Bintrees based on longest edge bisection and hierarchies of diamonds are popular multiresolution techniques on regularly sampled terrain datasets. In this work, we consider sparse terrain pyramids as a compact multiresolution representation for terrain datasets whose samples are a subset of those lying on a regular grid. While previous diamond-based approaches can efficiently represent meshes built on a complete grid of resolution (2k +1)2 , this is not suitable when the field values are uniform in large areas or simply non-existent. We explore properties of diamonds to simplify an encoding of the implicit dependency relationship between diamonds. Additionally, we introduce a diamond clustering technique to further reduce the geometric and topological overhead of such representations. We demonstrate the coherence of our clustering technique as well as the compactness of our representation. Categories and Subject Descriptors I.3.5 [Computer Graphics]: Computational Geometry and Objec...