In the recent years three-dimensional buildings modelling based on an raw air- borne laser scanning point clouds, became an important issue. A significant step towards 3D modelling is buildings segmentation in laser scanning data. For this purpose an algorithm, based on the multi-resolution analysis in wavelet domain, is proposed in the paper. The proposed method concentrates only on buildings, which have to be segmented. All other objects and terrain surface have to be removed. The algorithm works on gridded data. The wavelet-based segmentation proceeds in the following main steps: wavelet decomposition up to appropriately chosen level, thresholding on the chosen and adjacent levels, removal of all coefficients in the so-called influence pyramid and wavelet reconstruction. If buildings on several scaling spaces have to be segmented, the procedure should be applied iteratively. The wavelet approach makes the procedure very fast. However, the limitation of the proposed procedure is its scale-based distinction between objects to be segmented and the rest.

The research investigates the possibility of applying Sentinel-2, PlanetScope satellite imageries, and LiDAR data for automation of land cover mapping and 3D vegetation characteristics in post-agricultural areas, mainly in the aspect of detection and monitoring of the secondary forest succession. The study was performed for the tested area in the Biskupice district (South of Poland), as an example of an uncontrolled forest succession process occurring on post-agricultural lands. The areas of interest were parcels where agricultural use has been abandoned and forest succession has progressed. This paper indicates the possibility of automating the process of monitoring wooded and shrubby areas developing in post-agricultural areas with the help of modern geodata and geoinformation methods. It was verified whether the processing of Sentinel-2, PlanetScope imageries allows for reliable land cover classification as an identification forest succession area. The airborne laser scanning (ALS) data were used for deriving detailed information about the forest succession process. Using the ALS point clouds vegetation parameters i.e., height and canopy cover were determined and presented as raster maps, histograms, or profiles. In the presented study Sentinel-2, PlanetScope imageries, and ALS data processing showed a significant differentiation of the spatial structure of vegetation. These differences are visible in the surface size (2D) and the vertical vegetation structure (3D).

The integration of geodetic and photogrammetric data has become a new tool that has expanded the existing measurement capabilities, as well as it found its application outside the geodetic sector. As a result, over the past decades, the process of topographic data acquisition has caused cartographic industry to move from classical surveying methods to passive and active detection methods. The introduction of remote sensing technology has not only improved the speed of data acquisition but has also provided elevation data for areas that are difficult to access and survey. The aim of the work is to analyse consistency of elevation data from the Georeference Database of Topographic Objects (Pol. Baza danych obiektów topograficznych – BDOT500) with data from airborne laser scanning (ALS) for selected 15 research areas located in the City of Kraków. The main findings reveal discrepancies between elevation data sources, potentially affecting the accuracy of various applications, such as flood risk assessment, urban planning, and environmental management. The research gap identified in the study might stem from the lack of comprehensive investigations into the consistency and accuracy of elevation data across different databases and technologies in urban areas. This gap highlights the need for a thorough examination of the reliability of various data sources and methods of urban planning, disaster management, and environmental analysis. The integration of diverse databases and technologies, like ALS and geodetic measurements, in various applications introduces potential discrepancies that can significantly impact decision-making and outcomes.