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Unlock This CourseWhen you go out into the field whether that's a river, a beach, a city street or a forest you're collecting real evidence about the environment. But collecting data is only the start. You also need to record it carefully, analyse it to find patterns and present it so others can understand what you found. These three skills are at the heart of every good fieldwork investigation.
Think of it like being a detective. You gather clues (data), look for connections (analysis) and then explain your findings (presentation). Get these right and you'll be able to answer your investigation question with confidence.
Key Definitions:
You collect this yourself during fieldwork. It's fresh, specific to your location and directly answers your question. Examples include: river discharge measurements, soil pH readings, pedestrian counts, noise level recordings and litter surveys. The big advantage? It's tailored exactly to your investigation.
This is data already collected by others governments, scientists, charities or news organisations. Examples include: Environment Agency river flow data, Met Office weather records, satellite images and census population figures. It's useful for comparing your findings to wider trends or historical data.
Good recording is all about being systematic and accurate. If you record data messily or inconsistently, your whole investigation falls apart. Before you go out, you need to plan exactly what you'll measure, how you'll measure it and how you'll write it down.
Recording data carefully in the field
There are several tried-and-tested ways to record data during fieldwork. Choosing the right one depends on what you're investigating.
Great for counting things like vehicles, people, or species of plants. Simple, quick and easy to use in the field. For example, counting the number of pedestrians passing a point every 5 minutes in a CBD.
Used when you're taking readings with equipment like a thermometer, pH meter, or tape measure. You record readings in a pre-prepared table with columns for location, time and measurement value.
Qualitative methods that capture what a place looks like. A field sketch labels key features of a landscape. Photos provide visual evidence. Both are useful for showing environmental conditions that numbers can't fully describe.
You can't measure everything so you take a sample. There are three main sampling strategies used in iGCSE fieldwork:
Sample points are chosen completely by chance for example, using random number tables or a random number generator. This removes bias but might miss important areas. Good for: soil surveys, plant distribution studies.
Samples are taken at regular intervals for example, every 10 metres along a river or every 5th person who walks past. This gives even coverage of an area. Good for: transects along a beach or river.
The population is divided into groups (strata) and samples are taken from each group in proportion. For example, if 60% of an area is grassland and 40% is woodland, you'd sample in those proportions. Good for: land use surveys.
A group of students investigated whether water quality changes along the River Wye in Wales. They used systematic sampling, taking measurements every 500 metres downstream. At each point they recorded: water temperature (°C), pH level, dissolved oxygen (mg/L), turbidity (cloudiness) and flow speed (m/s). They used pre-prepared data tables and took photographs of each site. This gave them both quantitative and qualitative data to compare.
Once you've collected your data, it's time to make sense of it. Analysis means looking for patterns, trends, anomalies and connections in your data. You're trying to answer: does the data support your hypothesis or not?
Key Analysis Techniques:
A trend is a general direction that data moves in for example, temperature increasing as you move further from the coast. A pattern is a repeated relationship in the data for example, litter levels are always higher near fast food outlets. When you analyse data, always ask:
A positive correlation means as one variable increases, so does the other. For example, as distance from a city centre increases, green space increases. A negative correlation means as one increases, the other decreases. For example, as distance from a factory increases, air pollution decreases. No correlation means there's no clear relationship between the two variables.
Choosing the right presentation method is just as important as collecting the data. The wrong type of graph or map can make your data confusing or misleading. Here's a guide to the most common methods used in iGCSE Environmental Management fieldwork.
Best for showing change over time or continuous data. For example, plotting river discharge over 12 months, or temperature change throughout the day. Always label axes with units.
Best for comparing different categories. For example, comparing average litter counts at five different sites, or rainfall totals in different months. Bars should be the same width with gaps between them.
Best for showing proportions how something is divided up. For example, land use in a study area (40% residential, 25% green space, 35% commercial). Only use when you have percentage data that adds up to 100%.
Used to show the relationship (correlation) between two variables. Plot one variable on the x-axis and the other on the y-axis. Each data point is a dot. Then draw a line of best fit. For example: distance from city centre (x) vs. noise level in dB (y). The line of best fit shows whether the correlation is positive, negative, or absent.
Maps are ideal for showing spatial patterns how something varies across an area. A choropleth map uses shading to show data values across regions (darker = higher values). For example, shading areas by air pollution levels or population density. Always include a key, scale and north arrow.
Students investigating coastal erosion at Happisburgh, Norfolk, used a range of presentation methods. They drew a transect diagram showing cliff height and beach width at five points along the coast. They used a bar chart to compare erosion rates (metres per year) at each site. Annotated photographs showed evidence of undercutting and slumping. A choropleth map showed which sections of coastline were retreating fastest. By combining these methods, they could clearly show both the scale and location of erosion.
The final stage of any fieldwork investigation is writing up your conclusions and evaluation. This is where you explain what your data actually means.
A good conclusion should:
A good evaluation should:
❌ Don't just describe your graph explain what it means.
❌ Don't ignore anomalies always try to explain them.
❌ Don't forget units on graph axes.
❌ Don't confuse correlation with causation just because two things are linked doesn't mean one causes the other.
✅ Always link your conclusion back to your hypothesis.