Guérin, EricDigne, JulieGalin, EricPeytavie, AdrienJoaquim Jorge and Ming Lin2016-04-262016-04-2620161467-8659https://doi.org/10.1111/cgf.12821In this paper, we present a simple and efficient method to represent terrains as elevation functions built from linear combinations of landform features (atoms). These features can be extracted either from real world data-sets or procedural primitives, or from any combination of multiple terrain models. Our approach consists in representing the elevation function as a sparse combination of primitives, a concept which we call Sparse Construction Tree, which blends the different landform features stored in a dictionary. The sparse representation allows us to represent complex terrains using combinations of atoms from a small dictionary, yielding a powerful and compact terrain representation and synthesis tool. Moreover, we present a method for automatically learning the dictionary and generating the Sparse Construction Tree model. We demonstrate the efficiency of our method in several applications: inverse procedural modeling of terrains, terrain amplification and synthesis from a coarse sketch.I.3.3 [Computer Graphics]ModelingNatural PhenomenaModelingProcedural Modeling10.1111/cgf.12821177-187