You do not need an expensive imagery licence to start working with satellite data. Two long-running public programmes cover almost the whole planet for free: the European Space Agency's Sentinel-2, which revisits most places every five days at 10-metre resolution in its visible and near-infrared bands, and the United States Landsat programme, whose archive reaches back to the 1970s at 30-metre resolution. Both are genuine open data, not just free previews, so you can download full scenes, analyse them, and use the results in your own maps and reports with proper attribution.

Before you open any download portal, write down exactly what you need to see. A land-cover map of a town needs different imagery from a crop-health check of a single field or a before-and-after view of a flood. Note your area of interest, the date range that matters, and the smallest feature you must be able to recognise. A 10-metre Sentinel-2 pixel is about the size of a tennis court, so it can show a field, a road, or a river bend, but not a car or a fence line. Landsat at 30 metres is coarser still, but its decades-long archive makes it the better choice for change over time. Matching the sensor to the question first saves you from downloading gigabytes of data you will never use.

For Sentinel-2, start at the Copernicus Data Space Ecosystem, where you can draw your area on a map, filter by date and cloud cover, and download scenes in GeoTIFF format. For Landsat, the United States Geological Survey's EarthExplorer works the same way and also hosts older missions and elevation data. Both services ask you to create a free account, which takes a few minutes. Set your maximum cloud cover low, often under 20 percent, for a first project, because clouds hide the ground and confuse simple analyses. Download the level of product labelled as surface reflectance when it is offered, since that version has already been corrected for atmospheric haze and is easier to compare across dates.

In QGIS, use Layer, Add Layer, Add Raster Layer and select the downloaded GeoTIFF files. Sentinel-2 scenes arrive as separate files per band, so add the red, green, blue, and near-infrared bands together, or use the virtual raster builder to stack them into one file. Check that the coordinate reference system reads as WGS 84, which is the usual default for these products, and that your project uses the same system so layers line up. If the image looks washed out, adjust the band rendering stretch in the layer properties; satellite data stores a wide range of values, and the default display often needs a stretch before colours look natural. Save your project immediately, with a clear folder for raw downloads and a separate folder for outputs.

Once the image displays correctly, try a true-colour composite and then a false-colour composite that swaps the near-infrared band into the red channel. Healthy vegetation will jump out in bright red, while water goes dark and bare soil looks pale. That single comparison teaches you more about how satellite bands work than any textbook diagram. Next, use the raster calculator to compute a basic vegetation index from the red and near-infrared bands. Keep the area small for this first run, check the result against a familiar base map, and write down what worked and what confused you. Those notes become your checklist for the next, larger project.

Free imagery rewards patience more than speed. Pick one small area, one clear question, and one sensor, and work the whole chain from download to map before you branch out. Once that loop feels easy, adding new sensors, larger areas, and time series is simply repeating a workflow you already trust.