The study investigates the use of machine learning in remote sensing to identify and map linear features such as roads, pipelines, and utilities in civil engineering. Remote sensing involves using sensors to gather data about the Earth's surface and atmosphere from a distance. Machine learning is a powerful tool that can be used to analyze and interpret this data to extract meaningful insights and make predictions. The availability of large amounts of data from remote sensing technologies has greatly increased in recent years. It has become increasingly more work to analyze and interpret this data manually. Machine learning solves this problem by automating the analysis and interpretation of remote sensing data.