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IDENTIFY SUITABLE AREAS FOR PEANUT CULTIVATION IN OSMANIYE PROVINCE THROUGH THE AHP METHOD

Year 2025, Volume: 13 Issue: 4, 1063 - 1082, 01.12.2025
https://doi.org/10.36306/konjes.1661112

Abstract

Osmaniye is a province in the Mediterranean Region of Türkiye that stands out with its fertile agricultural lands and suitable climate conditions. Among the agricultural activities that form the basis of the regional economy, peanut production has an important economic and social place. Sustainable agricultural practices aim at the efficient use of agricultural lands and the protection of natural resources. In this context, determining suitable areas for cultivating strategic products such as peanuts is critical for protecting long-term agricultural production and ecosystem balance. In this study, 11 parameters were determined using the remote sensing & geographic information systems (RS&GIS)-based analytical hierarchy process (AHP) method to determine suitable areas for peanut cultivation in Osmaniye province. The receiver operating characteristic (ROC) curve was used to verify the produced model, and the area under the curve (AUC) value was 78.5%. Consequently, the analysis performed was found to be consistent and reliable. The study findings showed that Osmaniye allows peanut cultivation to be carried out sustainably and is strategically important for this species.

References

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  • W. Zhou et al., “Cultivated Land Quality Evaluated Using the RNN Algorithm Based on Multisource Data,” Remote Sens., vol. 14, no. 23, 2022, doi: 10.3390/rs14236014.
  • D. L. Nguyen, T. Y. Chou, M. H. Chen, T. V. Hoang, and T. P. Tran, “A GIS-Based Multicriteria Analysis of Land Suitability for Groundnut Crop in Nghe An Province, Vietnam,” Int. J. Geoinformatics, vol. 17, no. 6, pp. 85–95, 2021, doi: 10.52939/ijg.v17i6.2071.
  • M. Jiang et al., “Peanut Drought Risk Zoning in Shandong Province, China,” Sustain., vol. 14, no. 6, 2022, doi: 10.3390/su14063322.
  • Kamila Abba Tukur et al., “Land suitability mapping for groundnut production in southern region of Borno state, Nigeria,” World J. Adv. Res. Rev., vol. 23, no. 1, pp. 1961–1971, 2024, doi: 10.30574/wjarr.2024.23.1.2163.
  • “FAO,” 2024. https://www.fao.org/faostat/en/#data/QC/visualize (accessed Oct. 25, 2024).
  • “TÜİK,” 2024. https://biruni.tuik.gov.tr/medas/?locale=tr (accessed Sep. 23, 2024).
  • A. Kadiroğlu, “Yer fıstığı yetiştiriciliği,” Batı Akdeniz Tarımsal Araştırma Enstitüsü Müdürlüğü Antalya, 2023.
  • “Hilltarım,” 2025. https://www.hilltarim.com/tr/posts/dunyada-ve-ulkemizde-yer-fistigi (accessed Oct. 03, 2025).
  • “TOB,” 2024. https://arastirma.tarimorman.gov.tr/batem/Belgeler/Kutuphane/Teknik Bilgiler/yerfistigi yetistiriciligi.pdf#page=4.08 (accessed Sep. 23, 2024).
  • “Governorship of Osmaniye,” 2019. http://www.osmaniye.gov.tr/ (accessed Oct. 25, 2023).
  • N. İşler and R. Gözüyeşil, “Osmaniye İlinde Yerfıstığı Yetiştiriciliği ile İlgili Sorunların Saptanması,” Tarla Bitk. Merk. Araştırma Enstitüsü Derg., vol. 25, no. ÖZEL SAYI-2, pp. 36–36, 2016, doi: 10.21566/tarbitderg.281744.
  • “Tadportal,” 2021. http://tad.tarim.gov.tr/ (accessed Oct. 08, 2021).
  • “WorldClim,” 2024. https://www.worldclim.org/ (accessed Aug. 03, 2024).
  • “Copernicus,” 2024. https://land.copernicus.eu/ (accessed Mar. 08, 2024).
  • S. Cengiz, “Determination of land use suitability using multiple decision methods: A case study of Bartın basin,” Bartın University, 2015.
