In recent years, many papers have been published on the topics of the blockchain (BC) and blockchain technology (BCT). Some papers put BCT in the context of land registries (LRs), land cadastres (LCs), land registration, land administration (LA) and land management (LM) and its implementation benefits. Some eight years later, from its beginnings in 2014, the question of the future of the proposed concept and whether it has one, has been raised. The Scopus database was analysed using bibliometric analysis methodology and Rstudio software with the Bibliometrix R-package and the Shiny package environment. Based on this research, significant interest and growth in the topic was found in both technical and land-governance directions. Different approaches to the topic have been established in the global north and global south. From today’s perspective, the future of BCT in both worlds is guaranteed.

This paper explains the extent to which the importance of Marine Cadastre (MC) and Marine Spatial Data Infrastructure (MSDI) is recognized in the context of Marine Spatial Planning (MSP), Blue Economy (BE) and Blue Growth (BG), in the scientific community. A bibliometric assessment was performed using bibliometrics methodology. The research shows that MC and MSDI are underrepresented in the scientific literature. To the authors’ knowledge, theoretical, educational and capacity-building foundations are not developed enough in this domain. There are many practical issues in the marine and maritime domain that needed to be solved by the technical and engineering professions. They can be solved based on theoretical, scientific research and practical experience in different countries. The analysis of scientific papers was performed, together with different countries’ contributions, in the scientific database ISI Web of Science Core Collection (WoSCC). Another issue analysed is countries’ collaboration. The results show that there is almost no collaboration in the MC domain and some, but insufficient, in the MSDI domain. Based on analysing the recognition of the MC domain, as a basic layer of MSDI, the results are more satisfying than in other parts of the research.

Renewable energy is one of the main components of a sustainable world and its future. The consumption of electricity from renewable sources in Croatia has an impressive rate of 53.5%, but offshore wind turbines (OWT) have not yet been installed in the Adriatic Sea. The aim of this study is to determine the possibilities for offshore wind farm (OWF) positioning in the Croatian part of the Adriatic Sea using marine spatial planning (MSP). Initial research to determine the points of interest was conducted based on wind speed. The authors established ten possible points for further research. Subsequently, different parameters were used as inputs for exclusion. The Fuzzy Analytic Hierarchy Process (AHP) method was used to calculate the weighting coefficients for a suitable set of criteria, exactly six of them. Using a combination of geoinformation system (GIS) analysis and weighting coefficients established through Fuzzy AHP, four points were established as suitable for OWF installation in Croatia. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used to select the best order for OWF positioning in the eastern part of the Adriatic Sea. To conclude, there are not many options for OWF positioning in Croatia. Furthermore, it is clear that they exist and should be explored further.

More than two-thirds of the Earth’s surface is covered by oceans and yet only a small portion of these oceans has been directly explored in detail, highlighting the need for powerful tools like remote sensing (RS) technology to bridge this gap. International frameworks, the 2030 Agenda for Sustainable Development, and Ocean Decade point out the significance of marine areas for achieving sustainable growth. This study conducts a bibliometric analysis of RS over marine areas for sustainable development to identify key contributors, collaboration networks, and evolving research themes from the beginning of the 21st century until last year. Using the Web of Science Core Collection database, 499 relevant articles published between 2000 and 2023 were identified. The bibliometric analysis showed a significant increase in scientific productivity related to the field. On an international level, China emerges as the most productive country, but international collaboration has played a crucial role, with 36.87% of articles resulting from international co-authorship, pointing to the global nature of research in this field. RS technology has continuously evolved from airborne sensors to the augmentation of Earth Observation missions. Our findings reveal a shift towards automated analysis and processing of RS data using machine learning techniques to integrate large datasets and develop robust scientific solutions.

Stereoscopic visualization plays a significant role in the detailed and accurate interpretation of various geometric features on the surface of archaeological artifacts, which can be challenging to perceive using conventional two-dimensional visualizations. Moreover, virtual 3D models can be shared with other archaeologists for interpretation and the exchange of opinions. The hardware requirements for rendering stereoscopic 3D models are often readily available on desktop computers, or require only a minimal investment for implementation. This article focuses on creating stereoscopic visualizations of a stylized dove-shaped cult vessel for a virtual museum project. The term “visualization” is defined, emphasizing its significance and everyday applications. The camerawork techniques and processes involved in stereoscopic image production, including anaglyph imaging and polarization, are described. Blender (community-driven project under the GNU General Public License (GPL), Blender Foundation is a member of Open Invention Network, Khronos, Linux Foundation and the Academy Software Foundation) and StereoPhoto Maker (Muttyan, Japan) are reviewed as they relate to the production process of stereoscopic visualizations using open-source software. A series of static stereoscopic visualizations, along with two dynamic stereoscopic examples, are created, one using the anaglyph process, and the other using polarization. Lastly, the article discusses the contribution of stereoscopic visualizations to the interpretation of archaeological artifacts and suggests the optimal parameters for creating stereoscopic visualizations.

Procedural modeling offers significant advantages over traditional methods of geovisualizing 3D building models, particularly in its use of scripts or machine language for model description. This approach is highly suitable for computer processing and allows for the rapid rendering of entire building models and cities, especially when the buildings are not highly diverse, thus fully leveraging the strengths of procedural modeling. The first hypothesis is that buildings in the real world are mostly different and they should still be able to be displayed through procedural modeling procedures, and the second hypothesis is that this can be achieved in several ways. The first hypothesis suggests that real-world buildings, despite their diversity, can still be effectively represented through procedural modeling. The second hypothesis explores various methods to achieve this representation. The first approach involves recognizing the basic characteristics of a building from photographs and creating a model using machine learning. The second approach utilizes artificial intelligence (AI) to generate detailed building models based on comprehensive input data. A script is generated for each building, making reverse procedural modeling in combination with AI an intriguing field of study, which is explored in this research. To validate this method, we compare AI-generated building models with manually derived models created through traditional procedural modeling techniques. The research demonstrates that integrating AI and machine learning techniques with procedural modeling significantly improves the efficiency and accuracy of generating 3D building models. Specifically, the use of convolutional neural networks (CNNs) for image-to-geometry translation, and Generative Adversarial Networks (GANs) for texture generation, showed promising results in creating detailed and realistic 3D structures. This research is significant as it introduces a novel methodology that bridges the gap between traditional procedural modeling and modern AI-driven techniques. It offers a robust solution for automated 3D building modeling, potentially revolutionizing the fields of urban planning and architectural design by enabling more efficient and accurate digital representations of complex building geometries.