This is the third and last part of a blog post series about using remote sensing data to classify the earth’s surface. In this post we will finally walk through the typical steps it takes to classify remote sensing images with a supervised classifier to derive a land use/land cover map.

This is a three parts series about classification of remote sensing images. Remote sensing images are already beautiful enough to only look at, but they can also be used for mapping the earth’s surface. When the task is to map categorical classes, such as forest, water, meadow, farmland, residential area, etc. the task can be solved by classification, often more specifically called land use and/or land cover classification.