The standard method of transforming a continuous distribution on the line to the uniform distribution on the unit interval is the probability integral transform. Analogous transforms exist on compact Riemannian manifolds, in that, for each distribution with continuous positive density, there is a continuous mapping of the manifold to itself that transforms the distribution into the uniform distribution. In general, this mapping is far from unique. We introduce a construction of a version of such a probability integral that is almost canonical. The construction is extended to shape spaces, Cartan-Hadamard manifolds, and simplices. The probability integral transform is used to derive tests of goodness of fit from tests of uniformity. Illustrative examples of these tests of goodness of fit are given involving (i) Fisher distributions on the 2-sphere, (ii) isotropic Mardia-Dryden distributions on the shape space of triangles in the plane. Their behaviour is investigated by simulation.