ABSTRACT
This chapter focuses on the interface of images and (big) data through the perspective of machine-learning techniques, such as nowcasting and Next Frame Prediction. We take into account how this also includes a particular temporality that is mobilised in such AI techniques. The question of the production of possible futures becomes a driving force for a range of uses in terms of management of environments, creating models and scenarios, as well as creating a temporal feedback loop that characterises such uses of data sets, too. We address the relationship between environmental imaging and big data via an imaging technique relevant to time-critical images: Next Frame Prediction. NFP names a set of techniques aimed to predict the following frame in a video frame sequence, used, for instance, in the development of self-driving cars or robotic movements. We address this media technique as related to the use of predictive imaging in contemporary environmental research, such as agriculture and climate.
