## 4 Discussions and Limitations  
During the analysis performed, using the graphs generated and the information extracted over the period 2002-2023, an increased interest in the applicability of artificial intelligence to local or regional studies was observed, registering a high annual growth rate of 22.67%. Starting with a single article published in the field in 2002, the number of publications increased considerably, reaching a high number of 73 articles in 2023. In terms of the most relevant journals, four of them stood out, with a higher number of published articles, totaling 46 articles out of a total of 237 (_Remote Sensing_, _Sustainability_, _PLOS ONE_ and _Mathematical Problems in Engineering_). These publications are among the best known, with the main aim of promoting science at a global level through research on various topics of interest. In our analysis, China was observed as the country with the highest number of published articles, registering 215 publications in the field of using AI in local or regional studies, which represents 30.32% of the total scientific output by country, followed by the United States of America with 64, i.e., 9.03%. According to a bibliometric analysis carried out by [PERSON] et al. (2017) over the period 2009-2018, whose objective was to realize a bibliometric profile of the journal _Remote Sensing_, which we also observed in our analysis as the most favorite journal for authors to publish their creations, the two countries (China and the United States of America) represent the countries that contributed most frequently with publications, but also where a constant cooperation could be observed. Even though the highest number of articles came from China, in terms of the number of citations, this was observed in Vietnam, registering 614 citations, which represents 15.02% of the total number of citations by country. China is right behind with 595 citations, which is 14.55% of the total number of citations by country. As expected, according to the number of citations, but also to the ranking of the most productive countries, the top three universities from which significant articles originated were in Vietnam or China: \"Duy Tan University\", \"Chinese Academy of Science\", and \"Ton Duc Thang University\". Figure 22: Thematic map: authors’ keywords. Even if our work has provided valuable insights in terms of the applicability of AI to regional or local studies, we have to admit that during its realization, it has encountered some limitations. It is worth mentioning that the selection of articles for the formation of the database was limited to only those papers that were available in the WoS database. Thus, papers published in unindexed journals or in other document formats may have been excluded, which can be perceived as a limitation. The involvement of several databases (Scopus, Dimensions, or SpringerLink), could help to generate more comprehensive results of the field under study. Although the WoS does not include every publication, it remains one of the most respected and rigorous academic databases [108; 109]. Indexing in the WoS is an indicator of quality and relevance [110; 111], which means that the available articles have gone through a strict selection and evaluation process. In addition, the WoS offers advanced citation and analysis tools that allow researchers to identify trends and impacts in various academic fields [112]. Thus, although there are publications that may have been missed out on, the quality and integrity of the indexed articles compensates for this limitation, providing a solid basis for high-quality research. Another aspect to consider is the linguistic bias and the strict selection of document type. Even if English is one of the most widely known and widespread languages, restricting the analysis to papers only in this language could have an impact on the analysis. Moreover, including more types of papers could have helped by broadening the dataset. The restriction imposed by the choice of keywords is another limitation.