This study aims at conducting a literature review on GIS-based simulation for suitable onshore wind farm site selection. A total of 58 papers, which is published in 2010 to 2024 and from high-quality journals, were manually collected, investigated, and classified into the following categories: year of publication, keyword, journal index, application area, employed software, applied multi-criteria decision-making method, and proposed criteria. The top ten of the most used criteria were analysed in detail to indicate their importance order as well as value categories, potential value, restrictive value. Specifically, the criteria in the articles were the result of research conducted in different natural and economic climate zones in the world. Moreover, from these ten criteria, this study also determined combinations of criteria which simultaneously appeared the most in the collected papers. The set of criteria includes points of intersection and convergence of important characteristics of natural conditions and socio-economic infrastructure that significantly influence the decision on selecting the optimal location. The results showed that “distance from road network” was the most preferred criterion while “wind speed” was considered as the most important criterion. Furthermore, a combination of two criteria “wind speed” and “distance from road network” was the most used with a frequency of 50 (in total of 58 times). As the results, the research contributed a set of useful and necessary information for making decisions on suitable wind farm site selection which may help researchers, local government, investors easily determine and choose relevant influenced criteria and suitable methods.

This study explored the preliminary educational effects of a tsunami evacuation program using a streetscape reconstructed from a real district with a 3D laser scanner. The study area was Ono-machi, Kanazawa City, Japan, where 652 scan positions were captured using a Leica BLK360; the resulting point clouds were registered, cleaned, converted into a mesh model, and imported into Unity to build a desktop-based 3D evacuation experience. Twenty-five residents participated, operating the system individually or in small groups, discussing evacuation decisions, and completing pre- and post-experience questionnaires. Exploratory pre–post comparisons using the Wilcoxon signed-rank test were conducted for the 22 complete paired responses. Because five corresponding pairs were tested, the possibility of Type I error inflation due to multiple comparisons was considered. The results were interpreted using both uncorrected p-values and a Bonferroni-adjusted significance threshold of 0.01. The largest improvement was observed in the understanding of hazardous locations, with a mean increase of 1.59 points and a large effect size. The improvement in consideration of detours and alternative routes also remained below the adjusted threshold. Other corresponding item pairs showed positive descriptive changes and uncorrected p-values below 0.05, but they did not meet the Bonferroni-adjusted threshold. Therefore, these findings should be interpreted as preliminary evidence that a locally grounded, point-cloud-derived 3D urban model may support residents’ place-based understanding of local hazards and evacuation-related reflection. By supporting local risk communication, preparedness, and evacuation-related reflection, this approach may contribute to sustainable community-based disaster-prevention education and the development of more resilient coastal communities.