GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis

Abstract

The ' Land Suitability Analysis ' is a useful management method for ensuring that agricultural lands are utilized sustainably and planned based on their potential. Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) for cropland suitability analysis have seen substantial contributions from researchers worldwide. This combination assesses and maps the suitability of land for different crops by utilizing the multi-criteria decision analysis (MCDA) strengths of AHP and the spatial analytic capabilities of GIS. This Bibliometric analysis involves examining publications to identify patterns and trends, such as the most prolific authors & Countries, influential journals, and highly cited papers. It helps in understanding the development and current state of a research field. Using Biblioshiny software, the researchers obtained 183 publications of 687 authors and 319 different institutions using the bibliographic information from the Scopus database. The bibliometric analysis uses the following subcategories: Country, Authors, Publication Sources, Annual Scientific Production, and keywords. By examining the outcomes of bibliometric analysis, methodology, and applications, it was discovered that AHP and MCDA are the most often utilized techniques in this respect. Also, the findings indicated a rising number of publications and a growing interest in the subject, especially in recent years. Over the previous 23 years, the overall trend of publications in this field grew gradually at an annual growth rate of 21.81%. Asian nations, especially China, India, and Iran, have had the biggest influence on the nation's scientific output in the discipline. During this period, India and Iran had the most research papers published. In addition, "GIS," "Land Suitability," and "AHP" are the top three most often used terms. Future trends in this subject are predicted by the current keywords: "GIS," "Land Suitability," "AHP," and "Remote Sensing." Moreover, this exhaustive investigation provides a basis for comprehending the present status and future direction of GIS-based cropland suitability research. These discoveries offer valuable insights for future modeling and research endeavors on the subject and aid in identifying research gaps in the existing literature.