关键词: 对称交互熵(SCE), 地质灾害, 风险评估, 级差最大化组合赋权, 地面沉降

Abstract:

To accurately identify the distribution of geological disaster risk in the 2 630 km² hilly and mountainous areas of southern Jinan City and to support refined regional disaster prevention and mitigation, a multi-source-data-integrated assessment method at the village and community was proposed. First, surface deformation field was obtained from L-band Synthetic Aperture Radar (SAR) data acquired by the domestic Lutan-1 satellite using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique. Then an assessment index system of “hazard source-exposed elements” was constructed by integrating multi-source information, including geological hazards, socio-economic data, topography, and meteorological factors. Finally, the level difference maximization combination method was employed to integrate the Analytic Hierarchy Process (AHP) and the Entropy Weight Method(EWM) for determining subjective and objective combination weights. Subsequently, a risk assessment model was constructed by introducing SCE multi-attribute decision-making model. The results show that 163 high-risk villages and communities are identified among the 1095 villages and communities in the study area, primarily concentrated in Zhangqiu District and Laiwu District. The maximum surface subsidence rate, the number of geological hazard sites, and the resident population are the three main factors affecting geological disaster risk in the study area. For high-risk villages and communities, priority should be given to strengthen safety-production supervision of open-pit mines, hazard inspection and rectification for self-built houses, hillside restoration, waterlogging prevention and control, and geological disaster monitoring and early warning.

Key words: symmetric cross entropy(SCE), geological disaster, safety risk assessment, level difference maximization combined weighting, ground subsidence