摘要
针对传统地质灾害预测方法时空分辨率不足、多源异构数据融合困难等问题,文章提出基于时空大数据的动态地质灾害预测框架。通过构建多源异构数据采集体系与时空耦合分析模型,结合混合预测算法,实现了滑坡灾害演化过程的多尺度解析与预警提前期优化。
In response to the issues of insufficient spatiotemporal resolution and difficulties in integrating multi-source heterogeneous data in traditional geological disaster prediction methods,this study proposes a dynamic geological disaster prediction framework based on spatiotemporal big data.By constructing a multi-source heterogeneous data collection system and a spatiotemporal coupling analysis model,combined with hybrid prediction algorithms,it achieves multi-scale analysis of landslide disaster evolution processes and optimization of early warning lead times.
作者
刘士峰
LIU Shifeng(Shandong Zouping Natural Resources and Planning Bureau,Zouping 256200,China)
关键词
时空大数据
动态
地质灾害
spatiotemporal big data
dynamic
geological disasters
