Multi-Criteria Decision Analysis of Maize Planting Suitable Land: A Case Study in Uttaradit Province, Thailand
Article Sidebar
Main Article Content
Abstract
The aim of this particular research is to analyze the spatial suitability for maize planting in Uttaradit Province by using multi-criteria decision analysis with the SAW simple adding weighting method & the AHP analytic hierarchy potential and analyzing the sensitivity to weight changes of various criteria & the results of spatial suitability for maize planting.
The results showed that the importance of decision criteria for selecting suitable areas for maize planting was analyzed by SAW and AHP. They are divided into 3 groups, firstly the very high weight (weighting value > 0.175), including to the effective rainfall and nutrients in
the soil, secondly the relatively high weight (weighting value between 0.120-0.174), there are soil drainage, atmospheric temperature and soil acidity, finally the moderate to low weight (weighting value < 0.119), there are soil depth and slope. There was no significant difference between the priorities of the seven criteria derived from both analyses using the F-test.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
บทความในวารสารเกษตรนเรศวรที่ได้รับการตีพิมพ์ เป็นลิขสิทธิ์ของ คณะเกษตรศาสตร์
ข้อความที่ปรากฏในบทความแต่ละเรื่องในวารสารนี้เป็นความคิดเห็นส่วนตัวของผู้เขียนแต่ละท่านไม่เกี่ยวข้องกับคณะเกษตรศาสตต์ฯ
References
Ali-Khan, M., Ahmad, R., & Hasan-Khan, H. (2021). Multi-criteria land suitability analysis for agriculture using AHP and remote sensing data of Northern region India. In Zhang, Y., & Cheng, Q. (Eds), Geographic information systems and applications in coastal studies. Geographic Information Systems and Applications in Coastal Studies. Open Access Peer-Reviewed Chapter.
Cadet-Díaz, S., & Guerrero-Escobar, S. (2018). Factors that determine the maize production yields in Mexico: Evidence from the 2007 agriculture and livestock census Agricultura Sociedad y Desarrollo, 15(3), 311-337.
Habibie, I., Noguchi, R., Shusuke, M., & Ahamed, T. (2021) Land suitability analysis for maize production in Indonesia using satellite remote sensing and GIS-based multicriteria decision support system. Geo Journal, 86(2), 777-807.
Kazemi, H., & Akinci, H. (2018). A land use suitability model for rainfed farming by multi-criteria decision-making analysis (MCDA) and Geographic Information System (GIS). Ecological Engineering, 116, 1-6.
Kenzong, B., Bitondo, D., Tamfuh, P. A., Kameni, G., Simplice, K., Vounang, J. G., Enang, R. K., Temgoua, E., & Bitom, D. (2022) Land suitability assessment for maize (Zea mays L) production using integrated DEMATEL-ANP model and GIS in the foumbot agricultural basin (Cameroon Western Highlands) Journal of Agronomy & Agricultural Science, 10, 57-85.
Malczewski, J. (1999). GIS and multicriteria decision analysis. New York: John Wiley & Sons.
Mendas, A., & Delali, A. (2012) Integration of multi-criteria decision analysis in GIS to develop land suitability for agriculture: Application to durum wheat cultivation in the region of Mleta in Algeria. Computers and Electronics in Agriculture, 83, 117-126.
Özkan, B., Dengiz, O., & Turan, I. D. (2020). Site suitability analysis for potential agricultural land with spatial fuzzy multi-criteria decision analysis in regional scale under semi-arid terrestrial ecosystem. Scientific Reports, 10(22074), 1-18.
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
Yan-Sui, L., Jie-Yong, W., & Li-Ying, G. (2006). GIS–Based assessment of land suitability for optimal allocation in the Qinling mountain. China Pedosphere, 16(5), 579–586.
