低空遥感影像序列中典型灾损地物优化建模与演进评估模型研究

项目名称： 低空遥感影像序列中典型灾损地物优化建模与演进评估模型研究

项目编号： No.41271013

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 天文学、地球科学

项目作者： 王植

作者单位： 东北大学

项目金额： 71万元

中文摘要： 面向固体地球灾害（地震、滑坡、泥石流等）中建筑物和生命线工程（公路和铁路）的灾害应急监测与灾情快速评估重大需求，利用灵活机动的低空遥感观测平台获取超高分辨率、高重叠度的影像序列数据基础上，系统地研究：1）低空遥感影像序列中典型灾损地物三维点云数据高效生成算法及其质量评价模型，2）灾损地物三维点云自适应簇模型滤波分类与结构特征推理算法，3）复杂灾场环境下散乱三维点云数据中灾损地物优化建模与变化监测算法，4）灾损地物灰色关联分析、灾情动态评估及其应用试验。在固体地球灾害复杂灾场环境下，实现灾损地物三维信息快速高效获取与数据质量控制、灾损地物精细分类与结构特征提取、灾损地物优化建模与变化监测、灾情灰色关联分析与演进评估成套算法与技术体系。据此，为低空遥感影像序列数据处理奠定方法与技术基础，为国家重大固体地球灾害监测提供新方法，为灾情快速评估提供新模型，为国家防灾减灾、抗灾救灾提供理论与方法支持。

中文关键词： 低空遥感；点云数据；优化建模；三维建模；灾情评估

英文摘要： Based on extremely high resolution, high degree overlap of image sequences acquisition from flexible, low-altitude remote sensing platforms, for the significant demand of emergency monitoring and disaster rapid assessment of damaged buildings and lifeline (roads and railways) in solid earth hazards (earthquakes, landslides and debris flow, etc.), this research project systematically studies: 1) efficient generation algorithm and quality evaluation model of 3D point cloud data of disaster-damaged landmarks from the low-altitude remote sensing image sequences, 2) adaptive cluster model filter for classification and structural features reasoning algorithm of 3D point cloud of disaster-damaged landmarks, 3) optimize modeling and change detection algorithms of scattered 3D point cloud data in complex disaster environment, 4) gray relational analysis, disaster dynamic assessment and its experimental study on application of disaster-damaged landmarks. To realize quickly and efficiently three-dimensional information access and data quality control, fine classification and structural feature extraction, optimization modeling and change detection, disaster gray relational analysis and evolution assessment of disaster-damaged landmarks in complex disaster environment of the solid earth hazards. Hereby, to lay a foundation

英文关键词： Low-Altitude Remote Sensing；Point Cloud；Optimized Modeling；3D Modeling；Disaster Assessment