Making Different Topographic Maps with the Surfer Software Package

Digital Elevation Models (DEMs) are an important data source used in many engineering and Geographic Information System (GIS) applications. This paper illustrates a strategy for creating a DEM by utilizing elevation data from Google Earth and evaluating the vertical positional accuracy of the generated DEM adopting a well-defined methodology. To ensure the accuracy of the elevation data obtained from Google Earth, a thorough evaluation was done in three diverse small districts of the northern shoreline in Egypt. The evaluation process involved determining the ground coordinates of reference points utilizing two surveying techniques: total station and Real-Time Kinematic (RTK) Global Positioning System (GPS) surveys. These coordinates were compared with the ones predicated by the DEM generated by putting into service Google Earth's elevation data. Furthermore, the vertical accuracy was assessed using Shuttle Radar Topographic Mission (SRTM) data of Google Earth collected at two different periods in 2015 and 2023. The vertical accuracy of the Google Earth data is detailed utilizing Mean Error (ME), Maximum Absolute Error (MAE), and Root Mean Square Error (RMSE). According to the results, Google Earth's elevation data accuracy remains consistent from 2015 to 2023, and refining SRTM data does not improve the vertical accuracy. The vertical accuracy of the total station survey surpasses the one of the RTK GPS survey, and the elevation accuracy of the RTK GPS survey decreases with increasing height difference. In addition, the vertical accuracy of DEMs was found to be sufficient for some engineering applications but not accurate enough for precise engineering studies. The accuracy achieved in small height difference terrain can be utilized to produce large-scale cadastral maps, city plans, or land use maps. Finally, the elevation data offered by Google Earth can be utilized for preliminary studies at a low cost. However, to ensure the accuracy of these data, it is recommended that users compare them with reference data before implementation.

Vertical Accuracy of Google Earth Data

El-Ashmawy

2024

Comparative Analysis of GDM2000, WGS84, and MRT68 Coordinate Reference Systems based on Different Converter Modules

Hussaini,

Tang Kang Wee,

Izzati Abdul Hamid

et al. 2024

The employment of multiple data and coordinate systems in Malaysia has not only resulted in challenges in surveying and mapping purposes but has also caused data compatibility issues with the local positioning system. This study examines the disparities in coordinates converted from the localized Geocentric Datum of Malaysia 2000 (GDM2000) to the global coordinate system, the World Geodetic System 1984 (WGS84), and from GDM2000 to the Malayan Revised Triangulation 1968 (MRT68). Several coordinate converter tools, available in the mCOORD mobile app, Geodetic Datum Transformation System (GDTS), Global Mapper, and Quantum GIS (QGIS), were employed to analyze the variation between converted coordinates. The locally developed coordinate converter tools, mCOORD and GDTS, exhibit similar levels of accuracy and conform to the standards set by the local survey department. In contrast, the reliability of the coordinate conversion tools in Global Mapper and QGIS seems uncertain. It is recommended that each data revision should establish transparency to the latest geodetic reference frame, with publicly accessible transformation parameters.

Block-based Watermarking for Robust Authentication and Integration of GIS Data

Tareef,

Al-Tarawneh,

Sleit

2024

A Geographic Information System (GIS) is a computer system for gathering, storing, transmitting, and presenting data related to positions on Earth’s surface. This research aims to authenticate the GIS data during transmission via internet based on transform-based invisible watermarking. The proposed framework uses the singular value decomposition and discrete cosine transformation in the frequency domain. The proposed framework is evaluated on National DEM images obtained from the Geospatial Information Agency's (Badan Informasi Geospatial—BIG) geoportal, under several types of attacks. Two performance metrics (Peak to Signal Noise Ratio (PSNR) and Mean Square Error (MSE)) were considered for the evaluation of the security of the designed framework. Likewise, Normalized Correlation (NC) was computed to assess the robustness by calculating the similarity between the original and the extracted images. The experimental outcomes show that the extracted logos are readable even if altered, which guarantees that the received DEM data are authentic.