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The research applied ASPRS standards to determine the necessary number of check points to evaluate accuracy, with a proposed application of a simple method to identify outliers in elevation differences. Tests were conducted in the Latakia Governorate after dividing it into three areas: a moderate slope area, a moderate steep slope area, and a steep slope area. As for the check points, they were extracted from a topographic map with a scale of 1/25000.The results showed a strong positive correlation between reference elevations and elevations extracted from both the SRTM and ASTER models in all test areas, with a Pearson coefficient value of 0.99. It was also found that the vertical accuracy of the SRTM model is better than that of the ASTER model in the moderate slope area, where this accuracy reached 11.899m. In the case of the moderate steep slope area, the research found that the elevations extracted from the SRTM model are more accurate than those extracted from the ASTER model, with a vertical accuracy value of 21.609m for the SRTM model and 23.145m for the ASTER model. In the case of steep slope area, it was found that the elevations extracted from the ASTER model are more accurate than those extracted from the SRTM model, with a vertical accuracy of 36.770 meters for the ASTER model and 40.538 meters for the SRTM model.

Spectral indices developed to extract features from satellite images are simple and fast methods that reduce processing time compared to traditional satellite image classification.In this paper, the effectiveness of the normalized difference building index (NDBI), the normalized difference vegetation index (NDVI), and the Normalized Difference Water Index (NDWI) were evaluated in land cover mapping and detecting its changes in the period from 2013 to 2023 in Fayoum Governorate, Egypt, using Landsat 8-OLI images. The results of supervised classification showed a decrease in green areas between 2013 and 2023 by 76.03 square kilometers, with a slight decrease in the areas occupied by water amounting to 3.8 square kilometers and an increase in built-up areas by 79.83 square kilometers, at the expense of green lands. On the other hand, the results of using spectral indices showed a decrease in green areas between 2013 and 2023 by 91.12 square kilometers, with a slight decrease in the areas occupied by water amounting to 3.35 square kilometers. Meanwhile, we noticed an increase in built-up areas by 94.47 square kilometers at the expense of green areas. The results showed a general convergence in the changes in the studied classes during the study period, with a great convergence in the change in the area of the water bodies resulted from the classification and from the NDWI and a convergence in the effectiveness of both the NDVI and NDBI.

Drones are used by surveyors as an alternative to traditional methods of obtaining orthophoto maps and large-scale topographical maps, but several factors affect the accuracy of its data, one of them is software used in image processing. Because there are many types of software, choosing one of them is a real problem in survey projects using drones. Processing software is divided into commercial and open source software. Commercial software is a black box situation, which highlights the challenge of isolating accurate sources of errors and judging the accuracy of processing products.In this research, the capabilities of the commercial software Pix4Dmapper, Agisoft Metashape, and 3DF Zephyr Aerial were compared in calculating the aerial triangulation of the image blocks taken by drones, with a comparison of the capabilities of these softwares in getting the most important spatial products for surveyors from these images (Digital Elevation Model and Orthophoto). The results showed that Pix4Dmapper was able to perform aerial triangulation more accurate than Agisoft Metashape and 3DF Zephyr Aerial, with great convergence between the results of Agisoft Metashape and 3DF Zephyr A. The results also showed that 3DF Zephyr Aerial had extracted the densest point cloud. Another finding is that Pix4Dmapper produced the most accurate orthophoto and took the shortest processing time, and that the Agisoft Metashape interface is more flexible and user-friendly than the rest of the tested software.

Large horizontal displacements and tilts in tall structural elements such as towers and factory chimneys resulting from soil movement or earthquakes may lead to their collapse. The traditional methods of tilt monitoring require direct contact with the monitored buildings. Although the measurement results of sensors are accurate, sensors are typically cumbersome to deploy and can only provide local and relative deformation information Other monitoring methods do not require direct contact with the building, such as those using TLSs, GBInSAR, and photogrammetry; this last method had been used to obtain the geometric measurement of a 3D model, deformation data such as the displacement and inclination of buildings.In this study, close-range photogrammetry based on the principle of Structure from Movement technique (SfM Photogrammetry) had been used to monitor high structural elements because it considers safety and economical method where it isn't required direct contact with the monitored building, addition to low effort, short practical time and low budget; where the chimneys of the thermal station located at Tishreen University as a (case study). Results were then evaluated by comparing them with the traditional survey methods based on the use of the total station measurements. The results show that the value of the maximum displacement at the highest level, determined by using an uncalibrated mobile phone built-in camera and SfM photogrammetry (0.081 m) is approximately equal to twice the displacement and inclination determined by traditional surveying (0.049 m); but through some precautions and conditions, the accuracy of this method can be increased.