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The evaluation of urban underground space (UUS) suitability involves multiple indicators. Assigning weight to these indicators is crucial for accurate assessment. This paper presents a method for spatially variable weight assignment of indicators using the order relation analysis method (G1-method), the entropy weight method, an improved grey relational analysis (GRA) and a set of spatial weight adjustment coefficients. First, the subjective and objective weights of indicators for engineering geological and hydrogeological conditions were determined by the G1-method and entropy weight method, respectively, and their combined weights were then obtained using the principle of minimum discriminatory information. This study highlighted the impact of surface restrictions, such as buildings, on UUS, and the degree of the influence of these buildings gradually decreased with the increase in depth of the rock and soil mass in UUS, which resulted in changes in weights of indicators with depth. To address this issue, a coefficient was defined as the standardized value of the ratio of additional stress applied by restrictions to the self-weight stress of soil at the same depth to modify the combined weights so that all weights of indicators could vary in space. Finally, an improved GRA was used to determine the suitability level of each evaluation cell using the maximum correlation criterion. This method was applied to the 3D suitability evaluation of UUS in Sanlong Bay, Foshan City, Guangdong Province, China, including 16 evaluation indexes. This study comprehensively considered the influence of multiple factors, thereby providing reference for evaluating the suitability of UUS in big cities.

Urban development continues to reduce the amount of available ground space. The development of underground space is thus gathering increasing attention to alleviate ground congestion. However, there is currently a lack of a three-dimensional (3D) evaluation method to systematically evaluate the geological conditions of underground space and possible geological disaster risks caused by rock and soil masses. This paper presents an engineering geological suitability assessment framework based on 3D geological modeling and an analytic hierarchy process (AHP)-cloud model. As the basis for 3D evaluation, a 3D structural model of the study area is established based on the drilling data and geological profiles. Then the structural model is partitioned to obtain interpolation grids, and the ordinary Kriging interpolation method is applied to attribute interpolation. All the attributes are exported from the geological model, and the rock and soil masses are divided into four categories according to their engineering properties, namely soft soil, sandy soil, cohesive soil, and rock, upon which a targeted hierarchy structure is established based on the attributes that impact the suitability. This paper introduces the cloud model to characterize the uncertainty of these evaluation indexes, which synthesizes an AHP method, thus it is referred to as the AHP-cloud model. This new model is used to evaluate the geological suitability of underground space in the Sanlong Bay district, Foshan City, Guangdong, China. In addition, we also determine the excavation difficulty at different depths according to the lithology and weathering degree of the study area. The limitations and future directions of the proposed method are discussed, including the influencing factors and weight determination.