  • B. Akıncı, H., Özalp, A. Y., Özalp, M., Turgut, “Büyük barajların tarım arazileri üzerindeki etkilerinin incelenmesi ve Artvin’de CBS ve AHP yöntemi kullanılarak alternatif tarım arazilerinin belirlenmesi (in Turkish),” 2015.
  • T. L. Saaty, “A scaling method for priorities in hierarchical structures,” J. Math. Psychol., vol. 15, no. 3, pp. 234–281, 1977, doi: 10.1016/0022-2496(77)90033-5.
  • B. Akıncı, H., Özalp, A. Y., Turgut, “Determining Suitable Arable Lands with AHP Method,” 2012.
  • R. W. Saaty, “The analytic hierarchy process-what it is and how it is used,” Math. Model., vol. 9, no. 3–5, pp. 161–176, 1987, doi: 10.1016/0270-0255(87)90473-8.
  • T. Hao, J. Elith, J. J. Lahoz-Monfort, and G. Guillera-Arroita, “Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models,” Ecography (Cop.)., vol. 43, no. 4, pp. 549–558, 2020, doi: 10.1111/ecog.04890.
  • R. Valavi, G. Guillera-Arroita, J. J. Lahoz-Monfort, and J. Elith, “Predictive performance of presence-only species distribution models: a benchmark study with reproducible code,” Ecol. Monogr., vol. 92, no. 1, 2022, doi: 10.1002/ecm.1486.
  • R. D. Crego, J. A. Stabach, and G. Connette, “Implementation of species distribution models in Google Earth Engine,” Divers. Distrib., vol. 28, no. 5, pp. 904–916, 2022, doi: 10.1111/ddi.13491.
  • M. M. Özdel, B. Ustaoğlu, and İ. Cürebal, “Modeling of the Potential Distribution Areas Suitable for Olive (Olea europaea L.) in Türkiye from a Climate Change Perspective,” Agric., vol. 14, no. 9, 2024, doi: 10.3390/agriculture14091629.
  • S. Johnson, B. Molano-Flores, and D. Zaya, “Field validation as a tool for mitigating uncertainty in species distribution modeling for conservation planning,” Conserv. Sci. Pract., vol. 5, no. 8, 2023, doi: 10.1111/csp2.12978.
  • E. Salifu, W. Agyei Agyare, and S. Abdul-Ganiyu, “Evaluation of Land Suitability for Crop Production in Northern Ghana Using GIS and AHP Based Techniques,” Int. J. Environ. Geoinformatics, vol. 9, no. 4, pp. 46–56, 2022, doi: 10.30897/ijegeo.1022275.
  • M. D. Diallo et al., “Soil suitability for the production of rice, groundnut, and cassava in the peri-urban Niayes zone, Senegal,” Soil Tillage Res., vol. 155, pp. 412–420, 2016, doi: 10.1016/j.still.2015.09.009.
  • B. Kalaiselvi et al., “Promoting Agricultural Sustainability in Semi-arid Regions: An Integrated GIS–AHP Assessment of Land Suitability for Encouraging Crop Diversification,” J. Indian Soc. Remote Sens., vol. 52, no. 10, pp. 2221–2233, 2024, doi: 10.1007/s12524-024-01937-8.
  • N. Perveen, S. B. Muzaffar, A. Jaradat, O. A. Sparagano, and A. L. Willingham, “Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling,” Parasitology, 2024, doi: 10.1017/S0031182024001161.
  • T. A. S. T. M. Suhairi, E. Jahanshiri, and N. M. M. Nizar, “Multicriteria land suitability assessment for growing underutilised crop, bambara groundnut in Peninsular Malaysia,” IOP Conf. Ser. Earth Environ. Sci., vol. 169, no. 1, 2018, doi: 10.1088/1755-1315/169/1/012044.
  • M. B. Moisa, B. B. Merga, B. T. Gabissa, and D. O. Gemeda, “Assessment of land suitability for oilseeds crops (sesame and groundnut) using geospatial techniques: In the case of Diga district, East Wollega zone, western Ethiopia,” Oil Crop Sci., vol. 7, no. 3, pp. 127–134, 2022, doi: 10.1016/j.ocsci.2022.08.001.
  • V. L. Sivakumar, R. Radha Krishnappa, and M. Nallanathel, “Drought vulnerability assessment and mapping using Multi-Criteria decision making (MCDM) and application of Analytic Hierarchy process (AHP) for Namakkal District, Tamilnadu, India,” Mater. Today Proc., vol. 43, pp. 1592–1599, 2020, doi: 10.1016/j.matpr.2020.09.657.

