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Agricultural land suitability assessment with GIS-based multi-criteria decision analysis and geostatistical approach in semi-arid regions

Yıl 2023, Cilt: 12 Sayı: 1, 15 - 29, 18.07.2023
https://doi.org/10.21657/soilst.1328637

Öz

For sustainable land use planning, evaluating land characteristics and making suitable land use decisions is a priority and critical step. In order to make these evaluations safely, spatial analyzes of many criteria should be made. In this study, the suitability of the land for wheat production was evaluated by Geographical Information Systems (GIS) based Multiple Criteria Decision Analysis (MCDA) in semi-arid conditions. In obtaining the land suitability map; fuzzy set model, Analytical Hierarchy Process (AHP) and GIS are integrated. Ecological criteria weights for agricultural land suitability were determined by AHP. In the suitability analysis, a total of criteria including soil and topographic features were evaluated. Geostatistical analysis approach was applied to determine the spatial variability of soil properties (sand, clay, silt, pH, OM, CEC, ESP, CaCO3, EC). The lowest variation among soil properties was observed in pH (3.8%), while the largest variation was observed in ESP content (107.5%). The nugget/sill ratio is poor for EC and pH, while other soil properties are moderately spatially dependent. According to the results of the analysis, 25.7% (3.226 km2) of the area is highly suitable, while 27.6% (3.457 km2) is moderately suitable and 19.5% (2.440 km2) is marginally suitable for wheat cultivation. In addition, 27.2% (3.415 km2) of the area is not suitable for agricultural production. The use of geostatistical modeling, MCDA and GIS together is very beneficial in making agricultural land management decisions.

Kaynakça

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  • Dengiz, O. (2020). Soil quality index for paddy fields based on standard scoring functions and weight allocation method. Archives of Agronomy and Soil Science, 66(3), 301–315. https://doi.org/10.1080/03650340.2019.1610880. Di Virgilio, N., Monti, A., & Venturi, G. (2007). Spatial variability of switchgrass (Panicum virgatum L.) yield as related to soil parameters in a small field. Field Crops Research, 101, 232–239. https://doi.org/10.1016/j.fcr.2006.11.009.
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  • Everest, T., Sungur, A., & Özcan, H. (2021). Determination of agricultural land suitability with a multiple criteria decision making method in Northwestern Turkey. International Journal of Environmental Science and Technology, 18, 1073–1088. https://doi.org/10.1007/s13762-020-02869-9.
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Yıl 2023, Cilt: 12 Sayı: 1, 15 - 29, 18.07.2023
https://doi.org/10.21657/soilst.1328637

