Hanli Liu

This paper presents several enhancements to the universal generation of realistic 3D urban scenes with detailed roof shapes, leveraging key data sources such as OpenStreetMap and Digital Terrain Models. The prior approach relied on core principles of 3D mesh generation, producing models compatible with various 3D rendering systems and game engines. In this study, cadastral data is employed to automatically determine the number of building levels, utilizing datasets from the Spanish Virtual Cadastral Office for this determination. The proposed reconstruction method successfully processes approximately 97% of OpenStreetMap building entities that include valid roof definitions. A polygon‐covering algorithm was implemented to generate volumetric models for buildings with complex footprints and representative roof shapes. In future work, the capacity of this algorithm and the quality of the terrain models can still be improved.

This work presents the mathematical definition and programming considerations of an efficient geometric algorithm used to add roofs to polyhedral 3D building models obtained from OpenStreetMap. The algorithm covers numerous roof shapes, including some well-defined shapes that lack an explicit reconstruction theory. These shapes include gabled, hipped, pyramidal, skillion, half-hipped, gambrel, and mansard. The input data for the developed code consist of latitude and longitude coordinates defining the target area. Geospatial data necessary for the algorithm are obtained through a request to the overpass-turbo service. The findings showcase outstanding performance for buildings with straightforward footprints, but they have limitations for the ones with intricate footprints. In future work, further refinement is necessary to solve the mentioned limitation.

This work presents a numerical mesh generation method for 3D urban scenes that could be easily converted into any 3D format, different from most implementations which are limited to specific environments in their applicability. The building models have shaped roofs and faces with static colors, combining the buildings with a ground grid. The building generation uses geographic positions and shape names, which can be extracted from OpenStreetMap. Additional steps, like a computer vision method, can be integrated into the generation optionally to improve the quality of the model, although this is highly time-consuming. Its function is to classify unknown roof shapes from satellite images with adequate resolution. The generation can also use custom geographic information. This aspect was tested using information created by procedural processes. The method was validated by results generated for many realistic scenarios with multiple building entities, comparing the results between using computer vision and not. The generated models were attempted to be rendered under Graphics Library Transmission Format and Unity Engine. In future work, a polygon-covering algorithm needs to be completed to process the building footprints more effectively, and a solution is required for the missing height values in OpenStreetMap.

In the realm of programming education, enhancing student commitment is pivotal for both academic success and practical application. Traditional methodologies often fall short in catering to the evolving needs of today’s learners. Addressing this gap, this paper introduces a web-based gamified tool designed to transform the pedagogical approach in programming courses. The study’s theoretical contribution lies in its exploration of gamification as a strategy to augment student commitment, bridging the divide between conventional teaching and contemporary learning needs. From a practical standpoint, empirical data encompassing performance metrics, dropout rates, and student feedback demonstrate the tool’s significant positive impact. Notably, students exhibited improved pass rates and reduced dropout tendencies, underscoring the tool’s practical efficacy. Furthermore, feedback highlighted the tool’s usability and the enhanced satisfaction derived from its engagement. Aligned with the existing literature, the findings advocate for the broader adoption of gamification in programming education. This research substantiates the potential of gamification as both a theoretical model and a practical strategy, enriching the discourse on modern programming education.