Developing low-cost automated tool for integrating maps with GNSS satellite positioning data

Abstract

Abstract Representing the Earth’s physical features onto a flat surface is a critical and challenging issue for geodesists to build topographic mappings at field scale in various applications. Artificial satellite positioning data are currently defined on a global geocentric frame, while terrestrial geodetic networks are determined on a local ellipsoid. Hence, coordinate transformations in three-dimensional space are required for data fusion involving different coordinate systems utilizing common points in two sets of coordinates. On the other hand, small companies in many developing countries have some data conversion difficulties due to the need for high-cost software and qualified persons. A low-cost automated tool is helpful in achieving this task and ensuring quality and positional accuracy. In this investigation, the problem was undertaken by establishing a software tool in the Microsoft Visual Studio environment for map-matching with global coordinates based on similarity transformations and a conformal polynomial approach. The tool’s performance was evaluated through a numerical example to assign transformation parameters and derive coordinates of checkpoints from the prediction surface.