Grid-on-Grid Transformation for Integrating Spatial Reference System of Multi-source Data

Abstract

AbstractThe accessible, up-to-date, reliable, and usable data are considered sustainability tools for developing spatial data infrastructure. Geospatial data come from multi-sources and are georeferenced using an appropriate mapping reference system. Artificial satellite positioning data are now defined on a global geocentric frame, whereas traditional geodetic networks were built on a national datum. Hence, three-dimensional (3D) coordinate transformations are required for data harmonization using control points that can be caused some discrepancies between the physical reality and represented positions. In practice, grid-on-grid conversion is a mathematical model matching GNSS observations and official spatial data through two common datasets to minimize the datum-to-datum transformation errors. This research conducts a comparative analytical study of the conformal polynomial algorithms for map-matching with global coordinates utilizing least-squares estimation. The findings indicated that the proposed approach provides superior performance and employs any area with high accuracy.