Trees along tracks that are unstable or at risk of losing branches can fall on railroad installations during storms. Damage caused by toppled trees often disrupts operations. Teams of inspectors survey rail lines through wooded areas and check for potential risk. It takes a lot of time and effort to inspect large areas, however.
LiveEO has developed an earth observation solution for large areas. It uses machine learning to evaluate satellite images and identify vegetation near tracks.
The data are used to prepare a vegetation map that helps inspection teams plan and prioritize resources. The solution collects information about existing trees and distance from the track, which makes it possible to identify high-risk trees that could potentially disrupt the rail network during a storm.
The Berlin earth observation startup was established in 2017. Its team includes aerospace engineers, geographic information scientists and industrial engineers. LiveEO participated in the DB mindbox accelerator program in 2018.