We analyzed the relationship of landscape and environmental features on the genetic differentiation of Rhinella spinulosa (Wiegmann, 1834) in the Altiplano of Antofagasta (Chile). We performed three types of analyses at different spatial scales: (1) Considering all populations; (2) Grouping populations by watershed and by sub-watershed; and (3) Using the results of a spatial analysis of molecular variation (SAMOVA). Landscape features were incorporated using Geographic Information Systems, with three hypothetical dispersal models: (1) Euclidean distance (null model); (2) Least cost based on wetland locations; and (3) Least cost based on least slopes. We also included differences in temperature, precipitation and altitude among localities. The Akaike information criterion was used to select the best model and the relative importance of each variable in the model was estimated with partial regressions. We found a high genetic differentiation among populations (Fst = 0.693) and isolation by distance (r = 0.767). AMOVA showed that the watersheds explained 8.67 % of the genetic variance and sub-watersheds 35.99 %. At the largest spatial scale, considering all populations, the model that best explained genetic differentiation included Euclidean distance, altitude and annual precipitation. At a smaller scale, in two of three sub-watersheds (Río San Pedro and Salar de Atacama) the genetic differentiation was best explained by landscape variables (principally temperature and altitude). At the smallest scale, considering those populations that have diverged recently detected by SAMOVA, the genetic differentiation was best explained by the wetland-based route and annual precipitation. This approach revealed the importance of landscape features in the colonization of R. spinulosa in this zone.