Turbulence near hot surfaces such as desert terrains and roads during the summer, causes shimmering, distortion and blurring in images. While recent works have focused on image restoration, this paper explores what information about the scene can be extracted from the distortion caused by turbulence. Based on the physical model of wave propagation, we first study the relationship between the scene depth and the amount of distortion caused by homogenous turbulence. We then extend this relationship to more practical scenarios such as finite extent and height-varying turbulence, and present simple algorithms to estimate depth ordering, depth discontinuity and relative depth, from a sequence of short exposure images. In the case of general non-homogenous turbulence, we show that a statistical property of turbulence can be used to improve long-range structure-from-motion (or stereo). We demonstrate the accuracy of our methods in both laboratory and outdoor settings and conclude that turbulence (when present) can be a strong and useful depth cue.