Global environmental problems include environmental pollution and the destruction of ecological balance that transcend national boundaries. With the continuous development of human life, economy, trade, and technology, the intrusion into the environment has continued to deepen, causing extensive destruction of forests and other vegetation, large-scale killing of organisms, environmental pollution, and invasion of alien organisms. This has led to a sharp decline in biodiversity and a serious imbalance in the ecological environment. At the same time, the continuous improvement of information technology capabilities and the introduction of big data management and related detection models have brought new methods to the detection and governance of the global ecological environment. Based on the data related to the spread of Asian Hornet in the United States, this paper proposes a method and model for monitoring the number and distribution of new species based on the SAR model. Based on the spatial relationship and the distribution data of the Asian Hornet in the United States from May 2020 to October 2020, and taking into account environmental and climatic factors such as temperature, humidity, and air pressure, this paper conducts time series predictions to obtain the extent of the spread of the Hornet in the United States. The average RSME is 91.27, and a relatively ideal prediction result has been obtained, which proves that this model and method have a good effect on the control and management of alien species and the maintenance of ecological diversity.