Photogrammetry with unmanned aerial vehicles (UAVs) has become a source of data with extensive applications. The accuracy is of utmost significance, yet the intention is also to find the best possible solutions for data acquisition in economic terms. The objective of the research was the analysis of various variants of the bundle block adjustment. The analysis concerns data which is diversified with respect to the type of shutter (rolling/global), the measurement of external orientation elements, the overlap and the number of ground control points (GCPs).

Letychiv (pl. Latyczów) is a town located in central Ukraine in the Khmelnytskyi Oblast. It has a unique and complicated history. Second World War left it in ruin, destroying buildings, infrastructure and decimating its once large population. Perhaps the most prominent part of the town currently is the building Dominican convent with adjoin Letychiv Assumption Church. This object is surrounded by what is left of the previously impressive Letychiv Castle, founded by Jan Potocki in 1598. Past 30 years have been dedicated by this small Catholic parish towards rebuilding monastery-castle-church complex. Since this is an ongoing project, it was decided to perform a photographic inventory of the current state of the construction and to create a 3D digital model of the castle, facade of the church and monastery, and the altar. This task have proven to be difficult due to complicated structure of the object. Facades and inner parts of the church are almost white with limited number of distinctive elements, painted in pail gold. Elements other than white are almost identical to each other. It leads to various errors in the processing of Structure-from-motion. This article describes how various versions of SfM algorithm work thru mention difficulties, compares results in terms of accuracy, level of detail and overall look. It also describes how SfM can help to document various stages of restoration of important historical objects.

Unmanned aerial vehicles (UAVs) are used to acquire measurement data for an increasing number of applications. Photogrammetric studies based on UAV data, thanks to the significant development of computer vision techniques, photogrammetry, and equipment miniaturization, allow sufficient accuracy for many engineering and non-engineering applications to be achieved. In addition to accuracy, development time and cost of data acquisition and processing are also important issues. The aim of this paper is to present potential limitations in the use of UAVs to acquire measurement data and to present measurement and processing techniques affecting the optimisation of work both in terms of accuracy and economy. Issues related to the type of drones used (multi-rotor, fixed-wing), type of shutter in the camera (rolling shutter, global shutter ), camera calibration method (pre-calibration, self-calibration), georeferencing method (direct, indirect), technique of measuring the external images orientation parameters (RTK, PPK, PPP), flight design methods and the type of software used were analysed.

Photogrammetric products obtained by processing data acquired with Unmanned Aerial Vehicles (UAVs) are used in many fields. Various structures are analysed, including roads. Many roads located in cities are characterised by heavy traffic. This makes it impossible to avoid the presence of cars in aerial photographs. However, they are not an integral part of the landscape, so their presence in the generated photogrammetric products is unnecessary. The occurrence of cars in the images may also lead to errors such as irregularities in digital elevation models (DEMs) in roadway areas and the blurring effect on orthophotomaps. The research aimed to improve the quality of photogrammetric products obtained with the Structure from Motion algorithm. To fulfil this objective, the Yolo v3 algorithm was used to automatically detect cars in the images. Neural network learning was performed using data from a different flight to ensure that the obtained detector could also be used in independent projects. The photogrammetric process was then carried out in two scenarios: with and without masks. The obtained results show that the automatic masking of cars in images is fast and allows for a significant increase in the quality of photogrammetric products such as DEMs and orthophotomaps.