Ca2+ is an important second messenger that translates extracellular stimuli into intracellular responses. Although there has been significant progress in understanding Ca2+ dynamics in organs such as the brain, the nature of Ca2+ signals in the kidney is still poorly understood. Here, we show that by using a genetically expressed highly sensitive reporter (GCaMP6s), it is possible to perform imaging of Ca2+ signals at high resolution in the mouse kidney in vivo. Moreover, by applying machine learning-based automated analysis using a Ca2+-independent signal, quantitative data can be extracted in an unbiased manner. By projecting the resulting data onto the structure of the kidney, we show that different tubular segments display highly distinct spatiotemporal patterns of Ca2+ signals. Furthermore, we provide evidence that Ca2+ activity in the proximal tubule decreases with increasing distance from the glomerulus. Finally, we demonstrate that substantial changes in intracellular Ca2+ can be detected in proximal tubules in a cisplatin model of acute kidney injury, which can be linked to alterations in cell structure and transport function. In summary, we describe a powerful new tool to investigate how single cell behavior is integrated with whole organ structure and function and how it is altered in disease states relevant to humans.