Basics of Modern Photogrammetry

Digital photogrammetry emerged around 1980 and decisively accelerated the automation of workflows for converting images into georeferenced datasets for a wide range of appli-cations. The development of innovative technologies, including metric digital cameras; the miniaturization of powerful computers; and positioning and orientation systems, has accelerated since the turn of the century. Advanced photogrammetric and computer vi-sion algorithms have been developed and implemented in software, allowing many work-flows to run on computers from begin to end. Today, final products can be generated largely automatically, minimizing the timespan between image capture, even up to real-time, and acquiring the necessary datasets for the task at hand,. Thanks to the wide avail-ability of commercial and open-source software, the scope of applications has expanded rapidly, leading to a significant growth in the number of new users of photogrammetry. This article aims to serve this new group by providing an overview of the technologies underlying current photogrammetric workflows, starting with the geometric fundamen-tals of camera modeling and georeferencing. Next, we examine the algorithms that have revolutionized workflows and are known by various names, particularly: image match-ing, computer stereo vision, and structure from motion (SFM). Next basic characteristics of final photogrammetric products are briefly discussed. This is followed by methods to assess accuracy of the final product, a key component of extracting geometric information from imagery. The discussion section provides tips for selecting suitable textbooks to deepen your knowledge.