Year 2025, Volume: 13 Issue: 4, 1063 - 1082, 01.12.2025
https://doi.org/10.36306/konjes.1661112

Abstract

References

  • “FAO,” 2025. https://www.fao.org/faostat/en/#data/RL/visualize (accessed Mar. 10, 2025).
  • “TÜİK,” 2025. https://biruni.tuik.gov.tr/medas/?locale=tr (accessed Mar. 10, 2025).
  • “SDGs,” 2025. https://sdgs.un.org/goals (accessed Mar. 10, 2025).
  • K. Akpoti, A. T. Kabo-bah, and S. J. Zwart, “Agricultural land suitability analysis: State-of-the-art and outlooks for integration of climate change analysis,” Agric. Syst., vol. 173, pp. 172–208, 2019, doi: 10.1016/j.agsy.2019.02.013.
  • M. Mokarram and M. Hojati, “Using ordered weight averaging (OWA) aggregation for multi-criteria soil fertility evaluation by GIS (case study: southeast Iran),” Comput. Electron. Agric., vol. 132, no. 1, pp. 1–13, Jan. 2017, doi: 10.1016/j.compag.2016.11.005.
  • Y. E. Roell, A. Beucher, P. G. Møller, M. B. Greve, and M. H. Greve, “Comparing a random-forest-based prediction of winter wheat yield to historical yield potential,” Agronomy, vol. 10, no. 3, 2020, doi: 10.3390/agronomy10030395.
  • A. Bozdağ, F. Yavuz, and A. S. Günay, “AHP and GIS based land suitability analysis for Cihanbeyli (Turkey) County,” Environ. Earth Sci., vol. 75, no. 9, 2016, doi: 10.1007/s12665-016-5558-9.
  • M. Ö. Çelik, L. Kuşak, and M. Yakar, “Assessment of Groundwater Potential Zones Utilizing Geographic Information System-Based Analytical Hierarchy Process, Vlse Kriterijumska Optimizacija Kompromisno Resenje, and Technique for Order Preference by Similarity to Ideal Solution Methods: A Case S,” Sustain., vol. 16, no. 5, 2024, doi: 10.3390/su16052202.
  • O. Orhan, “Land suitability determination for citrus cultivation using a GIS-based multi-criteria analysis in Mersin, Turkey,” Comput. Electron. Agric., vol. 190, 2021, doi: 10.1016/j.compag.2021.106433.
  • M. G. Gümüş and S. S. Durduran, “Determination of Potential Geothermal Areas in Konya Seydişehir District Using GIS-based Multi-Criteria Decision Analysis,” Turkish J. Remote Sens., 2024, doi: 10.51489/tuzal.1400620.
  • Z. Zheng, T. Morimoto, and Y. Murayama, “A GIS-based bivariate logistic regression model for the site-suitability analysis of parcel-pickup lockers: A case study of Guangzhou, China,” ISPRS Int. J. Geo-Information, vol. 10, no. 10, 2021, doi: 10.3390/ijgi10100648.
  • S. Doğan, L. Genç, S. C. Yücebaş, and Ş. Yalpır, “Analyzing The Impact of the 2023 General Elections on Land Prices Using Machine Learning: A Case Study In Çanakkale, Turkey,” Konya J. Eng. Sci., vol. 13, no. 1, pp. 147–164, Mar. 2025, doi: 10.36306/konjes.1579931.
  • M. Akbari, E. Neamatollahi, and P. Neamatollahi, “Evaluating land suitability for spatial planning in arid regions of eastern Iran using fuzzy logic and multi-criteria analysis,” Ecol. Indic., vol. 98, pp. 587–598, 2019, doi: 10.1016/j.ecolind.2018.11.035.
  • S. K. Shaw, N. Sravani, A. Sharma, and J. Anand, “Assessment of probable zones of agricultural land suitability based on MCDM, probabilistic, and data-driven approach in Krishna District, India,” Environ. Monit. Assess., vol. 197, no. 3, 2025, doi: 10.1007/s10661-025-13803-2.
  • A. Li et al., “Spatial suitability evaluation based on multisource data and random forest algorithm: a case study of Yulin, China,” Front. Environ. Sci., vol. 12, 2024, doi: 10.3389/fenvs.2024.1338931.
