Paper
21 July 2024 Spatial and temporal distribution and prevention modelling of spotted lanternfly
Hanren Zheng, Yilin Jiang, Zuocan Ying
Author Affiliations +
Proceedings Volume 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024); 132191F (2024) https://doi.org/10.1117/12.3035089
Event: 4th International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2024), 2024, Kaifeng, China
Abstract
The Spotted Lanternfly(SLF) originates from Asia and spread to the United States about a decade ago, where it has since proliferated and inflicted significant damage on a variety of agricultural industries. Therefore, investigating the transmission behavior of SLF and devising strategies to suppress its spread is a worthwhile topic to study. In this study, we selected SLF monitoring data from four vineyards in New York State in 2022, established a population life model based on the life history and annual population dynamics of SLF, and combined it with the natural environment of New York State, autonomous dispersal behavior of SLF, reproductive behavior, human intervention, and other factors to construct a multi-level state transition network aimed at simulating the spatial-temporal distribution of the pest in New York State. In addition, we designed a cost-allocation strategy based on a greedy algorithm and a simulated annealing algorithm to evaluate the effectiveness of the three interventions and to predict the population of SLF in these four vineyards for the next five years after the intervention. The final results showed that the strategy was effective in suppressing the spread and growth of SLF in the vineyards with sustained impacts.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hanren Zheng, Yilin Jiang, and Zuocan Ying "Spatial and temporal distribution and prevention modelling of spotted lanternfly", Proc. SPIE 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024), 132191F (21 July 2024); https://doi.org/10.1117/12.3035089
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KEYWORDS
Vegetation

Transportation

Data modeling

Algorithms

Modeling

Agriculture

Computer simulations

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