Quality Control Framework of Big Data for Early Warning of Agricultural Meteorological Disasters

Agricultural meteorological disasters, including floods, droughts, dry hot winds, low temperature chills, typhoons, hail and continuous rain, can lead to significant reduction in agricultural output. Big data platform for early warning of agricultural meteorological disaster is the basis of business operation system for early warning of agricultural meteorological disasters, and the data quality is an important guarantee for success of the early warning. Quality control of big data for early warning of agricultural meteorological disaster involves names of data sets, metadata, data documents and content of data sets. The quality control for contents of data sets is divided into quality control of attribute data and that of spatial data, and quality control of spatial data is divided into quality control of vector data and that of raster data. Methods for data quality control are divided into fully automatic, semi-automatic and full manual control methods.