With technological evolution, 3D virtual environments continuously increase in complexity; such is the case with multiscale environments, i.e., environments that contain groups of objects with extremely diverging levels of scale. Such scale variation makes it difficult to interactively navigate in this kind of environment since it demands repetitive and unintuitive adjustments in either velocity or scale, according to the objects that are close to the observer, in order to ensure a comfortable and stable navigation. Recent efforts have been developed working with heavy GPU based solutions that are not feasible depending on the complexity of the scene. We present a spatial partitioning heurístic for automatic adjustment of the 3D navigation speed in a multiscale virtual environment minimizing the workload and transferring it to the CPU, allowing the GPU to focus on rendering. Our proposal describes a geometric strategy during the preprocessing phase that allows us to estimate, in real-time phase, which is the shortest distance between the observer and the object nearest to him. From this unique information, we are capable to automatically adjusting the speed of navigation according to the characteristic scale of the region where the observer is. With the scene topological information obtained in a preprocessing phase, we are able to obtain, in real-time, the closest object and the visible objects, which allows us to propose two different heurístics for automatic navigation velocity. Finally, in order to verify the usability gain in the proposed approaches, user tests were conducted to evaluate the accuracy and echiency of the navigation, and users subjective satisfaction. Results were particularly significant for demonstrating accuracy gain in navigation while using the proposed approaches for both laymen and advanced users.