  • E. Aşci and L. Genç, “Determination of the Effects of Various Spectral Index Combinations on Seasonal Land Use and Land Cover (Lulc) Changes Using Random Forest (Rf) Classification Case Study: Southeast Marmara Region 2016-2020,” Turkish J. Remote Sens., 2024, doi: 10.51489/tuzal.1395189.
  • S. Lee, S. M. Hong, and H. S. Jung, “A support vector machine for landslide susceptibility mapping in Gangwon Province, Korea,” Sustain., vol. 9, no. 1, 2017, doi: 10.3390/su9010048.
  • L. S. Reddy, D. Kumar, A. Rastogi, and K. Jain, “Enhancing agricultural sustainability through CNN-LSTM based land suitability assessment for improved production,” Multidiscip. Sci. J., vol. 6, p. 2024ss0514, 2024, doi: 10.31893/multiscience.2024ss0514.
  • W. Zhou et al., “Cultivated Land Quality Evaluated Using the RNN Algorithm Based on Multisource Data,” Remote Sens., vol. 14, no. 23, 2022, doi: 10.3390/rs14236014.
  • D. L. Nguyen, T. Y. Chou, M. H. Chen, T. V. Hoang, and T. P. Tran, “A GIS-Based Multicriteria Analysis of Land Suitability for Groundnut Crop in Nghe An Province, Vietnam,” Int. J. Geoinformatics, vol. 17, no. 6, pp. 85–95, 2021, doi: 10.52939/ijg.v17i6.2071.
  • M. Jiang et al., “Peanut Drought Risk Zoning in Shandong Province, China,” Sustain., vol. 14, no. 6, 2022, doi: 10.3390/su14063322.
  • Kamila Abba Tukur et al., “Land suitability mapping for groundnut production in southern region of Borno state, Nigeria,” World J. Adv. Res. Rev., vol. 23, no. 1, pp. 1961–1971, 2024, doi: 10.30574/wjarr.2024.23.1.2163.
  • “FAO,” 2024. https://www.fao.org/faostat/en/#data/QC/visualize (accessed Oct. 25, 2024).
  • “TÜİK,” 2024. https://biruni.tuik.gov.tr/medas/?locale=tr (accessed Sep. 23, 2024).
  • A. Kadiroğlu, “Yer fıstığı yetiştiriciliği,” Batı Akdeniz Tarımsal Araştırma Enstitüsü Müdürlüğü Antalya, 2023.
  • “Hilltarım,” 2025. https://www.hilltarim.com/tr/posts/dunyada-ve-ulkemizde-yer-fistigi (accessed Oct. 03, 2025).
  • “TOB,” 2024. https://arastirma.tarimorman.gov.tr/batem/Belgeler/Kutuphane/Teknik Bilgiler/yerfistigi yetistiriciligi.pdf#page=4.08 (accessed Sep. 23, 2024).
  • “Governorship of Osmaniye,” 2019. http://www.osmaniye.gov.tr/ (accessed Oct. 25, 2023).
  • N. İşler and R. Gözüyeşil, “Osmaniye İlinde Yerfıstığı Yetiştiriciliği ile İlgili Sorunların Saptanması,” Tarla Bitk. Merk. Araştırma Enstitüsü Derg., vol. 25, no. ÖZEL SAYI-2, pp. 36–36, 2016, doi: 10.21566/tarbitderg.281744.
  • “Tadportal,” 2021. http://tad.tarim.gov.tr/ (accessed Oct. 08, 2021).
  • “WorldClim,” 2024. https://www.worldclim.org/ (accessed Aug. 03, 2024).
  • “Copernicus,” 2024. https://land.copernicus.eu/ (accessed Mar. 08, 2024).
  • S. Cengiz, “Determination of land use suitability using multiple decision methods: A case study of Bartın basin,” Bartın University, 2015.
  • B. Akıncı, H., Özalp, A. Y., Özalp, M., Turgut, “Büyük barajların tarım arazileri üzerindeki etkilerinin incelenmesi ve Artvin’de CBS ve AHP yöntemi kullanılarak alternatif tarım arazilerinin belirlenmesi (in Turkish),” 2015.
  • T. L. Saaty, “A scaling method for priorities in hierarchical structures,” J. Math. Psychol., vol. 15, no. 3, pp. 234–281, 1977, doi: 10.1016/0022-2496(77)90033-5.
  • B. Akıncı, H., Özalp, A. Y., Turgut, “Determining Suitable Arable Lands with AHP Method,” 2012.
  • R. W. Saaty, “The analytic hierarchy process-what it is and how it is used,” Math. Model., vol. 9, no. 3–5, pp. 161–176, 1987, doi: 10.1016/0270-0255(87)90473-8.
  • T. Hao, J. Elith, J. J. Lahoz-Monfort, and G. Guillera-Arroita, “Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models,” Ecography (Cop.)., vol. 43, no. 4, pp. 549–558, 2020, doi: 10.1111/ecog.04890.
