Data scientist Asset.Insight.
Using 3D mobile laser scanner systems for improving the railway asset management
Acquiring accurate geospatial data about railway environment is of vital importance for railway asset management. Mobile laserscanning (MLS), is a promising technology for rapid 3D mapping of the railway in details along the corridors including tracks, clearance profile, natural obstructions (e.g., trees), and tunnel/bridge clearances.
In this presentation, we show our automatic methods to detect objects in railway environment using a mobile laser scanner system.
Anahita Khosravipour was born in Tehran, Iran. She studied Geography and Remote sensing in her B.Sc and M.Sc and worked as GIS and remote sensing specialist for 5 years in Iran. In 2011, she pursued her doctoral research at the Faculty of Geo-information Science and Earth Observation (ITC), University of Twente in Enschede, The Netherlands. Her research focused on improving the detection of individual trees from laser scanner systems. After graduation, she started her career as a data scientist at Asset.Insight. Her focus lies on developing new algorithms for extracting objects from 3D laser data sets.
Anahita received two awards In America for her outstanding work.