As seen in previous sections, all the data tends to migrate on the cloud. In order to standardize the access to them, there are common programming languages to process the data hosted in that infrastructure. These languages are mainly JavaScript, Python and R.

The Internet is full of tutorials and resources to learn these languages and it is very important to pay attention to the news and updates made to the platforms that use them.The most useful way to do this is to attend to conferences such as FOSS4G (Free and Open Source Software for Geospatial). https://2021.foss4g.org/

Why open source software? Because more and more people prove their skills by creating new robust and accessible infrastructures and software, in addition to providing free access to everyone. Then, they are easy to use and quite straightforward.

Google Earth Engine (ready to use with JavaScript and Python) provides the data access to most common remote sensing images taken through the history. They also provide training and documentation. https://developers.google.com/earth-engine

R and Python are the most common programming languages used for desktop applications as well. The Anaconda framework is a ready to use notebook with all python functionalities. In order to know more, the University of Tartu has an open access documentation: https://kodu.ut.ee/~kmoch/geopython2020/