Agricultural and environmental economists are in the fortunate position that a lot of what is happening on the ground is observable from space. Most agricultural production happens in the open and one can see from space when and where innovations are adopted, crop yields change, or forests are converted to pastures, to name just a few examples. However, converting images into measurements of a particular variable is not trivial, as there are more pitfalls and nuances than “meet the eye”. Overall, however, research benefits tremendously from advances in available satellite data as well as complementary tools, such as cloud-based platforms for data processing, and machine learning algorithms to detect phenomena and mapping variables. The focus of this keynote is to provide agricultural and environmental economists with an accessible introduction to working with satellite data, show-case applications, discuss advantages and weaknesses of satellite data, and emphasize best practices. This is supported by extensive Supplementary Materials, explaining the technical foundations, describing in detail how to create different variables, sketch out work flows, and a discussion of required resources and skills. Last but not least, example data and reproducible codes are available online.