We present a Markov chain model for land-use dynamics in a forested landscape. This model emphasizes the importance of coupling socioeconomic and ecological processes underlying landscape change. We assume that a forest is composed of many land parcels, each of which is in one of a finite list of land-use states. The land-use state of each land parcel changes stochastically. The transition probability is determined by two processes: the forest succession and the decision of landowners. The landowner tends to choose the land-use state which has a high expected discounted utility, i.e., the sum of the current and the future utilities of the land parcel. Landowners take the likelihood of future landscape changes into account when making decisions. We focus on a three-state model in which forested, agricultural, and abandoned states are considered. The land-use composition at equilibrium was analyzed and compared with the social optimum that maximizes the net benefit of all landowners in a society. We show that when landowners make a myopic choice focused on short-term benefits, their individual decisions tend to push the entire landscape toward an agricultural state even if the forested state represents the highest utility. This land-use composition at equilibrium is very different from the social optimum. A long-term management perspective and an enhanced rate of forest recovery can eliminate the discrepancy.