Infoscience

Student project

Accuracy Prediction in Aerial Mapping

Low cost and low weight unmanned aerial vehicle (UAV) systems with imaging capability have enjoyed a rapid development over the past years and are increasingly deployed as carriers for mapping purposes. They present a well-established tool for local-area remote sensing in the fields of agriculture, forestry, mining and hydrology as well as in scientific research. An important part of MAV mapping system is the ground station with a mission planner which serves for flight scheduling and mission execution. The traditional mission planners for MAVs are not dedicated to precise photogrammetry in complicated terrain. They allow planning and executing of autonomous flight as well as setting up of the autopilot systems. However, they lack functions for advanced flight planning, such as those motivated by achieving certain precision and reliability of the determined coordinates of features within the mapped area. The goal of this work is to create a software tool that given a planned trajectory (i.e. planned position and orientation of camera exposure), preliminary digital elevation model (DEM), assumptions on surface texture (i.e. number, distribution and accuracy of image observations) and (optionally) a certain number and distribution of ground control points (GCPs), allow to quantify the quality of the mapping.

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