Improve The Detection of Tree Crowns on Drone Images by Machine Learning Algorithm

Abstract

Huge advances in technology have allowed developers to modernize the way they handle data. Data management is one of the most important areas of AI today. AI systems rely on creating a way to analyze and manage data. The data we consider in our research is data from areas with trees such as forests. We collect and process data containing images taken by aircraft from above. The reason for the increase in land pressure, splitting of tree crowns under the high canopy, and deep forest areas remain unresolved tasks. High-density shortrange unmanned aerial vehicles can help solve this problem to some extent. We develop a smart model based on machine learning in which image processing tools are used to analyze forest aerial images. A comprehensive description of the image can be provided and the trees in it can be identified. Captured trees are also classified and statistics are provided for each classification.