestrians in 10 minutes before improvements to a shopping street, and 160 pedestrians after the improvements.
- Use the original value as the baseline, because the question asks how much footfall increased compared with before.
- Find the change: 160−125=35160 - 125 = 35160−125=35 extra pedestrians.
- Substitute into the percentage increase formula:
So:
35125×100=28\frac{35}{125} \times 100 = 2812535×100=28- Interpret it geographically: footfall increased by 28%, which suggests the area may have become more attractive or accessible, although you would need more evidence before claiming the regeneration was fully successful.
Percentages need context
A percentage change can be misleading if the original number is very small. Always consider the base figure as well as the percentage.
Qualitative data can also be analysed systematically. To code qualitative data means to sort words, images or observations into themes.
Coding interview comments
- Group comments into themes, such as safety, traffic, green space, housing cost and job opportunities.
- Count how often each theme appears to identify the strongest concerns, while remembering that this is still based on people’s responses.
- Select one or two short quotes that represent the main themes, then link them to your quantitative evidence.
4. Evaluate the data
To evaluate data means to judge its quality and usefulness. This is where strong GCSE answers often gain marks, because you are not just accepting evidence at face value.
Important evaluation terms:
- Accuracy: how close the data is to the true value.
- Reliability: whether repeating the method would give similar results.
- Validity: whether the data actually measures what it claims to measure.
- Bias: when data is unfairly influenced in one direction.
- Scale: the level of study, such as local, regional, national or global.
- Resolution: the level of detail, especially in images or maps.
- Recency: how up to date the data is.
Triangulation
Triangulation means using more than one source or method to check whether the evidence points to the same conclusion.
Evaluating Census data for a local enquiry
- Recognise the strength: Census data is official, large-scale and useful for comparing neighbourhoods across the UK.
- Identify the limitation: it may be several years old, so it might not show rapid recent change after regeneration, migration or new housing.
- Improve the judgement by triangulating it with primary fieldwork, such as land-use mapping, questionnaires or observations in the same area.
In the exam
- Name the data type and source clearly: for example, “primary quantitative traffic count data” or “secondary qualitative newspaper evidence”.
- Link presentation methods to purpose: maps show location, line graphs show change, scattergraphs show relationships, and photographs/quotes show detail.
- When evaluating, use specific criteria such as accuracy, reliability, bias, scale, date and sample size rather than saying “the data might be wrong”.
Check yourself
- Can you give one example each of primary qualitative, primary quantitative, secondary qualitative and secondary quantitative data?
- Which presentation method would you choose for data showing change over time, and why?
- How could you evaluate a satellite image or Census dataset before using it as evidence?
