In this poster, two major strategies for sampling phenomena with high rate of spatiotemporal variation, namely, multiscale sampling and adaptive sampling, are presented. Multiscale sampling is based on the hypothesis that a combination of sparse sensing along with auxiliary multiscale/multimode sensing will yield accuracy approaching exhaustive sampling. Adaptive sampling is a feature based sampling technique. Algorithms and simulation results for both techniques are demonstrated.