  • R. Valavi, G. Guillera-Arroita, J. J. Lahoz-Monfort, and J. Elith, “Predictive performance of presence-only species distribution models: a benchmark study with reproducible code,” Ecol. Monogr., vol. 92, no. 1, 2022, doi: 10.1002/ecm.1486.
  • R. D. Crego, J. A. Stabach, and G. Connette, “Implementation of species distribution models in Google Earth Engine,” Divers. Distrib., vol. 28, no. 5, pp. 904–916, 2022, doi: 10.1111/ddi.13491.
  • M. M. Özdel, B. Ustaoğlu, and İ. Cürebal, “Modeling of the Potential Distribution Areas Suitable for Olive (Olea europaea L.) in Türkiye from a Climate Change Perspective,” Agric., vol. 14, no. 9, 2024, doi: 10.3390/agriculture14091629.
  • S. Johnson, B. Molano-Flores, and D. Zaya, “Field validation as a tool for mitigating uncertainty in species distribution modeling for conservation planning,” Conserv. Sci. Pract., vol. 5, no. 8, 2023, doi: 10.1111/csp2.12978.
  • E. Salifu, W. Agyei Agyare, and S. Abdul-Ganiyu, “Evaluation of Land Suitability for Crop Production in Northern Ghana Using GIS and AHP Based Techniques,” Int. J. Environ. Geoinformatics, vol. 9, no. 4, pp. 46–56, 2022, doi: 10.30897/ijegeo.1022275.
  • M. D. Diallo et al., “Soil suitability for the production of rice, groundnut, and cassava in the peri-urban Niayes zone, Senegal,” Soil Tillage Res., vol. 155, pp. 412–420, 2016, doi: 10.1016/j.still.2015.09.009.
  • B. Kalaiselvi et al., “Promoting Agricultural Sustainability in Semi-arid Regions: An Integrated GIS–AHP Assessment of Land Suitability for Encouraging Crop Diversification,” J. Indian Soc. Remote Sens., vol. 52, no. 10, pp. 2221–2233, 2024, doi: 10.1007/s12524-024-01937-8.
  • N. Perveen, S. B. Muzaffar, A. Jaradat, O. A. Sparagano, and A. L. Willingham, “Camel tick species distribution in Saudi Arabia and United Arab Emirates using MaxEnt modelling,” Parasitology, 2024, doi: 10.1017/S0031182024001161.
  • T. A. S. T. M. Suhairi, E. Jahanshiri, and N. M. M. Nizar, “Multicriteria land suitability assessment for growing underutilised crop, bambara groundnut in Peninsular Malaysia,” IOP Conf. Ser. Earth Environ. Sci., vol. 169, no. 1, 2018, doi: 10.1088/1755-1315/169/1/012044.
  • M. B. Moisa, B. B. Merga, B. T. Gabissa, and D. O. Gemeda, “Assessment of land suitability for oilseeds crops (sesame and groundnut) using geospatial techniques: In the case of Diga district, East Wollega zone, western Ethiopia,” Oil Crop Sci., vol. 7, no. 3, pp. 127–134, 2022, doi: 10.1016/j.ocsci.2022.08.001.
  • V. L. Sivakumar, R. Radha Krishnappa, and M. Nallanathel, “Drought vulnerability assessment and mapping using Multi-Criteria decision making (MCDM) and application of Analytic Hierarchy process (AHP) for Namakkal District, Tamilnadu, India,” Mater. Today Proc., vol. 43, pp. 1592–1599, 2020, doi: 10.1016/j.matpr.2020.09.657.
There are 49 citations in total.

Details

Primary Language English
Subjects Photogrammetry and Remote Sensing, Geographical Information Systems (GIS) in Planning
Journal Section Research Article
Authors

Osman Orhan 0000-0002-1362-8206

Mehmet Özgür Çelik 0000-0003-4569-888X

Nagihan Karataş Taşci 0009-0006-7143-8423

Submission Date March 19, 2025
Acceptance Date July 18, 2025
Publication Date December 1, 2025
Published in Issue Year 2025 Volume: 13 Issue: 4

Cite

IEEE O. Orhan, M. Ö. Çelik, and N. Karataş Taşci, “IDENTIFY SUITABLE AREAS FOR PEANUT CULTIVATION IN OSMANIYE PROVINCE THROUGH THE AHP METHOD”, KONJES, vol. 13, no. 4, pp. 1063–1082, 2025, doi: 10.36306/konjes.1661112.