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Dergiler / Soil Studies / 2023 / Cilt: 12 Sayı: 1

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

Murat Güven TUĞAÇ
Abdullah TERCAN
Harun TORUNLAR
Erol KARAKURT
Mustafa USUL
Sayfa
15–29
Yayın Tarihi
2023-07-18
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The use of geostatistical modeling, MCDA and GIS together is very beneficial in making agricultural land management decisions.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:For sustainable land use planning, evaluating land characteristics and making suitable land use decisions is a priority and critical step.
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Temel Bulgular & Veri:In obtaining the land suitability map; fuzzy set model, Analytical Hierarchy Process (AHP) and GIS are integrated.
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Sonuç & Katkı:The use of geostatistical modeling, MCDA and GIS together is very beneficial in making agricultural land management decisions.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Land suitability · Multi-criteria decision · GIS

Abstract

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.

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Bu Makaleye Atıf Yap

TUĞAÇ, M. G., TERCAN, A., TORUNLAR, H., KARAKURT, E., USUL, M. (2023). Agricultural land suitability assessment with GIS-based multi-criteria decision analysis and geostatistical approach in semi-arid regions. Soil Studies, Cilt: 12 Sayı: 1, 15–29. https://ajindex.com/articles/956235

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Kaynakça (10)

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. Burrough, P. A., & Mc Donnell, R. A. (1998). Principles of