Abstract. The widespread availability of 3D city models enables us to answer a wide range of spatial visibility queries in the presence of obstacles (e.g., buildings). Example queries include "what is the best position for placing a billboard in a city?" or "which hotel gives the best view of the city skyline?". These queries require computing and differentiating the visibility of a target object from each viewpoint of the surrounding space. A recent approach models the visibility of a fixed target object from the surrounding area with a visibility color map (VCM ), where each point in the space is assigned a color value denoting the visibility measure of the target. In the proposed VCM, a viewpoint is simply discarded (i.e., considered as non-visible) if an obstacle even slightly blocks the view of the target from the viewpoint, which restricts its applicability for a wide range of applications. To alleviate this limitation, in this paper, we propose a scalable, efficient and comprehensive solution to construct a VCM for a fixed target that considers the partial visibility of the target from viewpoints. More importantly, our proposed data structures for the fixed target support incremental updates of the VCM if the target moves to near-by positions. Our experimental results show that our approach is orders of magnitude faster than the straightforward approach.