In this project I got to work with a fun dataset. The Sentinel-2 satellite images are openly and freely accessible provided in the Earth observation program Copernicus. A group of researchers put some of them together to create novel dataset consisting out of 10 classes with in total 27,000 labeled and geo-referenced images. I used a deep learning approach, utilizing the RESNET50 architecture, to find an algorithm to classify the land use and land cover of the 64x64 pixel pictures as accurate as possible.