Economic Activity & Energy Practical Skills

Every piece of fieldwork starts with a question. In an energy enquiry, that question is usually about a development like a wind farm or renewable energy plant — something being built, or already built, that changes the local area.

Think of it like this: you wouldn't set off on a road trip without deciding where you're going first. The aim is your destination — a broad statement of what you want to find out. The hypothesis is your prediction about what you'll discover when you get there — a statement you can test and either support or reject with your data.

Typical energy-enquiry questions that lead to aims include:

• What are people's views and opinions regarding a new wind farm?
• Why do people have the views and opinions they do?
• What environmental impact does a new renewable energy plant have on the surrounding area?

From these, you can write clear aims and hypotheses:

Once the aim and hypothesis are set, four practical steps follow, in this order:

1. Selecting the sites — using sampling
2. Deciding on equipment
3. Considering health and safety — completing a risk assessment
4. Data collection

Here's the problem: you can't survey every single square metre around a wind farm, and you definitely can't interview every person who lives nearby. It would take forever, and it's simply not practical. So geographers use sampling — a systematic way of choosing a smaller, manageable set of sites or people that still gives a fair, representative picture of the whole area.

The whole point of sampling is to reduce bias. If you just picked sites you liked the look of, or only asked people who happened to agree with you, your data would be skewed and untrustworthy. A good sampling strategy makes sure your results reflect reality, not your personal preference.

The Three Main Sampling Strategies

The equipment list for an economic activity and energy enquiry is refreshingly simple — nothing exotic here, just practical tools that let you record data accurately and safely in the field.

Before any fieldwork begins, students must think through what could go wrong and how to manage it — this is a risk assessment. It's not just a box-ticking exercise; it genuinely protects you while you're out collecting data in an unfamiliar place.

For economic activity and energy fieldwork specifically, the risks tend to cluster around four areas:

The exact methods used depend on your aim and hypothesis — but for energy fieldwork, three data collection methods dominate: questionnaires, environmental quality surveys, and photographs/field sketches. Good fieldwork always mixes quantitative data (numbers you can measure/count) with qualitative data (opinions, descriptions, images) — because numbers tell you what is happening, but words and images tell you why and what it looks like.

Questionnaires gather the attitudes and opinions of local people towards a wind farm expansion or a new renewable energy plant. A well-designed questionnaire mixes different question types so you collect a rich, useful dataset:

The big advantage of questionnaires is that they let you gather a large data sample relatively quickly, and — because you can mix question types — you get both qualitative and quantitative data from one method.

An Environmental Quality Survey is a scoring sheet used to compare different sites around an energy development. A survey is completed for each site, scoring a range of features on a numerical scale — typically from −2 (very negative) to +2 (very positive), with 0 as neutral.

Photographs and field sketches are both forms of qualitative data. In an energy enquiry, they're brilliant for capturing the visual reality of a development — showing new energy infrastructure (like turbines or solar panels) and its impact on the surrounding landscape. Photographs are also handy for simply illustrating what data collection methods looked like on the day (e.g. a photo of a student conducting a questionnaire).

Field sketches, in particular, have a real edge over photographs for analysis: you actively choose what to draw and what to leave out, which forces you to notice detail. And because you draw them yourself, you can label and annotate them directly.