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This paper proposes a method of reconstructing a scalar field by adaptively choosing sampling locations and using the measurements obtained from those locations to reconstruct an estimate of the underlying field using Gaussian process regression. Spreading sampling points evenly over the field may not always be effective if the field is not uniformly distributed and the maximum number of measurements...