Geospatial Big Data or Big Geospatial Data: A Bibliometric Review

Abstract

The study reviews a broad body of published literature on Geospatial big data or big geospatial data to analyse the nature of the research context, identify trends in the research area, and provide future research directions. Web of Science and Scopus databases were used to collect and convert data to information through an analysis conducted using the Bibliometrix R package and Biblioshiny.   1114 articles were retrieved after de-duplication and the analysis shows that the leading term, Geospatial big data, was first seen in the year 2012. Since then, it has captured the attention of researchers with a yearly increase in articles on the topic. The percentage decline from 2017 to 2018 was 6%, while that between 2020 and 2021 was 17%. On the other hand, the overall increase in annual scientific production between 2012 and 2021 was about 95%, which indicates a massive growth of interest in Geospatial big data.  The results identify the country with the largest number of published articles, the most globally influential author, and the author with the highest average number of citations per year, while research collaborations among countries and the top leading institutions were also identified. Furthermore, the study compared author keywords plus outputs, using co-word analysis. Finally, the study identified gaps and proffered future research directions along which scholarly investigations could expand. The paper suggests that future research should focus on Geospatial big data applications to social media, urban planning, disaster management, and incorporation of artificial intelligence in addressing sustainable development challenges.