This lecture provides a comprehensive introduction to the Image Processing for Earth Observation course, covering topics such as the history of Earth observation, the objectives of the course, the administration details, evaluation criteria, logistics, and the course content. The lecture also delves into the interdisciplinary nature of Earth observation, the relevance of Earth observation in various domains, and the steps involved in image processing for Earth observation. Concepts such as data fusion, feature extraction, classification, unmixing, regression, and the manipulation of images using Python are also discussed.