To outperform state-of-the-art navigation systems customized for planetary settings, the navigation algorithms need an immense amount of environmental data to be trained on, which because of its scarcity constitute a bottleneck. For this reason, we are developing our own high-fidelity lunar simulation environment. Based on scientific principles and recent advancements, it integrates lunar environment characteristics such as regolith properties, soil bearing capacity, illumination conditions, slope, temperature conditions, ice-deposits locations, and many more features that will be used for the training of our algorithms. This simulation environment leverages the state-of-the-art technologies in data integration and visualization thereby providing a realistic view and data of lunar environments. This can be used to train the navigation algorithms with precision thereby enabling robust and efficient navigation algorithm design and development suitable for lunar surfaces.