基于计算机视觉的自然灾害监测预警系统设计与实现

Design and Implementation of A Natural Disaster Monitoring and Early Warning System Based on Computer Vision

自然灾害监测预警是减灾防灾的关键环节,但传统方法难以满足日益复杂的应用需求。文中提出了一种基于计算机视觉的智能监测预警系统,该系统以无人机、卫星等多源遥感数据为基础,通过深度学习驱动的目标检测、图像分割和时空预测模型,实现了对洪水、崩塌、滑坡等典型灾害的快速识别、精细刻画和动态预估。在贵州山区的试验表明,该系统在多个场景下表现出良好的灾情分析和预警能力,为提升自然灾害防治的智能化水平提供了新思路。

Natural disaster monitoring and early warning is a key link in disaster reduction and prevention,but traditional methods are difficult to meet the increasingly complex application needs.This paper proposes an intelligent monitoring and early warning system based on computer vision,which is based on multi-source remote sensing data such as drones and satellites.Through deep learning driven object detection,image segmentation,and spatiotemporal prediction models,the system achieves rapid identification,fine characterization,and dynamic estimation of typical disasters such as floods,collapses,and landslides.Experiments in mountainous areas of Guizhou have shown that the system exhibits good disaster analysis and early warning capabilities in multiple scenarios,providing new ideas for improving the intelligence level of natural disaster prevention and control.