Landsat data is extremely useful for geographical analysis that aims to measure large visible changes in any system over time. Collecting data on this sort of scale by any other method is bascially unfeasible.

A good example of analysis that Landsat data can be used to perform would be looking at the change in sea ice cover in the Arctic. You could use the data to explore infinite questions in terms of how the ice cover is changing based on different time scales etc. One example would be measuring the rate at which the sea ice melts moving from winter to summer. To do this you could measure the area of sea ice cover in each Landsat image and then calculate a rate of change between them. The time interval you would select depends on the specific research question you aim to answer, but for example if you were looking at the rate of area loss, you would likely take every Landsat image during that period – ie. every image from maximum cover at the end of winter to minimum cover at the end of summer and look at the changes between each image. If you were looking at changes in sea ice area from winter to winter, then you would just select the Landsat images from around the time that maximum cover is expected to occur and compare the areas in each image.