The construction of the St. Adalbert Church in Gdansk dates to 1310. It is a church of rich history and great historical value, and its care is challenging. In this study, the combination of unmanned aerial vehicle (UAV) photogrammetry and terrestrial laser scanning (TLS) was used to accurately build a 3D model of the church. Together with the collected historical inventory documentation, the historic building information model (HBIM) was generated. The Autodesk-Revit® tool was used for this purpose. On the basis of the generated model, the reflection properties of the laser scanner beam and red–green–blue (RGB) images, a methodology was proposed for analysing the degradation of the church’s components. The main hypothesis of this study is based on the analysis of sunlight outside the church. In addition to the importance of the method for determining the risks of church degradation, a high-quality method for model visualization combining two photogrammetric techniques (TLS + UAV) is presented.

The rapid development of scanning technology, especially mobile scanning, gives the possibility to collect spatial data coming from maritime measurement platforms and autonomous manned or unmanned vehicles. Presented solution is derived from the mobile scanning. However we should keep in mind that the specificity of laser scanning at sea and processing collected data should be in the form acceptable in Geographical Information Systems, especially typical for the maritime needs. At the same time we should be aware that data coming from maritime mobile scanning constitutes a new approach to the describing of maritime environment and brings a new perspective that is completely different than air and terrestrial scanning. Therefore, the authors, would like to present results of an experiment aimed at testing the possibilities of using mobile scanning at sea. Experiment was conducted in the harbour and the associated environment of neighbouring southern coast of the Baltic Sea.

In recent years, there has been an increasing use of satellite sensors to detect and track oil spills. The satellite bands, namely visible, short, medium infrared, and microwave radar bands, are used for this purpose. The use of satellite images is extremely valuable for oil spill analysis. With satellite images, we can identify the source of leakage and assess the extent of potential damage. However, it is not yet clear how to approach a specific leakage case methodologically. The aim of this study is the remote sensing analysis of environmental changes with the development of oil spill detection processing methods. Innovative elements of the work, in addition to methodological proposals, include the long-term analysis of surface water changes. This is very important because oil is very likely to enter the soil when water levels change. The classification result was satisfactory and accurate by 85%. The study was carried out using images from Landsat 5, Landsat 7, Landsat 8, Sentinel-1, and Sentinel-2 satellites. The results of the classification of the oil stains in active and passive technologies differ. This difference affects the methodology for selecting processing methods in similar fields. In the case of this article, the oil spill that occurred on 29 May 2020 in Norilsk was investigated and compared with data from other years to determine the extent of biodegradation. Due to the tank failure that occurred at the Nornickel power plant on that day, a large amount of crude oil leaked into the environment, contaminating the waters and soil of local areas. Research shows that oil spills may be caused by human error or may be the effect of climate change, particularly global warming.

One of the major tasks in environmental protection is monitoring the coast for negative impacts due to climate change and anthropopressure. Remote sensing techniques are often used in studies of impact assessment. Topographic and bathymetric procedures are treated as separate measurement methods, while methods that combine coastal zone analysis with underwater impacts are rarely used in geotechnical analyses. This study presents an assessment of the bathymetry airborne system used for coastal monitoring, taking into account environmental conditions and providing a comparison with other monitoring methods. The tests were carried out on a section of the Baltic Sea where, despite successful monitoring, coastal degradation continues. This technology is able to determine the threat of coastal cliff erosion (based on the geotechnical analyses). Shallow depths have been reported to be a challenge for bathymetric Light Detection and Ranging (LiDAR), due to the difficulty in separating surface, water column and bottom reflections from each other. This challenge was overcome by describing the classification method used which was the CANUPO classification method as the most suitable for the point cloud processing. This study presents an innovative approach to identifying natural hazards, by combining analyses of coastal features with underwater factors. The main goal of this manuscript is to assess the suitability of using bathymetry scanning in the Baltic Sea to determine the factors causing coastal erosion. Furthermore, a geotechnical analysis was conducted, taking into account geometrical ground change underwater. This is the first study which uses a coastal monitoring approach, combining geotechnical computations with remote sensing data. This interdisciplinary scientific research can increase the awareness of the environmental processes.

Nowadays, maritime infrastructure is heavily exploited, which requires monitoring. The article presents the implementation of spatial information which are point clouds for monitoring and analysis of the area around the port (buildings and wharves). For this study, point clouds coming from terrestrial (TLS) and airborne laser scanning (ALS), each of them having different accuracy, were used. An important part of the analysis was the integration of the two data sources. Through integration, the acquisition of information on areas not covered by the measurement in the presented case, one of the methods was possible for use (e.g. the roofs in case of TLS, or the lack of some of the walls of buildings in case of ALS). Another aspect was to use this data. Measurement of the shape and geometry of objects was executed. Additionally, the planeness analysis of individual elements of port infrastructure has been carried out. An interesting analysis was to determine the water level, based on relation to specific characteristics of the light reflectance.