Forming Planetesimals in Solar and Extrasolar Nebulae

Planets are built from planetesimals: solids larger than a kilometer which grow by colliding pairwise. Planetesimals themselves are unlikely to form by two-body collisions; sub-km objects have gravitational fields individually too weak, and electrostatic attraction is too feeble for growth beyond a few cm. We review the possibility that planetesimals form when self-gravity brings together vast ensembles of small particles. Even when self-gravity is weak, aerodynamic processes can accumulate solids relative to gas, paving the way for gravitational collapse. Particles pile up as they drift radially inward. Gas turbulence stirs particles, but can also seed collapse by clumping them. While the feedback of solids on gas triggers vertical shear instabilities that obstruct self-gravity, this same feedback triggers streaming instabilities that strongly concentrate particles. Numerical simulations find that solids 10-100 cm in size gravitationally collapse in turbulent disks. We outline areas for progress, including the possibility that still smaller objects self-gravitate.Comment: To appear in Annual Reviews. This review is intended to be both current and pedagogical. Incorporates suggestions from the community; further comments welcome. v2: Single-space

Automatic recognition of impact craters on the martian surface from DEM and images

Impact craters are the most outstanding and attractive geomorphological features on the surface of the planets, showing variety and complexity of the surface morphology. The accurate recognition of impact craters on Mars is very useful to analyze and understand the relative dating of Martian surface. In this chapter, four crater-detection methods have been presented and discussed with various extent of discrimination ability on Martian images or topography data. Themodified ad boosting approach demonstrates the best performance in classification of craters, while the algorithms based on topography data have low efficiency in automatic detection. Comparing to previous solutions, the modified ad boosting method has greatly improved the detecting performance of the algorithm and reduced detection time. © Springer-Verlag Berlin Heidelberg 2015