Determination of the Agricultural Land in the Zamanti Sub-basin in Türkiye Using GIS and Analytical Hierarchy Process

Year 2024, Volume: 11 Issue: 4, 29 - 38, 25.12.2024

Abdishakur Dahir Abdullahi

Abstract

This study assessed the suitability of agricultural land within the Zamantı Watershed, located in the Seyhan Basin of Turkey, using Multicriteria Decision Analysis (MCDA) within a Geographic Information Systems (GIS) framework and the Analytical Hierarchy Process (AHP) method. Eight criteria, including elevation, soil, land use, slope, precipitation, drainage density, aspect, and water source proximity, were used to evaluate different regions within the basin. Data from various sources, such as the Digital Elevation Model (DEM), the CORINE Land Cover (CLC) database, rainfall data from Turkey General Directorate of Meteorology and soil data from the Food and Agricultural Organization (FOA), were utilized. The AHP methodology determined the relative importance of the criteria and sub-parameters through pairwise comparison and the Consistency Ratio (CR) analyzed the consistency of the pairwise comparison matrix. The results indicated that 78% of the study area was suitable for agricultural production, with 14.72% being highly suitable, 34.38% moderately suitable, 29.44% typically suitable, 17.93% not suitable and 3.53% permanently unsuitable. The highly suitable areas had flat topography and suitable soil. The average elevation of the basin ranged between 1,000 m and 2,000 m, resulting in slopes that were suitable for agricultural activities. The shape of the basin boundary allowed for easy irrigation of the farm areas as the most remote areas of the basin were located less than 25 km away. The study provided a comprehensive assessment of the suitability of the Zamantı Watershed for agricultural production and could be used for agricultural development of the region.

