Using Unmanned Aerial Vehicles (UAVs) combined with various sensors brings the benefits associated with fast, automatic, and contactless spatial data collection with high resolution and accuracy. The most frequent application is the possibility of effectively creating spatial models based on photogrammetric and lidar data. This review analyzes the current possibilities of UAVs. It provides an overview of the current state of the art and research on selected parameters regarding their history and development, classification, regulation, and application in surveying with creating spatial models. Classification and regulation are based on national sources. The importance and usability of this review are also carried out by analyzing the UAV application with selected photogrammetric and lidar sensors. The study explores and discusses results achieved by many authors in recent years, synthesizing essential facts. By analyzing the network of co-occurring High-Frequency Words, in addition, we visualized the importance of the primary keyword UAV in the context of other keywords in the literary sources processed.

Coastal areas are increasingly endangered by climate change and associated sea level rise, which could have serious consequences, such as shoreline erosion and coastal city submergence. The current study aims to conduct a historical trend analysis (HTA) and predict the shoreline changes of the Nile Delta coasts. The Digital Shoreline Analysis System (DSAS) software, with the GIS environment, is used for monitoring the shoreline changes using a number of statistical methods (SCE, NSM, EPR, WLR and LRR). Satellite images from 1974 to 2022 were collected and geometrically corrected using supervised classification to detect the shoreline change of the Nile Delta. The GIS was used for detecting and monitoring changes in the shoreline, as well as forecasting future changes in the shoreline for the next 10 and 20 years (2033–2043). The critical sections of the Nile Delta were identified, and a time series analysis of shoreline changes was conducted. For each section, linear equations were established to predict probable changes in the shoreline. Between 1974 and 2022, the shoreline of the Nile Delta moved inland in different directions due to coastal erosion, and predictions indicate that this erosion will continue until both 2033 and 2043, particularly affecting the Rosetta and Damietta sections. The erosion rate ranged between 30–60 and 10–25 m/year at Rosetta and Damietta, respectively, but at Manzala, it ranged between 8–15 m/year. Continued erosion of the Nile Delta shoreline could have severe consequences that could affect the inhabitants, economy, buildings, roads, railways, and ports. These areas need an integrated coastal management strategy which incorporates increasing consciousness, urban development, and the implementation of rules and adaptation plans. The results of the current study and forecasting the shoreline change could help in protecting such areas.

The case study focuses on evaluating the suitability of roof surfaces in terms of their solar potential based on their geometric parameters. The selected processing methodology detects segments of roof surfaces from the LiDAR base, supplemented with spatial information (orthophoto map, real estate cadastre (REC)—footprint, basic database for the geographic information system (ZBGIS)—classification of buildings—current use). The approach based on spatial analyses takes into account the limit conditions for determining the impact of solar radiation resulting from the roof area, slope, aspect, and hillshade. Considering to the available subsidy scheme for family houses in the conditions of the Slovak Republic, a narrower sample of 35 family houses was selected from the total number of typologically represented buildings (194). A 3D model of the building created by combining REC and LiDAR substrates shows the roof surface without overlap, while another 3D model made of LiDAR substrates alone represents the actual dimension of the roof surface. The results presented for each selected building show good agreement with each other, and their visualizations were obtained using two GIS environment approaches. In the area of family houses, up to 94% of the roof areas of buildings registered in the REC meet the conditions for the installation of a PV system with an output of 2.6/3.3 kW.

The identification of roof surfaces is characterized by a sequence of several processing steps. The boundary detection of different types of roof is realized from light detection and ranging (LiDAR) cloud points and can confirm the real boundary of the roof. In the process of processing LiDAR data, shortcomings have been found regarding the inappropriate classification of points (class 6 “buildings”) concerning the roofs (the points of the building facade were marked as outliers and reclassified). In cases of insufficient point density, there is a problem with not being able to capture either the roof boundary or small roof objects, along with the possible occurrence of gaps inside the roof areas. This study proposes a processing procedure in a geographic information system (GIS) environment that advocates the identification of roof surfaces based on the LiDAR point cloud. We created the contours of a roof surface boundary with a simplified regular shape. From 824 roofs in the studied area, six different types of roof were selected, which this study presents in detail. The expected result of the study is the generation of segments inside the roof boundary. The study also includes the visualization of the outcomes of the spatial analyses of the identified roof surfaces, which forms the basis for determining the potential of solar systems with respect to green roofs for the development of smart city buildings.

Weather-related disasters represent a major threat to the sustainable development of society. This study focuses directly on the assessment of the state of spatial information quality for the needs of hydrodynamic modeling. Based on the selected procedures and methods designed for the collection and processing of spatial information, the aim of this study was to assess their qualitative level of suitability for 3D flood event modeling in accordance with the Infrastructure for Spatial Information in the European Community (INSPIRE) Directive. In the evaluation process we entered geodetic measurements and the digital relief model 3.5 (DMR 3.5) available for the territory of the Slovak Republic. The result of this study is an assessment of the qualitative analysis on three levels: (i) main channel and surrounding topography data from geodetic measurements; (ii) digital relief model; and (iii) hydrodynamic/hydraulic modeling. The qualitative aspect of the input data shows the sensitivity of a given model to changes in the input data quality condition. The average spatial error in the determination of a point’s position was calculated as 0.017 m of all measured points along a watercourse and its slope foot and slope edge. Although the declared accuracy of DMR 3.5 is assumed to be ±2.50 m, in some of the sections in the selected area there were differences in elevation up to 4.79 m. For this reason, we needed a combination of DMR 3.5 and geodetic measurements to refine the input model for the process of hydrodynamic modeling. The quality of the hydrological data for the monitored N annual flow levels was of fourth-class reliability for the selected area.

Mining, especially surface mining, has a significant impact on the upper part of the soil cover, including fauna and flora. The article deals with the use of geodetic methods to observe the mining process and its possible impact on the environment. The created model can be used to design the recovery and reclamation of open-pit mines after their closure and mining termination. For the modeling of an open-pit mine, 2151 points from two stages of geodetic measurements were used. Graphical presentations of the geodetic measurements were compared with data from aerial photogrammetry. The measurement and processing results were used to visualize the spatial changes in the open-pit mine, which are necessary to take measures related to the recovery of the landscape affected by mining. Based on the calculation, 145.266 m³ were extracted during the period under exploration. When calculating the average excavated volume per working day, it was found that 188 m³ = 500 tons = 0.5 kilotons per day were extracted between the monitored periods. When comparing the original surface and the generated model of the open-pit mine, it was found that the entire top of the rock massif was permanently removed in the total volume of 3,421,000 m³. To capture the impact of mining on the surrounding environment, multispectral images of Landsat 7 and 8 during the observed period. Focused attention was divided into two factors, land surface temperature, and vegetation condition. The results from the temperature maps show that the open-pit mine is becoming a heat island. Analysis of the vegetative state confirms the rapid change in the health of vegetation, resp. reduction of its condition in the area around the open-pit mine. The presented results show that the selected methods and procedures are applicable in the conditions of the small mining company in Slovakia.