Individual treecrowns detection algorithm using remote sensing data

Major advances in technology have allowed programmers to modernize the way they manage data. Today, artificial intelligence is very focused on one of its sub-fields: data management. To function properly, AI systems require some form of data analysis and management. The data obtained from wooded places such as forests are the data taken into consideration in our research. We acquire and process data that includes photographs taken by high-flying aircraft. In this study, data were obtained from the Western Balkan mountain ranges in Bulgaria and different regions of the city of Baghdad. The database contains different pictures of seasonal or evergreen tree species such as citrus. High-density, short-range drones can be used to aid image acquisition. The quality of the images helps alleviate the problem of recognizing tree crowns to some extent. We build an intelligent model based on machine learning concept and analyze forest aerial images using various image processing techniques. It is possible to provide a comprehensive description of the image and identify the trees in it. In addition, the captured trees are classified and data is provided for each category. The categories are young trees and old trees. Excellent recognition and classification accuracy is achieved.