Abstract Navigation in 3D terrain is considered to be a challenging task and requires virtual camera control skills such as zooming, panning and tilting. Novice users can easily get distracted and disoriented that may result with lost in space. Methods to overcome the virtual environment exploration problems are still being researched to assist users during their journey inside virtual environments. Assisted camera control techniques require viewpoint computation and path planning. This paper introduces a novel approach to navigate over a 3D terrain with minimal loss of information. We exploit the concept of the Viewpoint Entropy for best view determination and use our Greedy N-Best View Selection for visibility calculations. We integrate road network data to extract regions for detailed visibility analysis in subsections of the terrain. In order to connect the calculated viewpoints an evolutionary programming approach for Traveling Salesman problem is used where the distance objective is minimized. The generated tour is presented using Google Earth framework for terrain exploration where we can get real data streams. The computed and planned viewpoints reduces human effort when used as starting points for scene exploration or generating the representative images of the terrain dataset. The proposed framework can be integrated into 3D game engines or any urban visualization system to give quick glimpse or tour of the environment for the novice users without the help of prior planning