An extended maxima transform-based region growing algorithm for convective cell detection on satellite images

AbstractConvective cell detection is a critical step for tracking and forecasting of Mesoscale Convective Systems from geostationary satellite infrared (IR) data. Conventional threshold methods for identifying convective cell depend on the choice of threshold. Adjacent convective cells cannot be well distinguished because of the influence of anvil cloud. To address this problem, a new algorithm called extended maxima transform–based region growing (EMTRG) is proposed. First, EMTRG algorithm uses extended maxima transform to generate seed points of convective cell, and applies neighbourhood criterion to cluster adjacent seed points. Second, the merger and split times of pair-wise seed clusters are counted, and a merger criterion is utilized to decide whether pair-wise seed clusters should be merged. The algorithm is applied to various case studies over China. Experimental results on geostationary satellite IR images show that the proposed algorithm distinguishes adjacent convective cells region efficiently. AcknowledgementThe authors thank the National Satellite Meteorological Center (NSMC) of China for providing satellite images.