Öz

Kaynakça

  • AbdelRahman, M. A. E., Zakarya, Y. M., Metwaly, M. M., & Koubouris, G. (2020). Deciphering soil spatial variability through geostatistics and interpolation techniques. Sustainability, 13, 194. https://doi.org/10.3390/su13010194.
  • Aggag, A. M., & Alharbi, A. (2022). Spatial analysis of soil properties and site-specific management zone delineation for the South Hail Region, Saudi Arabia. Sustainability, 14, 16209. https://doi.org/10.3390/su142316209.
  • Arab, S. T., & Ahamed, T. (2022). Land suitability analysis for potential vineyards extension in afghanistan at regional scale using remote sensing datasets. Remote Sensing, 14, 4450. https://doi.org/10.3390/rs14184450. Arora, N. K. (2019) Impact of climate change on agriculture production and its sustainable solutions. Environmental Sustainability, 2, 95–96. https:// doi. org/ 10. 1007/ s42398- 019-00078-w.
  • Azadi, A., & Baninemeh, J. (2022). Performance analysis of geostatistical approach and PCA techniques for mapping cation exchange capacity in the South West of Iran. Eurasian Soil Science, 55(12), 1749–1760. https://doi.org/10.1134/S1064229322601494.
  • Bagherzadeh, A., & Gholizadeh, A. (2018). Assessment of soil fertility for sugar beet production using fuzzy AHP approach and GIS in the Northeastern region of Iran. Agricultural Research, 7(1), 61-71. https://doi.org/10.1007/s40003-018-0295-9. Baroudy, A. A. E. (2016). Mapping and evaluating land suitability using a GIS-based model. Catena, 140, 96–104. http://dx.doi.org/10.1016/j.catena.2015.12.010.
  • Behera, S. K., Mathur, R. K., Shukla, A. K., Suresh, K., & Prakash, C. (2018). Spatial variability of soil properties and delineation of soil management zones of oil palm plantations grown in a hot and humid tropical region of southern India. Catena, 165, 251–259. https://doi.org/10.1016/j.catena.2018.02.008.
  • Bogunovic, I., Kisic, I., Mesic, M., Percin, A., Zgorelec, Z., Bilandžija, D., Jonjic A., & Pereira, P. (2017). Reducing sampling intensity in order to investigate spatial variability of soil pH, organic matter and available phosphorus using co-kriging techniques. A case study of acid soils in Eastern Croatia. Archives of Agronomy and Soil Science, 63, 1852-1863. https://doi.org/10.1080/03650340.2017.1311013.
  • Burrough, P. A. (1996). Natural objects with Indeterminate Boundaries. in P.A. Burrough and A.U. Frank (eds.), Geographic Objects with Indeterminate Boundaries, London: Taylor & Francis, pp. 3–28. Burrough, P. A., & Mc Donnell, R. A. (1998). Principles of geographical information systems. Oxford Univ. Press, Oxford. 333 pp.
  • Cambardella, C. A., & Karlen, D. L. (1999). Spatial analysis of soil fertility parameters. Precision Agriculture, 1, 5–14. https://doi.org/10.1023/A:1009925919134.
  • Cambardella, C. A., Moorman, T. B., Novak, J. M., Parkin, T. B., Karlen, D. L., Turco, R. F., & Konopka, A. E. (1994). Fieldscale variability of soil properties in Central Iowa Soils. Soil Science Society of America Journal, 58, 1501-1511.
  • Dedeoğlu, M., & Dengiz, O. (2019). Generating of land suitability index for wheat with hybrid system aproach using AHP and GIS. Computers and Electronics in Agriculture, 167, 105062. https://doi.org/10.1016/j.compag.2019.105062.
  • Dengiz, O., & Baskan, O. (2009). Land quality assessment and sustainable land use in Salt Lake (Tuz Gölü) specially protected area. Environmental Monitoring and Assessment, 148(1-4), 233–243. https://doi.org/10.1007/s10661-008-0154-4.
  • Dengiz, O. (2020). Soil quality index for paddy fields based on standard scoring functions and weight allocation method. Archives of Agronomy and Soil Science, 66(3), 301–315. https://doi.org/10.1080/03650340.2019.1610880. Di Virgilio, N., Monti, A., & Venturi, G. (2007). Spatial variability of switchgrass (Panicum virgatum L.) yield as related to soil parameters in a small field. Field Crops Research, 101, 232–239. https://doi.org/10.1016/j.fcr.2006.11.009.
  • Durdevic, B., Jug, I., Jug, D., Bogunovic, I., Vukadinovic, V., Stipeševic, B., & Brozovic, B. (2019). Spatial variability of soil organic matter content in Eastern Croatia assessed using different interpolation methods. International Agrophysics, 33(1), 31-39. https://doi.org/10.31545/intagr/104372.
