Joint Analysis Of Seismic Damage Information Of Multi - Source Remote Sensing Data Buildings

Earthquake is one of the worst natural disasters that causing people’s lives and property loss. Remote sensing technology plays an important role in gathering building damage information, which is crucial for relief and reconstruction work after strike. Remote observation has become an essential method for data collection in the initial stage of earthquake relief, since it can provide disaster information in a large scale objectively and effectively.Nowadays, remote observation for seismic damage information takes advantage of mainly two types of sensors:optical sensors which observe reflective and radiometric characteristics passively, and radar sensors which actively emit microwaves. High-resolution optical images can be used to assess damage at building level. Unfortunately, this method is not applicable in regions with cloud cover or snow. On the other hand, radar sensors are capable of observing the ground irrespective of weather conditions at any time of the day, and therefore have been gaining prominence as a reliable tool for grasping the overall picture of damage from disasters. In recent years, Light Detection and Ranging (LiDAR) is also used in building assessment after earthquake, it can obtain accurate true three-dimensional point clouds of the ground including building elevation information. The combination of various kinds of data can promote the analysis of seismic building imaging mechanism and improve the extraction accuracy as they have respective advantages.In this paper, the main research content is building damage analysis and extraction from multi-source remote sensing data. Since building damage information has different performance in different data sources, summarizing its quantitative characteristics is effective in building damage information extraction; optical data and LiDAR data with full content and high visualization can help SAR image interpretation for better understanding and quantitative analysis of buildings; multi-source data has enriched object-oriented extraction method from multi-source data, and provides guarantee for rapid assessment after strike. The main research work is as follows:(1)Summarizing damage building features in optics, SAR and LiDAR data. Selecting Dujiangyan as the experimental zone, building sample library is established. Based on that, the characteristic parameters of different data sources are statisticed and compared, which is important for building damage extraction.(2)Joint analysis based on multi-source data:according to different imaging geometric models of buildings in SAR images, supplemented by optical data, vector data and photos, SAR images in sample library are analyzed. Point clouds of typical buildings are profiled to quantitatively analyze their deformation and their corresponding expression forms in SAR image.(3)Building damage object-oriented extraction is conducted with multi-source data:building information is extracted based on feature fusion of optical and LiDAR data; fast object-oriented building extraction is conducted for optical, SAR and LiDAR data respectively, then rapid assessment method which is superior to that with single data source can be got.