The SkyScanner project aims to deploy multiple UAVs to measure cloud micro-physical properties. So in order to efficiently guide the UAVs to the desired cloud in real time, I present a method of specific cloud tracking using a network of All-sky cameras. An All-sky camera is a camera that is able to view a hemispherical sky (2pi steradians). Such a system currently does not exist and so the plausibility of using this system were explored. The uncertainties in the deployment of the camera system were characterized and various techniques developed to calculate the spatial dimensions of the cloud are detailed. The first spatial parameter that needs to be obtained is the cloud base altitude. Two types of camera system were proposed to acquire the cloud base altitude: 1-camera system and 2-camera system. The 1-camera system is easy to set up but it requires inputs from other meteorological instruments. It needs to compare two images that were taken at a known time interval. The 2-camera system is independent within itself but requires the two cameras to be placed apart by a known separation distance. It utilizes the concept of stereographic imaging to triangulate the location of the desired cloud. With cloud base altitude, the images can be geo-referenced which allows cloud width and cloud height information to be extracted. Uncertainty analysis revealed that a higher pixel resolution for the camera sensor is desired and that the inclination angle of the camera is the most dominant uncertainty. The uncertainty of the measurements is the lowest at inclination angle of about 45 while the uncertainty is large at both the zenith (0 degrees) and the horizon (90 degrees). The 2-camera system’s technique to measure cloud base was also compared to data from a ceilometer. It was able to measure cloud base altitude to within the same precision as the ceilometer. As a proof of concept, the All-sky camera system has produced encouraging results to warrant further development.