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汶川大地震灾情综合地理信息遥感监测与信息服务系统
引用本文:张继贤,刘正军,刘纪平.汶川大地震灾情综合地理信息遥感监测与信息服务系统[J].遥感学报,2008,12(6).
作者姓名:张继贤  刘正军  刘纪平
作者单位:中国测绘科学研究院,北京,100039
摘    要:结合此次汶川大地震灾情综合地理信息监测与评估工作,着重探讨航空航天遥感技术在地震灾情监测与评估中的方法和技术路线.通过集成多平台和多传感器数据.根据不同区域受灾严重程度不同的情况,研究制定了地震灾区灾情综合地理信息监测指标;通过综合震前震后多源数据,制定了快速几何处理、快速数据质量综合分析、快速变化提取、快速目标判读和次生滑坡灾害空间危险性评估的技术流程,实现了汶川大地震震区灾情综合地理信息的解译、制图和统计评估.在此基础上,开发了汶川地震灾情综合地理信息服务系统,实现了灾情监测信息的综合管理、可视化查询和统计分析.并对当前工作中存在的问题进行了探讨.

关 键 词:汶川大地震  遥感  监测与评估

Remote Sensing Monitoring of the Wenchuan Earthquake Disaster Situation and the Information Service System
ZHANG Ji-xian,LIU Zheng-jun and LIU Ji-ping.Remote Sensing Monitoring of the Wenchuan Earthquake Disaster Situation and the Information Service System[J].Journal of Remote Sensing,2008,12(6).
Authors:ZHANG Ji-xian  LIU Zheng-jun and LIU Ji-ping
Institution:Chinese Academy of Surveying and Mapping, Beijing 100039, China;Chinese Academy of Surveying and Mapping, Beijing 100039, China;Chinese Academy of Surveying and Mapping, Beijing 100039, China
Abstract:Earthquake is one ofmost serious natural disasters in theworld. Ithaswide geographic coverage, huge dam- age, and long tmi e influence for recovery. The earthquake happened inWenchuan onMay12, 2008 caused greatdamage in 42 counties in Sichuan province, 23 counties inGansu province, and 19 counties in Shaanxi province. In addition, it also hasmuch influence on Chongqing, Yunnan, Shanx,i Guizhou, andHubei provinces. Because of the severely destroyed in- frastructures, complicated topography and badweather condition after the earthquake, the disaster situation assessment from ground investigation is very difficult to undertake. In this situation, feasible approaches should be investigated. In this paper, we take the remote sensingmonitoring and assessment of theWenchuan Earthquake disaster situation as a case study and discuss the technical approaches and methods on application of space and airborne remote sensing technology for earthquake disaster situationmonitoring and assessment. Firstly, by integratingmulti-platformmulti-sensordata, we defined the earthquake disaster situationmonitoring inde- xes according to two differentdisasterseverity levels. Forareaswith high-leveldisaster loss, aerialphotos and high-resolu- tion satellite mi ageswith less than 1meter resolution are used as themajordata sources, where fourmajor categorieswith detailed subclasses are classified, .i e., 1) urban and rural residential areas; 2) urban and rural infrastructures such as industrial andmining lands, highways, railways, bridges, tunnels, electric facilities, telecommunication facilities, chan- nels, dikes, reservoirs, and dams; 3) geological and environmental change information such as earthquake lakes, rock slumps, landslides, and turbidities; and 4) destroyed farmlands such as croplands and forest lands. For areaswith low- level disaster loss, high andmedium resolution optical and SAR satellite mi ages before and after the earthquake are used as themajordata sources, where fourmajor categorieswith lessdetailed subclasses are classified, .i e., 1) urban and ru- ral residential areas; 2) urban and rural infrastructures such as industrial and mining lands, highways, railways, and large reservoirs; 3) geological and environmental change information such as earthquake lakes, rock slumps, landslides, and turbidities; and 4) destroyed farmlands such as croplands and forest lands. By combining themulti-tempora,l multi-source data before and after the earthquake, we establish the technical flows for quick geometric processing, quick data quality analysis and assessment, quick change detection, quick target interpre- tation, quick spatial risk assessment for landslides induced by earthquake, and the synthesis of thesemethods fordisaster monitoring. For geometric processing, the ImageInfo softwaremodulePixelGrid isused. For mi age fusion, the data fusion module of ImageInfo isused. For interpretation ofdifferentarea of mi ages, theArcGIS software isused. Additionally, the SINMAPmodule underArcGIS software is also used for the validation of the extracted geological risk areas. The approach has been successfully applied inmonitoring, mapping, and statistical assessmentof the earthquake disaster situation. In addition, we also develope an application system which could provide functionalities fordisaster informationman- agement, visualization, and statisticalanalysis. Itutilize 2DWebGIS user interface and 3D virtual smi ulation environment tomanage the disasterdatabase and visualize themonitored results as2D maps, statistic tables, graphs, and 3D models, and provide functionalities formeasure and analysis. Finally, we also addressed and discussed some practical problemswhen applying this approach that should be well justified in the future, including the development of new geometric correction algorithm without control points, and the standardization of theworkflow described in this paper forbetter accuracy.
Keywords:Wenchuan Earthquake  remote sensing  monitoring and assessment
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