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This work presents an automatic algorithm for extracting vectorial land registers from altimetric data in dense urban areas. We focus on elementary shape extraction and propose a method that extracts rectangular buildings. The result is a vectorial land register that can be used, for instance, to perform precise roof shape estimation. Using a spatial point process framework, we model towns as configurations of and unknown number of rectangles. An energy is defined, which takes into account both low level information provided by the altimetry of the scene, and geometric knowledge about the disposition of buildings in towns. Estimation is done by minimizing the energy using simulated annealing. We use an MCMC sampler that is a combination of general Metropolis Hastings Green techniques and the Geyer and Møller algorithm for point process sampling. We define some original proposition kernels, such as birth or death in a neighborhood and define the energy with respect to an inhomogeneous Poisson point process. We present results on real data provided by the IGN (French National Geographic Institute). Results were obtained automatically. These results consist of configurations of rectangles describing a dense urban area. [ABSTRACT FROM AUTHOR]