This article mainly discusses the application methods and allocation plans of two typesofdrones dealing with wildfires in specific situations. We established a model to coordinateforest
fire supporting drones based on computer simulations. In State Victoria, we have collectedandprocessed the relevant data of forest fires with digital image processing technology. We selectedthe most representative area and used the Alpha Shapes algorithm to estimate the boundariesofthe state's forest fire-prone areas. The obtained area can be used to determine a unit range, thenwe used computers to make fire simulations within this range. The model uses securityasanindicator, and through multiple simulations, it provided an estimated value of the number ofdrones needed to ensure a high communication timeliness with the least quantity. Meanwhile, thedrone shifting model is introduced to ensure a smoother transmission: additional Drones will beused when the initial drone returns to the headquarters for charging. The influence of extremeterrain on the signal transmission between Drones is also considered, and a correspondingalgorithm is designed to optimize the Drones ’ positions. By analyzing the historical dataofwildfires in Australia, we divided forest fires into three different levels and calculatedthefrequency of each levels as their weights. Then our model can provide the appropriate quantityofthe drones we need to buy. We prepared a budget request for the CFA based on the model above. Simulation experiments have proved that this model has a strong rob