Abstract: Automatic extraction of building and tree crown in airborne LIDAR data is an essential work of city model reconstruction. In this paper, multi-marked point process based method is used to extract building and tree crown from point cloud feature image, which generated from airborne LIDAR data. At first, the Gibbs free energy change model is build according to the geometric feature of the object. This model contains both a data coherence term which fits the objects to the data and a prior term which incorporates the prior knowledge of the plantation geometric properties. Then the previously defined model will be sampled using a RJMCMC (Reverse Jump Markov Chain Monte Carlo) algorithm and optimized using a simulated annealing algorithm. The experimental results show that our method is capable of efficient extracting building and tree crown from airborne LIDAR data with great robustness.