A Study on the Prediction of Dandelion Seed Dispersal Based on Gaussian Probability Distribution

Abstract

The "Spread Prediction Model" presented in the study focuses on forecasting the dispersion of dandelion seeds across a landscape using a Gaussian Probability Distribution. Initially assuming dandelions start from a central point in a 1-hectare area divided into 10,000 units, the model employs a two-dimensional Gaussian function to simulate seed spread influenced by wind direction and strength. Factors such as germination rates, seed production per plant, and survival rates across different climates (temperate, tropical, arid) are integrated into growth cycle simulations. These simulations, conducted in stages from seed dispersal to plant growth, are validated through sensitivity analysis of key parameters. Finally, the model's results are visualized using heat maps to demonstrate seed spread patterns over time and under varying environmental conditions.