Human understanding of ecological and social dynamics is clouded by uncertainty, and landowners may not know the true forest-use value. In order to deal with the uncertainty, we develop a decision model of deforestation under social learning. We assume that a forest is composed of a number of land parcels that are individually managed; landowners choose whether or not to cut trees by comparing the expected utilities of forest conservation and deforestation; landowners learn utility values not only from their own experiences, but also by exchanging and sharing information with others in a society. We observed three possible outcomes: a stationary-forested landscape, a stationary-deforested landscape, and a cyclic-forested landscape induced by synchronized deforestation. Synchronized deforestation, which resulted in a resource shortage in a society, was likely to occur when landowners employed a short-term memory. Social welfare under a cyclic-forested landscape can be significantly lower than that of a stationary-forested landscape. This implies that learning and remembering past experiences are crucial to prevent overexploitation of forest resources and degradation of social welfare.