ABSTRACT
As many underground structures have been installed in urban areas, various types of ground subsidence have occurred around the world. In this paper, the correlation between the recorded ground subsidence and the density of underground structures in Seoul was studied. The relationship between the density of buried structures using GIS spatial digital data for 6 types of underground utilities (water, sewer, power, heat, communication, natural gas) and ground subsidence was optimized based on the concept of normalized line density. The effect of each buried utility on the recorded ground subsidence was optimized using weight factors generated from a random function. An algorithm was developed that can optimize the line density of buried utilities along with the 6 weight factors and the correlation between the normalized line density and the recorded ground subsidence. As a result of analyzing the normalized line density, it was found that more than 80% of recorded ground subsidence occurred in areas with higher normalized line density when the optimization algorithm was applied. It is concluded that the proposed optimization algorithm can be usefully applied to the analysis of the risk of ground subsidence using GIS digital data of buried utility structures.
