This report summarizes the ATMOS project (Advanced Terrain Analysis for Modelling and Simulation) 2018-2020, with in the Swedish Armed Forces' R&D program. The objective of ATMOS has been to develop methods and algorithms for automated terrain analysis aiming at increasing the quality of different types of simulations, and to show the benefits of tools offering automated support to interpret geographical data when planning military ground operations. Within ATMOS the tool ASTERIKS has been developed, that allows users to analyse the terrain in real-time from different perspectives through a set of variable parameters. In a first version, the functionality of ASTERIKS focuses on analysing visibility conditions and physical cover to support evaluation of vantage points. The tool was validated in an initial round of trials for planning on platoon-level but its applicability is quite general. The trial was conducted as a stand-alone exercise in combination with demonstrations and interviews. The purpose was to give the participants the opportunity to choose suitable terrain areas for closer inspection. The task can be approached in several ways, and a thorough validation of the tool would require a greater number of participants and situations than what was possible to realize within this project. A method for identifying alternatives regarding avenues of approach for combat vehicles has also been developed. The method uses previously developed path planning algorithms and involves conducting a large number of path searches and aggregating those into a summarizing picture that shows possible alternatives. The method is deemed primarily applicable in simulation contexts, e.g. to direct simulated units towards tactically advantageous terrain, thus reducing the need for manual work in scenario set-up phases, and to produce large quantities of representative training data for development of machine learning algorithms. The project has also contributed to integrating terrain analysis functions in the NetScene simulation engine, e.g. to support development of functions for optimal sensor planning in FOI Multi Sensor Simulation Lab (MSSLab), and in the FLAMES simulation framwork to increase the quality of combat simulations of ground vehicles.