Vertical Accuracy of Digital Elevation Models Based on Differential Global Positioning System

  • Aqeel A. Abdulhassan Department of Civil Engineering, College of Engineering, Wasit University, Wasit, Iraq
  • Ahmed A. Naji Department of Civil Engineering, College of Engineering, Wasit University, Wasit, Iraq
  • Haqi H. Abbood Department of Civil Engineering, College of Engineering, Wasit University, Wasit, Iraq
Keywords: Terrain analysis, Digital elevation model, Open source, Accuracy assessment, Vertical Accuracy, Data pre-processing

Abstract

The Digital Elevation Model (DEM) has been known as a quantitative description of the surface of the Earth, which provides essential information about the terrain. DEMs are significant information sources for a number of practical applications that need surface elevation data. The open-source DEM datasets, such as the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and the Advanced Land Observing Satellite (ALOS) usually have approximately low accuracy and coarser resolution. The errors in many datasets of DEMs have already been generally examined for their importance, where their quality could be affected within different aspects, including the types of sensors, algorithms, terrain types, and other features. Ground control points (GCPs) used in this study were observed through the utilization of differential global positioning system (DGPS) with dual frequencies. Statistical indices were used to compare, evaluate, and validate the DEMs data against DGPS data. Statistical analysis of DEMs pointed out that SRTM accuracy was higher, with Root Mean Square Error (RMSE) of ±6.276m as compared to the other DEMs. ASTER showed the biggest residual error with an RMSE of ±10.241m. Nevertheless, ALOS was noticeably improved by having an RMSE of ±6.988m.

Published
2021-05-08
How to Cite
Abdulhassan, A. A., Naji, A. A., & Abbood, H. H. (2021). Vertical Accuracy of Digital Elevation Models Based on Differential Global Positioning System. Iraqi Journal of Science, 91-99. https://doi.org/10.24996/ijs.2021.SI.2.10
Section
Remote Sensing