Spatiotemporal distribution analysis of Vespa Mandarinia based on GM model

Abstract

As a natural enemy of the European honeybee, the Chinese great steller’s wasp can have a serious impact on local bee populations, so they are considered an agricultural pest. After the emergence of these pests, countries must decide how to prioritize their limited resources for follow-up investigations. In this paper, a model was established to predict the emergence of wild silkworm, which could be used to provide strong support for pest management. when predicting how pests spread over time, we built a GM model to predict the spread of Vespa mandarinia from the spatial and temporal distribution. When predicting the geographic location of Vespa mandarinia, we set up a two-dimensional GM model using longitude and latitude as two variables to predict the longitude and latitude of the next Vespa mandarinia. At the same time, when predicting the occurrence time of Vespa mandarinia, we formed a sequence of the annual 12-month report times of previous years, and still used GM model for data processing and prediction.