Improving the Accuracy of the SRTM Global DEM Using GPS data fusion and regression Model

Digital Elevation Models (DEMs) are commonly produced through different surveying approaches that varied in processing techniques, time, and cost. During the last decade, the Global DEMs of the Shuttle Radar Topography Mission (SRTM) with a horizontal resolution of 90 m is representing the freely available DEMs worldwide with relevant quality. The main objective of this research is to improve the accuracy of the DEM generated by SRTM using GPS data fusion and a developed regression model. Ground control points (GCP) were observed using GPS with centimetre-level accuracy. Herein, the GCP are divided into two main groups. The first group is the solution dataset that define the coefficients of the polynomial, while the behaviour of the polynomial has been investigated against the number of used common points and the average spacing between these points. The second group is a check dataset which is used to assess the accuracy of the new developed DEM using statistical methods. Moreover, the potential of using visual analysis technique has been proved by the evaluation of the validity of the visual techniques in doing such analysis. The final analysis results has shown that the applied polynomial of the first order using control points with average spacing 250 m has improved the SRTM DEM to be more close to the GPS DEM. Also, the statistical analysis has supported these results where the value of the root mean square error (RMSE) of the check points is ranging between ±0.42 m and ±1.21 m for flat terrain.