  • Emadi, M., Baghernejad, M., Emadi, M., & Maftoun, M. (2008). Assessment of some soil properties by spatial variability in saline and sodic soils in Arsanjan plain, Southern Iran. Pakistan journal of biological sciences, 11(2), 238–243. https://doi.org/10.3923/pjbs.2008.238.243.
  • Everest, T., Sungur, A., & Özcan, H. (2021). Determination of agricultural land suitability with a multiple criteria decision making method in Northwestern Turkey. International Journal of Environmental Science and Technology, 18, 1073–1088. https://doi.org/10.1007/s13762-020-02869-9.
  • Goovaerts, P. (1998). Geostatistical tools for characterizing the spatial variability of microbiological and physio-chemical soil properties. Biology and Fertility of Soils, 27, 315–334. https://doi.org/10.1007/s003740050439.
  • FAO. (1976). A Framework for land evaluation. Soil Bulletin, vol. 32. FAO, Rome. ISBN 92-5- 100111-1.
  • FAO. (1993). Guidelines for land-use planning. FAO Development Series I. FAO, Rome.
  • FAO. (2017). The future of food and agriculture. Trends and challenges.
  • FAO-TOB. (2020). Ulusal Bozkır Koruma Strateji ve Eylem Planı. Doğa Koruma Merkezi, Türkiye’nin Bozkır Ekosistemlerinin Korunması ve Sürdürülebilir Yönetimi Projesi Yayını. 167 sayfa. Ankara. Birleşmiş Milletler Gıda ve Tarım Örgütü (FAO), Tarım ve Orman Bakanlığı (TOB).
  • Jiang, H. L., Liu, G. S., Liu, S. D., Li, E. H., Wang, R., Yang, Y. F., & Hu, H. C. (2012). Delineation of site-specific management zones based on soil properties for a hillside field in central China. Archives of Agronomy and Soil Science, 58(10), 1075–1090. https://doi.org/10.1080/03650340.2011.570337a.
  • Kariuki, S. K., Zhang, H., Schroder, J. L., Hanks, T., Payton, M., & Morris, T. (2009). Spatial variability and soil sampling in a grazed pasture. Communications in Soil Science and Plant Analysis, 40(9-10), 1674–1687. https://doi.org/10.1080/00103620902832089.
  • Khan, M. Z., Islam, M. A., Sadiqul Amin, M., & Bhuiyan, M. M. R. (2019). Spatial variability and geostatistical analysis of selected soil. Bangladesh Journal of Scientific and Industrial Research, 54(1), 55-66. https://doi.org/10.3329/bjsir.v54i1.40731.
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  • Mousavi, S. R., Sarmadian, F., Dehghani, S., Sadikhani, M. R., & Taati, A. (2017). Evaluating inverse distance weighting and kriging methods in estimation of some physical and chemical properties of soil in Qazvin Plain. Eurasian Journal of Soil Science, 6(4), 327–336. https://doi.org/10.18393/ejss.311210.
  • Mousavifard, S. M., Hamireza Momtaza, H., Sepehr, E., Davatgar, N., & Sadaghiani, M. H. R. (2013). Determining and mapping some soil physico-chemical properties using geostatistical and GIS techniques in the Naqade region, Iran. Archives of Agronomy and Soil Science, 59(11), 1573–1589. http://dx.doi.org/10.1080/03650340.2012.740556.
  • Nguyen, T. T., Verdoodt, A., Tran, V. Y., Nele Delbecque, N. Tran, T. C., & Van Ranst, E. (2015). Design of a GIS and multi-criteria based land evaluation procedure for sustainable land-use planning at the regional level. Agriculture, Ecosystems and Environment, 200, 1–11. http://dx.doi.org/10.1016/j.agee.2014.10.015.
  • Obalum, S. E., Chibuike, G. U., Peth, S., & Ouyang, Y. (2017). Ouyang soil organic matter as sole indicator of soil degradation. Environmental Monitoring and Assessment, 89(4), 1–19. https://doi.org/10.1007/s10661-017-5881-y.
  • Öner, N., Erşahin, S., Ayan, S., & Özel, H. B. (2016). Rehabilitation of semi-arid areas in central anatolia. Anatolian Journal of Forest Research, 2 (1-2), 32-44.
  • Özkan, B., Dengiz, O., & Turan, İ. 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. https://doi.org/10.1038/s41598-020-79105-4.
  • Piccini, C., Marchetti, A., & Francaviglia, R. (2014). Estimation of soil organic matter by geostatistical methods: use of auxiliary information in agriculture and environmental assessment. Ecological Indicators, 36, 301–314. https://doi.org/10.1016/j.ecolind.2013.08.009.
