# Suitability Evaluation of Urban Underground Space Development: A Case Study of Qingdao City
## 3 Research Method
### Weight Assignment of Evaluation Indicators  
Determining the weights of evaluation indicators is a crucial process in multi-objective decision-making. The rationality of indicator weights is closely related to the rationality of evaluation results. Any change in the weight of each indicator will affect the final evaluation results. Therefore, it is essential to find appropriate methods for assigning \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Number** & **Data Name** & **Data Sources** & **Data Type** \\ \hline
1 & 30 m resolution DEM & USGS & Grid \\
2 & Landform type & & Grid \\
3 & Fault distribution & China Geological Survey Bureau & Grid \\
4 & Rock and soil type & & Grid \\
5 & Distribution of soft soil layers & & Grid \\
6 & Surface water system & Standard Map of Shandong Province & Vector \\
7 & Groundwater water richness & China Geological Survey Bureau & Grid \\
8 & Distribution of geological hazards & & Vector \\
9 & Ground building height & China Resource Satellite Application Center & Vector \\
10 & Road and underground rail transit & National Basic Geographic Information Center & Vector \\
11 & Population density & National Bureau of Statistics & Grid \\
12 & Land price & China Land Price Information Service Platform & Grid \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Main data sources. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Evaluating Indicator** & **0.75–1** & **0.5–0.75** & **0.25–0.5** & **0–0.25** \\ \hline Surface elevation & \textless{}100 & 100–300 & 300–500 & \textgreater{}500 \\  & Erosion and & Structural erosion of & Mountain valley & Moderate to shallow \\ Landform type & accumulation quasi & low mountains and & impact plain & cutting in low to \\  & plain & hills & medium mountainous & medium mountainous \\ Slope & 0–5 & 5–14 & 14–31 & \textgreater{}31 \\ Rock and soil type & Excellent & Good & Medium & Bad \\ Soft soil thickness & None & \textless{}3.5 & \textless{}10 & \textless{}15 \\ Surface water & Non-buffer zone & - & - & Buffer zone \\ Hydrophilicity & \textless{}100 & 100–500 & 500–3000 & \textgreater{}3000 \\ Disasters such as & & & & Disaster point buffer \\ landslides and & Non-buffer zone & - & - & zone \\ collapses & & & & \\ Active fracture & Non-buffer zone & - & - & Fault zone buffer zone \\ Depth of influence of & None & 0–10 & 10–50 & \textgreater{}50 \\ surface buildings & & Subway hub & Subway Station & Road & Others \\ Transportation & & & & \\ accessibility & & & & \\ Population density & Very dense & Slightly dense & Commonly & Rare \\ Land price & \textgreater{}30 k & 20–30 k & 10–20 k & \textless{}10 k \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The grading and scoring systems of evaluation indicators in the main urban area of Qingdao City. weights to ensure the scientific and objective nature of the evaluation process. In this study, the Variable-Weight Analytic Hierarchy Process (VWAHP) method, which incorporates the concept of variable weights, was employed. This method overcomes the shortcomings of the traditional Analytic Hierarchy Process (AHP) [33], where fixed weights may lead to biased evaluation results. The concept of variable weights was initially proposed by Chinese scholar Professor [PERSON] in 1980 [34]. The introduction of variable-weight models aimed to address the limitations of traditional fixed-weight models in dealing with complex and dynamic decision-making environments, providing a more flexible and adaptable decision-making tool. The Variable Weight Analytical Hierarchy Process (VWAHP) adjusts weights based on varying conditions. First, define the hierarchy and criteria; then, construct pairwise comparison matrices and calculate initial weights; next, adjust weights dynamically according to specific conditions or contexts; then, recalculate the priority vectors and consistency; finally, aggregate the adjusted weights to determine the optimal decision.