This Master’s thesis provides an overview of the methods to automatically detect different landscape processes in thermokarst areas. As the Arctic region is vulnerable to climate change, different developments lead to a fast-changing landscape. Especially three different processes are of interest: coastal erosion, retrogressive thaw slumps and thermokarst lakes. To detect the influence of these processes on the environment, different methods have been tested. As a basis for the evaluation Planet images were used. This data is acquired via nanosatellites with a resolution of 3 meters. Due to their small size and low cost, more than 200 active satellites are in the orbit monitoring the entire earth daily. With the help of a Python script, an automatic detection is possible, which leads to a classification afterwards. This is followed by an evaluation of the generated data. This data showed that the coast of Alaska is eroded at over 20 meters per year, the growth rate of thaw slumps in Noatak Valley exceed more than 25 meters per year. Surprisingly, thermokarst lakes in Siberia tend to be stable and no drainage could be detected.