Abstract: Visibility analysis is one of the most important parts of the spatial analysis in geographic information system, which is calculated based on the measurable models. However, it is hard to construct accurate models for the huge number of objects automatically because there is a mess of various objects in the urban area. Mobile laser scanning can acquire accurate three-dimensional information together with other physical properties (such as reflected intensity, echo waveform, etc.) on road and along roadside flexibly and efficiently, which provides an alternative data source for visibility analysis of the large-scale road scenes. This paper proposes a fast and robust depth-buffering method to analyze visibility based on point cloud data in road scenes efficiently and robustly. To achieve the goal, an adaptive spatial index construction strategy is firstly introduced based on the viewpoint and the corresponding field of view. Then the viewshed between the viewpoint and the field of view is analyzed efficiently using the depth-buffering method. The visualizing degree from the road to the traffic sign and the illuminated region on road of the street lamps are estimated respectively to verify the feasibility as well as the flexibility of the proposed method. The performance of the experiments shows that the proposed method can assist in monitoring the infrastructure health and decision support for the municipal planning department.