利用WebGIS的灾害应急响应系统设计与实现OA

To address the urgent demand for rapid assessment and decision support in sudden geological disasters,we developed a disaster emer-gency response system based on WebGIS.The system is constructed on the Django framework,integrates the Cesium visualization engine,Post-greSQL spatial database,and semantic segmentation models based on deep learning,and provides core functionalities such as image data manage-ment,model inference,disaster element recognition,statistical analysis,and chart-assisted visualization.The system comprises four major mod-ules,including fundamental data management,disaster element identification,disaster analysis,and system administration,and can automatically detect and classify key disaster-related features,such as landslide bodies,damaged buildings,roads,vegetation,and water bodies.Furthermore,we adopted a pixel-proportion-based disaster quantification approach,and realized rapid assessment and multi-dimensional expression of disas-ters through the interactive linkage between statistical charts and spatial maps.Application tests in typical landslide disaster scenarios verify the high recognition accuracy,stable visualization performance,and efficient response capability of system,demonstrating its potential for improving the intelligence and automation of disaster emergency response.