甘肃、重庆示范区滑坡监测预警数据

依据考核指标，研发机器学习远程预警方法及可视化系统，构建动态反分析机器学习与专家交互的会商模式；研发空-地窄带物联网融合传输网关，建设基于国家-省-市-县地质灾害监测预警物联网的动态信息平台；研发基于多源数据融合的在线预警系统，实现“设备-平台-会商”协同预警，开展滑坡崩塌监测预警应用示范，形成了示范区滑坡监测预警数据库（35.30 MB）。Following the assessment criteria, machine learning-based remote early warning methods and visualization systems were developed, and a consultation mode integrating dynamic reverse analysis-based machine learning and expert interaction was constructed. An air-ground Narrow Band Internet of Things (NB-IoT) converged transmission gateway was developed, and a dynamic information platform based on the national, provincial, municipal, and county-level geological disaster monitoring and early warning IoT network was built. A multi-source data fusion-based online early warning system was developed, realizing the collaborative early warning of "equipment-platform-consultation". Application demonstrations for landslide and collapse monitoring and early warning were carried out, and a landslide monitoring and early warning database for the demonstration zone (35.30 MB) was established.

搜集汇总

背景与挑战

背景概述

该数据集是甘肃和重庆示范区滑坡监测预警的专项数据，基于国家重点研发计划项目，研发了机器学习预警方法、空-地窄带物联网传输网关和多源数据融合在线系统，实现了“设备-平台-会商”协同预警，数据量35.39MB，包含5个文件，适用于地质学和监测技术领域的研究与应用。