EN
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.
Keywords
- Analytical Hierarchy Process
- Bibliometric Analysis
- Cropland
- Geographic Information System
- Suitability
Ethical Statement
not relevant
Thanks
No
References
- Abushnaf, F. F., Spence, K. J., & Rotherham, I. D. (2013). Developing a land evaluation model for the Benghazi region in Northeast Libya using a geographic information system and multi-criteria analysis. APCBEE Procedia, 5, 69-75. https://doi.org/10.1016/j.apcbee.2013.05.013
- Amin, S., Rohani, A., Aghkhani, M. H., & Abbaspour-Fard, M. H., Asgharipour, M. R. (2020). Assessment of land suitability and agricultural production sustainability using a combined approach (Fuzzy-AHP-GIS): A case study of Mazandaran province, Iran. Information Processing in Agriculture, 7(3). 384-402. https://doi.org/10.1016/j.inpa.2019.10.001
- Al Garni, H. Z., & Awasthi, A. (2018). Solar PV Power Plants Site Selection: A Review. In: I. Yahyaoui (Eds.), Advances in Renewable Energies and Power Technologies Volume 1: Solar and Wind Energies (pp. 57-75). https://doi.org/10.1016/B978-0-12-812959-3.00002-2
- Aria, M., & Cuccurullo, C. (2020). Biblioshiny: Bibliometrix for No Coders. 2020. (Accessed:25/04/2024) https://www.bibliometrix.org/home/index.php/layout/bibliometrix
- Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007
- Atenstaedt, R. (2012). Word cloud analysis of the BJGP. British Journal of General Practice, 62(596), 148. https://doi.org/10.3399/bjgp12X630142
- Azzari, G., Jain, M., & Lobell, D. B. (2017). Towards fine resolution global maps of crop yields: Testing multiple methods and satellites in three countries. Remote Sensing of Environment, 202, 129-141. https://doi.org/10.1016/j.rse.2017.04.014
- Baydas, M., Elma, O. E., & Pamučar, D. (2022). Exploring the specific capacity of different multi-criteria decision-making approaches under uncertainty using data from financial markets. Expert Systems with Applications, 197, 116755. https://doi.org/10.1016/j.eswa.2022.116755
Details
Primary Language
English
Subjects
Geoscience Data Visualisation
Journal Section
Research Article
Authors
Publication Date
September 30, 2024
Submission Date
July 4, 2024
Acceptance Date
August 28, 2024
Published in Issue
Year 2024 Volume: 11 Number: 3
APA
Wijesinghe, D. C. (2024). GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis. Gazi University Journal of Science Part A: Engineering and Innovation, 11(3), 598-621. https://doi.org/10.54287/gujsa.1510527
AMA
1.Wijesinghe DC. GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis. GU J Sci, Part A. 2024;11(3):598-621. doi:10.54287/gujsa.1510527
Chicago
Wijesinghe, Dilnu Chanuwan. 2024. “GIS-Based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis”. Gazi University Journal of Science Part A: Engineering and Innovation 11 (3): 598-621. https://doi.org/10.54287/gujsa.1510527.
EndNote
Wijesinghe DC (September 1, 2024) GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis. Gazi University Journal of Science Part A: Engineering and Innovation 11 3 598–621.
IEEE
[1]D. C. Wijesinghe, “GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis”, GU J Sci, Part A, vol. 11, no. 3, pp. 598–621, Sept. 2024, doi: 10.54287/gujsa.1510527.
ISNAD
Wijesinghe, Dilnu Chanuwan. “GIS-Based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis”. Gazi University Journal of Science Part A: Engineering and Innovation 11/3 (September 1, 2024): 598-621. https://doi.org/10.54287/gujsa.1510527.
JAMA
1.Wijesinghe DC. GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis. GU J Sci, Part A. 2024;11:598–621.
MLA
Wijesinghe, Dilnu Chanuwan. “GIS-Based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis”. Gazi University Journal of Science Part A: Engineering and Innovation, vol. 11, no. 3, Sept. 2024, pp. 598-21, doi:10.54287/gujsa.1510527.
Vancouver
1.Dilnu Chanuwan Wijesinghe. GIS-based AHP and MCDA Modeling for Cropland Suitability Analysis: A Bibliometric Analysis. GU J Sci, Part A. 2024 Sep. 1;11(3):598-621. doi:10.54287/gujsa.1510527
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