Heuristic search on statistics of wind data and cloud images for automatic typhoon eye location

Identifying typhoon eye location is quite a challenging task since several factors are needed to be evaluated. With deficient information from a single resource, it may lead to disappointed results. The wind information from satellite provides great ability in tropical cyclone intensity estimation, however, lacking in sufficient data to be analyzed in the blank swaths area due to its non-overlapped orbit. Moreover, it is sometimes noisy, incomplete and indirect. In addition to satellite information, the cloud image is an alternative choice. However, the uncertain cloud shape can result in undesirable excessive search time. In order to improve the detection efficiency, a novel heuristic search is proposed to automatically detect the typhoon eye location using the statistics of wind parameters from QuikSCAT satellite and spiral cloud images. The heuristic search is employed to find the best candidate eye location in the region of interest (ROI) obtained from QuikSCAT wind information. This offers great ability to restrain searching range of spiral cloud detection. The candidate eye location is further expanded in order to search for the best eye location using the SCM. The proposed technique can achieve approximately 64.4 % decrease in distance error compared to the three references. This can demonstrate significant enhancement in detecting the location of the typhoon eye.