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Land changes are the result of a complex web of interaction between human and biophysical factors, which act over a wide range of temporal and spatial scales. In this paper we conceptualize spatial relations among geographic objects at different scales. We analyze two types of spatial relations: hierarchical, which handles the interaction of nested objects at different scales (countries, states and municipalities, for example); and a network-based relation, which handles action-at-a-distance types of interaction (market chains, for instance) of objects at different scales (such as farms in Central Amazonia to soybean market consumers at the global scale). We implemented such relations in the Terralib environment, in which they can be constructed using selected strategies, and then used in dynamic models. We exemplify the use of such concepts in a real-world case study in the Brazilian Amazonia. We conclude that combining hierarchical and network-based spatial relations provide a comprehensive conceptual framework to include top-down and bottom-up interactions and feedbacks in multi-scale landchange models.