Nowadays, surveys using unmanned aerial vehicles are becoming popular. The resulting orthophotomap is the final product for creating digital plans and cardboard. The objectives of the study are to study the possibilities of obtaining orthophotomaps from survey materials using unmanned aerial vehicles based on the results of the experiment. The article describes various types of aerial photography. Some types of unmanned flying vehicles to conduct aerial photography for the purpose of monitoring, engineering surveys, inventory of agricultural land, and crop forecasts are considered. A description of aerial photography surveying is given on the example of the city of Dzerzhinsk, Minsk Region, which is performed taking into account the unmanned flying vehicles of GeoScan 201 and the Republican agricultural aero-geodesic unitary enterprise BelPSHAGI. A description of the GeoScan Planner software and basic pre-flight preparation is given. The stages of the preparatory work before the aerial photography, the creation of the planning and high-altitude geodetic justification, the implementation of aerial photography procedures, the steps of the aerial photograph anchorage procedure are considered. Agisoft Photoscan, which allows to get clouds of points, surfaces, 3D models and orthophotomaps using digital raster images are presented. The map of heights (DEM) of the terrain and the orthophotomap was made on the basis of a dense points cloud. According to the results of the research, a conclusion was made on the possibility of using aerial photography materials obtained using unmanned flying vehicles to get orthophotomaps of the required accuracy.

With recent advances in aerial data acquisition technologies from aircraft and Unmanned Aerial Vehicles (UAVs) very large datasets can be collected rapidly, covering significant surfaces with centimetre-scale resolution, with the consequence possibility to analyse geological structures of coastal areas within those datasets digitally. The monitoring of erosion mechanisms in fact requires high standards of precision to appreciate their effects. With the availability of a regular coastal monitoring programme being carried out in a large territory, UAVs can replace many of the conventional flights, with considerable advantages in the cost of data acquisition and without any loss in the quality of topographic and aerial imagery data. Several works in literature have been focused on finding an effective and sustainable survey strategy to limit costs and work times. However, it is necessary to refine the photogrammetric mapping process to optimize its geometrical accuracy and ensure the multi-temporal and multi-scaling repeatability of final products. The aim of this work is to test the accuracy obtainable from various photogrammetric workflows concerning the 3D modelling of a coastline area that is subject to hydrogeological instability. To this purpose, a set of image data acquired with a UAV, equipped with a non-metric camera and a low-accuracy GNSS/INS receiver, was processed. To maintain and test the accuracy of the whole process, an adequate number of Ground Control Points (GCPs) was acquired by means of a high precision GNSS surveying.

In the study, creation of 3D surface relief model in Jelgava, for southern part of the Castle Island is depicted. Information about remote sensing, its historical development, as well as directions of remote sensing, development of photogrammetry and laser scanning is summarized and analysed. Principles of work and methods of photogrammetry and laser scanning are viewed. Information about creation of surface relief model from planning of unmanned aircraft, data capture and alignment to the end product – surface relief model are described. Application of evaluation of data obtained. The purpose of the study – to create 3D surface relief model in Jelgava, for the southern part of the Castle Island. Tasks of the study – to consider development and improvement of photogrammetry and its processes, as well as development of laser scanning and principles of its work; to research, analyse and describe technological processes of laser scanning; to create 3D surface relief model in Jelgava, for the southern part of the Castle Island; to perform comparison of surface models obtained and describe application of laser scanning. Preparation of surface relief model is time-consuming process, which includes flight planning and preparation of end-product. End-products obtained in data processing of laser scanning have very broad usage in many sectors related to geodesy and construction.

For photogrammetric works, a fundamental issue is the determination of camera internal orientation parameters (IOP). Without camera calibration, it is difficult to imagine a correct adjustment of the image network. Many industries use nonmetric cameras, ranging from automatics and robotics, to heritage inventories, and the increasingly popular social mapping phenomenon uses low-budget cameras. Many different calibration methods exist, but dedicated calibration fields are commonly replaced by fast in-plane calibration with regular patterns. The main goal of this research is to verify the thesis that calibrating cameras on a checkerboard gives worse results in determining IOP than on a laboratory test field which may translate into the resulting model. For the purpose of this study, a special field was constructed, allowing calibration of the instruments on the basis of the network solution by the bundle adjustment. Unlike classical 2D fields, the field is equipped with a cork background providing a good base for matching and automatically detecting measurement marks. Calibration results were compared with calibration performed on a checkerboard implemented in MATLAB Camera Calibration Toolbox. In order to determine IOP in MATLAB, images of the checkerboard must be taken in such a way, that the whole pattern fits into the frame, otherwise toolbox defines the incorrectly coordinate system, which has a bad impact on calibration results. Moreover, the determined parameters have several times larger standard deviations than those determined in the laboratory test field, which confirms the thesis.