EO Data Integration and Processing Based on Grid for Flood Monitoring

Earth Observation (EO) is an effective way to monitor hazards for rapid response. The sensors such as optical, passive microwave, Synthetic Aperture Radar (SAR) can be used. For rapid response purpose based on EO data, fast data acquisition from data provides and processing in near real-time are two key issues. In this paper, the automatic data integration method based on metadata harvest interface is introduced. Distributed computing resources are collaborated based on gird computing to process the RS data into flood map. And grid workflow technique is used to manage and monitor the flood detecting processes. Flood is used as use case. The monitoring results from multi-sensor data can be used as time-serial monitoring of the flood extent and detection results from different sensors can be cross-validated. SAR and MODIS data from distributed websites and flood detection algorithms base on these data are used for test. An integrated web portal test bed based on data integration service and flood detection algorithms is developed. The test bed can be used to request and automatic access distributed RS data source and process RS data on demand to get flood extent in near real time.