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2 Artificial Satellites : Journal of Planetary Geodesy

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A Proposed Merging Methods of Digital Elevation Model Based on Artificial Neural Network and Interpolation Techniques for Improved Accuracy

Alemam Mustafa K., Yong Bin, Sani-Mohammed Abubakar

Artificial Satellites : Journal of Planetary Geodesy

2023

Vol. 58, No. 3

122--170

The digital elevation model (DEM) is one of the most critical sources of terrain elevations, which are essential in various geoscience applications. Most of these applications need precise elevations, which are available at a high cost. Thus, sources like the Shuttle Radar Topography Mission (SRTM) DEM are frequently accessible to all users but with low accuracy. Consequently, many studies have tried to improve the accuracy of DEMs acquired from these free sources. Importantly, using the SRTM DEM is not recommended for an area that partly contains high-accuracy data. Thus, there is a need for a merging technique to produce a merged DEM of the whole area with improved accuracy. In recent years, advancements in geographic information systems (GIS) have improved data analysis by providing tools for applying merging techniques (like the minimum, maximum, last, first, mean, and blend (conventional methods)) to improve DEMs. In this article, DEM merging methods based on artificial neural network (ANN) and interpolation techniques are proposed. The methods are compared with other existing methods in commercial GIS software. The kriging, inverse distance weighted (IDW), and spline interpolation methods were considered for this investigation. The essential step for achieving the merging stage is the correction surface generation, which is used for modifying the SRTM DEM. Moreover, two cases were taken into consideration, i.e., the zeros border and the H border. The findings show that the proposed DEM merging methods (PDMMs) improved the accuracy of the SRTM DEM more than the conventional methods (CDMMs). The findings further show that the PDMMs of the H border achieved higher accuracy than the PDMMs of the zeros border, while kriging outperformed the other interpolation methods in both cases. The ANN outperformed all methods with the highest accuracy. Its improvements in the zeros and H border respectively reached 22.38% and 75.73% in elevation, 34.67% and 54.83% in the slope, and 40.28% and 52.22% in the aspect. Therefore, this approach would be cost-effective, especially in critical engineering projects.

Integration of artificial neural network and the optimal GNSS satellites’ configuration for improving GNSS positioning techniques (a case study in Egypt)

Alemam Mustafa K., Yong Bin, Mohammed Abubakar S.

Artificial Satellites : Journal of Planetary Geodesy

2022

Vol. 57, No. 1

18--46

Nowadays, the global navigation satellite system (GNSS) positioning techniques based on the International GNSS Service (IGS) products are extensively used for various precise applications. However, specific conditions such as the dual-frequency observations and the final IGS products are required. Consequently, the absence of the final IGS data and using single-frequency observations will degrade these techniques' accuracy. In this paper, two algorithms through two separated stages are formulated for improving the single-frequency GNSS observations by using one GNSS receiver based on the broadcast ephemerides in real time or close to real time. The first algorithm represents the preparation stage for the second one. It classifies the observations by separating the optimal values of position dilution of precision (PDOP) and the number of satellites (NOS), as well as the corresponding values of coordinates. The second stage includes an algorithm based on the artificial neural network (ANN) approach, which is set at the ANN variables that produce the best precision through the applied tests at the present study. Binary numbers, log sigmoid-Purelin, cascade forward net, and one hidden layer with a size of 10 neurons are the optimal variables of ANN inputs format, transfer functions constellations, feedforward net type, and the number of hidden layers (NHL) and its size, respectively. The simulation results show that the designed algorithms produce a significant improvement in the horizontal and vertical components. Lastly, an evaluation stage is performed in the case of dual-frequency observations by using broadcast ephemerides. The simulation outputs indicate that the precision at applying the proposed integration is completely enhanced compared with the outputs of IGS final data.