In the paper,a set of algorithms to construct synthetic aperture radar(SAR)matching suitable features are frstly proposed based on the evolutionary synthesis strategy.During the process,on the one hand,the indexes of primary matching suitable features(PMSFs)are designed based on the characteristics of image texture,SAR imaging and SAR matching algorithm,which is a process involving expertise;on the other hand,by designing a synthesized operation expression tree based on PMSFs,a much more flexible expression form of synthesized features is built,which greatly expands the construction space.Then,the genetic algorithm-based optimized searching process is employed to search the synthesized matching suitable feature(SMSF)with the highest effciency,largely improving the optimized searching effciency.In addition,the experimental results of the airborne synthetic aperture radar ortho-images of C-band and P-band show that the SMSFs gained via the algorithms can reflect the matching suitability of SAR images accurately and the matching probabilities of selected matching suitable areas of ortho-images could reach 99±0.5%. 相似文献
Early warning systems represent an innovative and effective approach to mitigate the risk associated with natural hazards. Early warning technologies are now available for almost all natural hazards and systems are already in operation in all parts of the world. Nevertheless, recent disasters such as the Indian Ocean tsunami in 2004 and Katrina hurricane in 2005, highlighted inadequacies in early warning technologies.
Efforts towards the development of a global warning system are necessary for turning the tide in early warning processes and technologies. There is a pressing need for a globally comprehensive early warning system based on existing systems. The global system should be a mechanism which can consolidate scientific information and evidences, package this knowledge in a form usable to international and national decision makers and actively disseminate this information to those users.
The proposed Global Environmental Alert Service (GEAS) will provide information emanating from monitoring, Earth observing and early warning systems to users in a near-real-time mode and bridge the gap between the scientific community and policy makers. Characteristics and operational aspects of such a service, GEAS, are discussed. 相似文献