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

Ahmed A Naji,Haqi H Abbood,Aqeel A Abdulhassan

doi:10.24996/ijs.2021.si.2.10

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.

Highlights

The Digital Elevation Model (DEM) has been known as a quantitative description of the surface of the Earth, which provides essential information about the relief or terrain [1]
They can be classified into two groups: Digital Surface Models (DSMs), which display the surface of the Earth and contain all natural and man-made objects, and Digital Terrain Models (DTMs), where there are no types of objects like trees and buildings [3]
Weak or strong relationships among the ortho-metric (DGPS) and DEM heights could be identified by referring to the findings of the regression model. These findings indicate that the strongest and most suitable model was selected as the best technique for the digital elevation model

Summary

Introduction

The Digital Elevation Model (DEM) has been known as a quantitative description of the surface of the Earth, which provides essential information about the relief or terrain [1]. DEMs are significant information sources for a number of practical applications that need surface elevation data and they have been utilized as sources of elevation data in several geospatial applications and studies, including plant cover research, urban studies, tsunami assessments, geomorphology, glacier observations, topography, and archaeology [2]. They can be classified into two groups: Digital Surface Models (DSMs), which display the surface of the Earth and contain all natural and man-made objects, and Digital Terrain Models (DTMs), where there are no types of objects like trees and buildings [3]. DEMs can be seen in a format of raster data, that are arrays of square cells [7]

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Conclusion