 Remote sensing is a relatively new discipline that has come to maturity in the past decade or so due to the confluence of several different disciplines and technologies like physics, engineering, computer science, the internet, sensors, and their deployment on platforms ranging from satellite constellations, aircraft, and unmanned aerial systems. The deployment of novel sensors like multispectral, hyperspectral, radar, lidar, to name a few, has created a data deluge, and this data needs to be converted into information such that it goes to work in the public policy domains. There is an increasing need for a remote sensing literate workforce at all levels of our society. In this course, we are going to learn about remote sensing platforms, the data types that are collected, and how these are converted to actionable information for decision making. The data collected has to be pre-processed and then classified to generate map products to address complex geospatial issues and problems. We will learn image processing techniques including multi-sensor fusion, image segmentation, geographic object-based image analysis, also known by the acronym Geobia, image classification, and how the resulting map product is analyzed. Remote sensing is a very central component of contemporary geospatial science and technology, and it is a very powerful tool for the stewardship of our Earth, and I do look forward to seeing you in class.