Applying a Scientometrics Approach to Analyze Studies of Optimal Land Use Allocation in a Spatial Information System

Document Type : Original Article

Authors

1 PhD. Candidate in Geospatial Information Systems (GIS), Aerospace Research Institute, Tehran, Iran

2 Assistant Professor, Aerospace Research Institute, Ministry of Science, Research, and Technology, Tehran, Iran

Abstract

Purpose: Land use allocation optimization, as an interdisciplinary field, plays an important role in natural resource management, urban planning, and sustainable development, facilitated by Geographic Information Systems (GIS). In this regard, the aim of the present study is to employ a scientometric approach to analyze the status of published scientific articles. This study aims to provide a comprehensive and accurate overview of trends, key concepts, and commonly utilized methods
in research within this field, as well as to outline future directions for both scientific and practical advancements in the discipline.
Method: This study analyzed a collection of 584 articles published between 1991 and 2024, utilizing data extracted from the Web of Science database. Statistical analyses were conducted using Excel software to identify publication trends, the geographical distribution of articles, and the most active publishers. In addition, VOSviewer software was utilized to identify frequently occurring keywords, cluster them, and analyze their thematic structure.
Findings: The results indicate that since 2010, the production of articles in the field of land use allocation optimization has garnered increased attention, with a steady rise in output continuing until 2022. In this context, China, the United States, and Iran have contributed the most to scientific production in this field, with 302, 103, and 41 articles published, respectively. Among the publishers, Elsevier has been the most prolific, accounting for over 38 percent of the total articles published. Additionally, the identification of keywords revealed that the term GIS is the most frequently
used phrase. Furthermore, meta-heuristic algorithms, such as genetic algorithms, particle swarm optimization, and ant colony optimization, are commonly employed methods for addressing complex land use allocation optimization problems. Keyword clustering has also identified four primary areas: metaheuristic algorithms, spatial modeling, multi-objective optimization, and resource allocation within spatial information systems.
Conclusion: The findings of this study highlight the increasing trend of research in the area of optimal land use allocation. Additionally, the countries and publications that are active in this field have been identified. Furthermore, common methods employed in this domain, including metaheuristic algorithms such as genetic algorithms, have been introduced. Therefore, this study
can serve as a valuable reference for researchers conducting future studies on land use allocation optimization.
 

Keywords

References

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Applied Scientometric Studies
Volume 1, Issue 3
October 2024
Pages 7-18

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