The methods we use to produce geomorphic data are deeply interwoven with the geomorphic questions we choose to ask, and with the geomorphic theories we construct. Authors have described major changes in the history of geomorphology in terms of theoretical shifts and/or social-cultural changes, but it seems clear that shifts in methodological practices also can produce deep changes in geomorphology as a whole. The camera has had a long, illustrious, and complex history as a geomorphic tool, and as such is useful for assessing larger geomorphological concerns and themes. The camera is also a symbol of the ongoing revolution in geomorphology from a data-poor to a data-rich subject; this revolution is built upon many methodological changes, and it has had many side-effects. The interrelated history of cameras and fluvial geomorphology provides an illuminating case study in past and present changes in the geomorphic sciences. Some past geomorphic practices, such as using photos as descriptive evidence for verifying geomorphic theory, remain as important approaches today. Other camera-based practices have dwindled to some degree, such as the production of large-area topographic maps through traditional aerial-photogrammetry, which have been overtaken by alternative methods such as Lidar and interferometric radar. And newer camera-based techniques, such as structure from motion photogrammetry, are at the heart of the recent democratization of geomorphic data. As the modern data revolution progresses, it is important to ask questions such as “who has been part of the data revolution, and what have been their motivations?” and “have winners and losers been produced as part of the data revolution?” Not all effects of the data revolution have been completely positive; many geomorphologists feel overwhelmed by big data expectations and methodological concerns. From a philosophy of science perspective, the moves toward population-like geomorphic data have strained “normal” inductive inference procedures, and recent research has brought to light inferential alternatives such as advanced data mining and the hypothetico-deductive approach. Even so, most current analytical techniques appear to be lagging behind the newly-introduced big data, producing “new wine in old bottles”: new data for old analyses. Beyond pure geomorphic research, the camera and its derivatives are also part of profound shifts in educational and outreach expectations and practices. Clearly, the data revolution in geomorphology is still in its infancy, and much of that revolution has been wrought by the humble camera.