  • Pilevar, A. R., Matinfar, H. R., Sohrabi, A., & Sarmadian, F. (2020). Integrated fuzzy, AHP and GIS techniques for land suitability assessment in semi-arid regions for wheat and maize farming. Ecological Indicators, 110, 105887. https://doi.org/10.1016/j.ecolind.2019.105887.
  • Pham, T. G., Kappas, M., Van Huynh, C., & Nguyen, L. H. K. (2019). Application of ordinary kriging and regression kriging method for soil properties mapping in hilly region of central Vietnam. ISPRS International Journal of Geo-Information, 8(3), 147. https://doi.org/10.3390/ijgi8030147.
  • Prosekov, A. Y., & Ivanova, S. A. (2018). Food security: the challenge of the present. Geoforum 91, 73–77. https://doi.org/10.1016/j.geoforum.2018.02.030.
  • Raffa, W. D., Bogdanski, A., & Tittonell, P. (2015). How does crop residue removal affect soil organic carbon and yield? A hierarchical analysis of management and environmental factors. Biomass and Bioenergy, 81, 345-355. http://dx.doi.org/10.1016/j.biombioe.2015.07.022.
  • Ramamurthy, V., Reddy, G. P. O., & Kumar, N. (2020). Assessment of land suitability for maize (Zea mays L) in semi-arid ecosystem of southern India using integrated AHP and GIS approach. Computers and Electronics in Agriculture, 179, 105806. https://doi.org/10.1016/j.compag.2020.105806.
  • Reza, S. K., Nayak, D. C., Chattopadhyay, T., Mukhopadhyay, S., Singh, S. K., & Srinivasan, R. (2016). Spatial distribution of soil physical properties of alluvial soils: a geostatistical approach. Archives of Agronomy and Soil Science, 62, 972-981. https://doi.org/10.1080/03650340.2015.1107678.
  • Saaty, T. L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation; McGraw-Hill International: New York, NY, USA.
  • Sharma, R., & Sood, K. (2020). Characterization of spatial variability of soil parameters in apple orchards of himalayan region using geostatistical analysis, Communications in Soil Science and Plant Analysis, 1-13. https://doi.org/10.1080/00103624.2020.1744637.
  • Saidian, M., Godinez, L. J., & Prasad, M. (2016). Effect of clay and organic matter on nitrogen adsorption specific surface area and cation exchange capacity in shales (mudrocks). Journal of Natural Gas Science and Engineering, 33, 1095–1106. https://doi.org/10.1016/j.jngse.2016.05.064.
  • Selmy, S., Abd El-Aziz, S., El-Desoky, A., & El-Sayed, M. (2022). Characterizing, predicting, and mapping of soil spatial variability in Gharb El-Mawhoub area of Dakhla Oasis using geostatistics and GIS approaches. Journal of the Saudi Society of Agricultural Sciences, 2, 383–396. https://doi.org/10.1016/j.jssas.2021.10.013.
  • Shaloo, Singh, R. P., Bisht, H., Jain, R., Suna, T., Bana, R. S., Godara, S., Shivay, Y. S., Singh, N., Bedi, J., Begam, S., Tamta, M., & Gautam, S. (2022). Crop-suitability analysis using the analytic hierarchy process and geospatial techniques for cereal production in North India. Sustainability, 14, 5246. https://doi.org/10.3390/su14095246.
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  • Zhan, J., He, Y., Zhao, G., Li, Z., Yuan, Q., & Liu, L. (2020). Quantitative Evaluation of the spatial variation of surface soil properties in a typical alluvial plain of the lower yellow river using classical statistics, geostatistics and single fractal and multifractal methods. Applied Sciences, 10(17), 5796; https://doi.org/10.3390/app10175796.
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Toplam 66 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ziraat Mühendisliği (Diğer)
Bölüm Research Articles
Yazarlar

Murat Güven Tuğaç Bu kişi benim 0000-0001-5941-5487

Abdullah Tercan 0000-0002-0393-4656

Harun Torunlar 0000-0003-3504-7231

Erol Karakurt Bu kişi benim 0000-0002-0977-3419

Mustafa Usul 0000-0003-0410-642X

Yayımlanma Tarihi 18 Temmuz 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 12 Sayı: 1

Kaynak Göster

APA Tuğaç, M. G., Tercan, A., Torunlar, H., Karakurt, E., vd. (2023). Agricultural land suitability assessment with GIS-based multi-criteria decision analysis and geostatistical approach in semi-arid regions. Soil Studies, 12(1), 15-29. https://doi.org/10.21657/soilst.1328637