Keywords

MCDA, AHP, GIS

References

• Aburas, M. M., Abullah, S. H., Ramli, M. F., Ash’aari, Z. H. (2016). A Review of Land Suitability Analysis for Urban Growth by using the GIS-Based Analytic Hierarchy Process. Asian Journal of Applied Sciences, 3.
• Akıncı, H., Özalp, A. Y., Turgut, B. (2013). Agricultural land use suitability analysis using GIS and AHP technique. Computers and Electronics in Agriculture, 97, 71-82.
• Atik, M. E., Safi, O. (2024). Investigation of GIS-based Analytical Hierarchy Process for Multi-Criteria Earthquake Risk Assessment: The Case Study of Kahramanmaras Province. International Journal of Environment and Geoinformatics, 11(3), 156-165.
• Aykut, T. (2021). Determination of groundwater potential zones using Geographical Information Systems (GIS) and Analytic Hierarchy Process (AHP) between Edirne-Kalkansogut (northwestern Türkiye). Groundwater for Sustainable Development, 12, 100545.
• Bellitürk, K. (2018). Vermicomposting in Türkiye: Challenges and opportunities in future. Eurasian Journal of Forest Science, 6(4), 32-41.
• Bonham-Carter, G. (1994). Geographic Information Systems for Geoscientists: Modelling with GIS.
• Bozdağ, A., Yavuz, F., Günay, A. S. (2016). AHP and GIS based land suitability analysis for Cihanbeyli (Türkiye) County. Environmental Earth Sciences, 75(9), 813.
• Brans, J. P., Vincke, Ph. (1985). A preference ranking organisation method (the PROMETHEE method for multiple criteria decision-making). Management Science, 31(6), 647-656.
• Everest, T., Sungur, A., Özcan, H. (2021). Determination of agricultural land suitability with a multiple-criteria decision-making method in Northwestern Türkiye. International Journal of Environmental Science and Technology, 18(5), 1073-1088.
• FAO. (1976). A framework for land evaluation. Food and Agriculture Organization of the United Nations.
• Ghosh, A., Kar, S. K. (2018). Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal, India. Natural Hazards, 94(1), 349-368.
• Hekimoğlu, M., Savun-Hekimoğlu, B., Erbay, B., Gazioğlu, C. (2022). Multi-Criteria Decision-Making analysis for the selection of desalination technologies. International Journal of Environment and Geoinformatics, 9(4), 207-216.
• Hopkins, L. D. (1977). Methods for Generating Land Suitability Maps: A Comparative Evaluation. Journal of the American Institute of Planners, 43(4), 386400.
• Hwang, C.-L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey. Lecture Notes in Economics and Mathematical Systems.
• Kalogirou, S. (2002). Expert systems and GIS: an application of land suitability evaluation. Computers, Environment and Urban Systems, 26(2), 89-112.
• Liu, R., Zhang, K., Zhang, Z., Borthwick, A. G. L. (2014). Land-use suitability analysis for urban development in Beijing. Journal of Environmental Management, 145, 170-179.
• Mahdi, A., Esztergar-Kiss, D. (2021). Modelling the Accommodation Preferences of Tourists by Combining Fuzzy-AHP and GIS Methods. Journal of Advanced Transportation, 2021, 9913513.
• Malczewski, J. (2004). GIS-based land-use suitability analysis: a critical overview. Progress in Planning, 62(1), 3-65.
• Miller, W., Collins, M. G., Steiner, F. R., Cook, E. (1998). An approach for greenway suitability analysis. Landscape and Urban Planning, 42(2), 91105.
• Opricovic, S., Tzeng, G.-H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
• Petersen, J. F., Sack, D., Gabler, R. E. (2013). Physical Geography 672p.
• Purnamasari, R. A., Ahamed, T., Noguchi, R. (2019). Land suitability assessment for cassava production in Indonesia using GIS, remote sensing and multi-criteria analysis. Asia-Pacific Journal of Regional Science, 3(1), 1-32.
• Razvanchy, H. A. S., Fayyadh, M. A. (2022). GIS and AHP Based Techniques for Agricultural Land Suitability Assessment in Erbil Province, Kurdistan region, Iraq. Basrah Journal of Agricultural Sciences, 35(1), 140-157.
• Roy, B. (1968). Classement et choix en presence de points de vue multiples (la methode ELECTRE).
• Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234-281.
• Saaty, T. L. (1980). The analytic hierarchy process: planning, priority setting, resource allocation.
• Saini, S. S.., S.P. (2012). Risk and vulnerability assessment of flood hazard in part of Ghaggar Basin: A case study of Guhla block, Kaithal , Haryana , India. International Journal of Geomatics and Geosciences, 3(1), 42-54.
• Savun-Hekimoğlu, B., Erbay, B., Burak, Z. S., Gazioğlu, C. (2021). A comparative MCDM analysis of potential short-term measures for dealing with mucilage problem in the Sea of Marmara. International Journal of Environment and Geoinformatics, 8(4), 572-580.
• Seyedmohammadi, J., Sarmadian, F., Jafarzadeh, A. A., McDowell, R. W. (2019). Development of a model using matter element, AHP and GIS techniques to assess the suitability of land for agriculture. Geoderma, 352(February 2018), 80-95.
• Store, R., Kangas, J. (2001). Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modelling. Landscape and Urban Planning, 55(2), 79-93.
• Taneja, S., Ozen, E. (2023). Impact of the European Green Deal (EDG) on the Agricultural Carbon (CO2) Emission in Türkiye. International Journal of Sustainable Development and Planning, 18(3), 715727.
• Thakuriah, G. (2023). Geographic information system and analytical hierarchical process approach for groundwater potential zone of lower Kulsi basin, India. Sustainable Water Resources Management, 9(3), 85
• Tolche, A. D., Gurara, M. A., Pham, Q. B., Ditthakit, P., Anh, D. T. (2022). Agricultural land use suitability analysis using AHP and GIS techniques at basin scale. Arabian Journal of Geosciences, 15(18), 1522.
• Ustaoglu, E., Sisman, S., Aydınoglu, A. C. (2021). Determining agricultural suitable land in peri-urban geography using GIS and Multi Criteria Decision Analysis (MCDA) techniques. Ecological Modelling, 455.
• World Bank. (2020). World Development Report 2020: Trading for Development in the Age of Global Value Chains. Washington, DC: World Bank.
• Wu, Q., Liu, Y., Liu, D., Zhou, W. (2011). Prediction of Floor Water Inrush: The Application of GIS-Based AHP Vulnerable Index Method to Donghuantuo Coal Mine, China. Rock Mechanics and Rock Engineering, 44(5), 591-600. https://doi.org/10.1007/s00603-011-0146-5
• Wulder, M. A., Franklin, S. E. (2006). Understanding Forest Disturbance and Spatial Pattern: Remote Sensing and GIS Approaches.
• Yanmaz, A. M. (2018). Applied Water Resources Engineering.
• Yazici, H., Hilmi ŞAHİN, S., Kocatepe Üniversitesi Eğitim Fak Sos Bil Öğrt Afyonkarahisar, A., Fevzi Çakmak Ortaokulu Afyonkarahisar, M. (2013). Teknolojik Araştirmalar CBS Yardımıyla Zamantı Çayı Havzası Ekoturizm Çekiciliklerinin Sunulması. Electronic Journal of Map Technologies, 5(3), 3343. www.teknolojikarastirmalar.com
• Ying, X., Zeng, G.-M., Chen, G.-Q., Tang, L., Wang, K.-L., Huang, D.-Y. (2007). Combining AHP with GIS in synthetic evaluation of eco-environment quality—A case study of Hunan Province, China. Ecological Modelling, 209(2), 97-109.
• Yohannes, H., Soromessa, T. (2018). Land suitability assessment for major crops by using GIS-based multi-criteria approach in Andit Tid watershed, Ethiopia. Cogent Food Agriculture, 4(1), 1470481.