3D maps are becoming more and more popular due not only to their accessibility and clarity of reception, but above all, they provide comprehensive spatial information. Three-dimensional cartographic studies meet the accuracy requirements set for traditional 2D stu-dies, and additionally, they naturally connect the place where the phenomenon occurs with its spatial location. Due to the scale of the objects and difficulties in obtaining comprehensive data using only one source, a frequent procedure is to integrate measurement, cartographic, photo-grammetric information and databases in order to generate a comprehensive study in the form of a 3D map. This paper presents the method of acquiring and processing, as well as, integrating data from TLS and UAVs. Clouds of points representing places and objects are the starting point for the implementation of 3D models of buildings and technical objects, as well as for the con-struction of the Digital Terrain Model. However, in order to supplement the spatial information about the object, the geodetic database of the record of the utilities network was integrated with the model. The procedure performed with the use of common georeferencing, based on the global coordinate system, allowed for the generation of a comprehensive basemap in a three-dimensional form.

Circular arcs are a graphical element present in the cadastral systems of many countries. Unfortunately, this type of record of the geometry of parcel borders is a problem described by the directives of Infrastructure for Spatial Information in Europe (INSPIRE) Data Specification on Cadastral Parcels. Because of the difficulties of using such geometric objects, the solution to this problem, as recommended by the European Commission, should be monitored. The target effect should be a cadastral data model based solely on linear segments. Solutions based on a classic approach of converting such data (like arcs), unfortunately, always involves changes of one of the most important attributes of a parcel—its area. The paper presents a proposal for solving this important problem using an algorithm, ensuring the preservation of the area of the parcels after converting the arcs into linear segments. Moreover, attention was paid to the technical aspects of the proposed changes.

This article explores the problem related to preparing the digital data used for 3D visualizations on big areas. Because of the frequent problem of having only a small amount of such data the authors introduce a technology allowing densification of the data that make up the Digital Terrain Model. This is where SURFER software finds its application. These methods are sufficient to generate images for landscape visualization.

Locating a point in relation to a systematic division of sheets remains a key issue in computational geometry and GIS practice, especially in the context of for archival cartographic resources. The Krakow Local System (ULK), widely used in the past for mapping the city of Krakow, is still found across numerous analog and digital datasets. This paper presents spatial indexing algorithms for ULK: an encoder (point → sheet code) and a decoder (sheet code → sheet extent) that mirror the cascaded subdivision from 1:2000 down to 1:1000 and 1:500. The procedures are concise and constant-time O(1), which allows them to be used “on the fly”—for example, automatic derivation of the sheet code from coordinates (XY) and immediate attachment of the corresponding archival rasters, as well as computing a sheet frame prior to loading based on a code embedded in the filename. In combination with ULK ↔ PL-2000/1992 transformations, the approach supports resource consolidation, quality assurance (QA), and integration with GIS repositories and web services. In AI/ML workflows, the sheet code serves as a spatial label, facilitating automated data labelling, training set construction, and multimodal search. Importantly, these are not just sketches or pseudocode: the algorithms are provided as ready-touse implementations (VB6) and can be ported directly to a variety of environments—from GIS and CAD (e.g., MicroStation VBA), through Python/R scripts (code translator), database functions (e.g., SQL/PLpgSQL), and even spreadsheets (Excel/LibreOffice: formulas, Power Query). This makes them a practical foundation for indexing and managing large collections of archival rasters within modern GIS/AI pipelines.

The systematic division into section sheets adopted in the International World Map is the standard in many countries. This division is used for most types of small-scale maps. Due to the scope of application, it is also often the basis for indexing orthophoto images and data from laser scanning. Data accummulated in central State resources cover entire countries. Their coverage includes more than information obtained and processed for the users’ needs in the source format. Increasingly often, data is transformed into formats that facilitate their application (e.g. setting up a GRID for a digital terrain model). The need for quick spatial identification is a determinant of the availability of resources stored in these databases. The dynamic development of Open Source software in the fields of GIS is another increasingly broad area of study, and the research focus of scientists from around the world. They see it not only as a ready-made tool for conducting spatial analyses, but also in terms of searching for algorithmic solutions to meet the needs resulting from the requirement to process ever larger amounts of this type of data. The present paper discusses the method for designating a map sheet identification number (index) in a selected scale, based on the longitude and latitude of the given point. An unquestionable advantage of the presented solution is the possibility of dividing map sheets into scales, which were missing in their basic description. It follows from the fact that this spatial indexing method is indispensable for large amounts of data.