Based on evolution characteristics of rainstorms, we propose an algorithm for extracting and tracking rainstorm events with long-term raster-formatted datasets. The first step is the rainstorm extraction in the temporal domain. We calculate the cumulative rainfall of each grid of a time series, and identify the rainstorm levels. The second step is the rainstorm connection in a spatial domain:connecting the adjacent spatial grids tagged by rainstorm in a rainstorm object, and transforming it from raster format to the vector one with temporal, spatial and thematic information. Then rainstorm is tracked in the spatiotemporal domain. The relationship between storm objects will be fined based on the intersection of spatial topologies at adjacent moments, and the rainstorm objects are extracted based on the relationship, and calculate rainstorm event information. We using GPM-IMAGE final products, station datasets and radar datasets to compare and verify the algorithm. Experimental results show that the algorithm can completely extract the dynamic development process of rainstorm.
YANG Guanghui, XUE Cunjin, LIU Jingyi, WU Qunyong, WU Chengbin
. Algorithm for Extracting and Tracking Rainstorm Events Based on Time Series Raster-Formatted Datasets[J]. Journal of Applied Sciences, 2019
, 37(4)
: 510
-518
.
DOI: 10.3969/j.issn.0255-8297.2019.04.008
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