## 1 Introduction
[18] discussed the DEM modeling method of artificial terrain, such as roads, in cities from the perspective of surface water catchment analysis. This research is based on vehicle-mounted laser point cloud data. On the basis of urban feature classification data, the original point cloud data have been carefully filtered and manually edited. At the same time, the DEM of different terrain elements has been edited and processed according to the water catchment function, and, consequently, its modeling results are well expressed. However, it does not assign enough importance to the morphological expression of the road surface. [PERSON] et al. [16] took InSAR as the main data source to discuss the construction of the road DEM in different landforms. The study focused on the elevation error of the road DEM, and did not consider the morphological characteristics of road pavement. As mentioned above, although their types are diverse, roads are a typical artificial terrain [19], and the shapes of different roads have common characteristics. At this time, semantic information should be integrated into the modeling process, and the road DEM construction method should be designed to realize the effective expression of common characteristics of roads. Based on this approach, this study's research team first proposed a road DEM modeling method with the road boundary line as the morphological constraint. The main idea was to first use modeling elevation information to calculate the elevation value of the nodes on the sideline of the road, and then to obtain the densified points on the road surface by generating vertical lines between the corresponding nodes of the two road sidelines. Finally, the road DEM would be generated by interpolating the densified road elevation points [20; 21; 22]. The above research uses mainly large-scale DLG data. Subsequently, our team improved the aforementioned road DEM modeling method for dense point cloud data and achieved good results [23]. However, there are still deficiencies in the above studies, which are reflected in two main aspects. First, the above studies simplified the road into horizontal and vertical undulating banded artificial ground objects, which simplifies the road DEM modeling process, but results in great differences from the actual road shape. Second, the constructed road DEM has a good visualization effect, but it does not consider the water catchment process on the road surface; as a result, its usability is poor, and it cannot effectively facilitate research on issues such as urban surface water catchment simulation. Based on the above analysis, this study intends to further improve the road DEM construction method on the basis of existing research. The main work involves the following three aspects. First, the road sideline and the road centerline are taken as the road macro-morphological constraint line, and the upwards and horizontal undulation characteristics of the road extension are considered. Second, form constraint equations are constructed in the transverse and longitudinal directions of the road to ensure a smooth road surface. Third, with the intention of correctly simulating the surface water catchment process, a DEM elevation correction algorithm is designed so that the processed DEM can correctly simulate the road surface water catchment process.