Research Article
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Real estate assessment of agricultural lands outside the zoning plan with artificial neural networks and multiple regression analysis methods: The case of Aksaray, Bahçesaray and Kırımlı rural districts

Year 2023, Volume: 4 Issue: 1, 1 - 12, 24.10.2023

Kamil Karataş Hakan Karaduman

https://doi.org/10.48053/turkgeo.1213142

Abstract

This study aims to determine the market value of the agricultural lands in the rural Bahçesaray and Kirimli districts, which are outside the zoning plan, where agricultural production continues in Aksaray Province, Central District, in Turkey, by mass valuation methods. It is also aims to provide value estimation and value map production with the help of geographic information systems (GIS). Using the sales data from 125 parcels in the study area, the market value of the real estates for which the value is unknown in the region, was estimated. The most frequently used criteria in the assessment of agricultural lands were determined, and the valuation was carried out with Multiple Regression Analysis (MRA) and Artificial Neural Networks (ANN). By means of the assessment and the valuation study, the performance of the valuation methods was compared, and it was determined that the best result according to the test data was the valuation with ANN. In the performance analysis conducted with ANN, the Coefficient of Determination (R²)=0.87, Mean Absolute Percentage Error (MAPE)=0.192, Mean Absolute Error (MAE)=0.047 and Root Mean Square Error (RMSE)=0.059 was found. Moreover, according to the proportional standards guide determined by the International Association of Assessing Officers (IAAO), the performance measurement, the values derived for the Coefficient of Dispersion as (COD)=19.58 and Price-Related Differential as (PRD)=1.02 were also found to be within acceptable limits. Since the valuation of agricultural lands is a less studied subject, there are few articles in the literature. For this reason, it will be useful to increase such as article and evaluate the results applying it region by region. In this study, estimates were found with MRA and ANN methods and value maps were created.

Keywords

Agricultural land Land valuation ANN MRA GIS

References

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  • Bilgilioğlu, S.S. (2018). Development of spatial decision support systems with machine learning techniques: Case of Aksaray province (PhD thesis). Aksaray University, Aksaray, Turkey (in Turkish).
  • Choumert, J., & Phélinas, P. (2015). Determinants of agricultural land values in Argentina. Ecological Economics, 110, 134-140.
  • Cupal, M. (2014). The Comparative approach theory for real estate valuation. Procedia-Social and Behavioral Sciences, 109, 19-23.
  • Çınar, G., Altınok, A.C, Özcan, H., & Aslan, F. (2018) Aydın ilinde tarımsal arazi değerini etkileyen faktörlerin hedonik fiyatlandırma modeli ile tahmin edilmesi. Ahtamara 1. Uluslararası Multidisipliner Çalışmalar Kongresi, 25-26 Ağustos 2018, 58-67.
  • Çoșar, G.Ö., & Engindeniz, S. (2013). Hedonic analysis of agricultural land values: the case of Menemen, Izmir. Ege Üniversitesi Ziraat Fakültesi Dergisi, 50(3), 241-250.
  • Doğrama, E. (2020). Present land use situation and sustainable management of balikesir plain lands (MSc thesis). Uludağ University, Bursa, Turkey (in Turkish).
  • Erdem, N. (2016). An approach for Turkish real estate valuation system (PhD thesis). Erciyes University, Kayseri, Turkey (in Turkish).
  • Ertas, M. (2014). Using bare valuation method in valuation of rural area. In FIG Congress.
  • Bilal, E.R., Kurugöllü, S., & Ünel, F.B. (2022). Tarım arazilerinin yapay sinir ağları ve çoklu lineer regresyon analizi ile toplu taşınmaz değerlemesi: Mersin, Mezitli-Bozön mahallesi örneği. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 4(1), 5-14.
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  • Han, G., Sönmez, E.F., Avcı, S., & Aladağ, Z. (2022). Uygun normalizasyon tekniği ve yapay sinir ağları analizi ile otomobil satış tahminlemesi. İşletme Ekonomi ve Yönetim Araştırmaları Dergisi, 5(1), 19-45.
  • IAAO, (2013). International Association of Assessing Officers, Standard on Ratio Studies. Retrieved 23 December 2022 from https://www.iaao.org/media/standards/Standard_on_Ratio_Studies.pdf
  • İban M.C. (2021). Taşınmaz mal değeri kestiriminde topluluk algoritmalarının doğruluk analizi. 1. Uluslararası Yapay Zeka ve Veri Bilimi Kongresi, İzmir.
  • İlhan, A.T. (2019). Investigation of applicability of artificial neural networks on mass valuation of real estates: The case of Gölbaşi district (MSc thesis). Ankara University, Ankara, Turkey (in Turkish).
  • Karakayacı, Z. (2011). Using geographic information systems in agricultural land valuation: The case of Konya province Çumra, (PhD thesis). Selçuk University, Konya, Turkey (in Turkish).
  • Küsek, G. (2014). Arazi toplulaştırmasının parsel şekli ve tarımsal mekanizasyon uygulamalarına etkileri: Konya-Ereğli-Acıkuyu ve Özgürler Köyleri örnekleri. Çukurova Üniversitesi, Ziraat Fakültesi Dergisi, 29(2),1-4.
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  • Koç, M. (2011). Econometric analysis of factors affecting farmland prices: A case study in Keskin district of Kirikkale province (PhD thesis). Ankara University, Ankara, Turkey (in Turkish).
  • Lehn, F., & Bahrs, E. (2018). Analysis of factors influencing standard farmland values with regard to stronger interventions in the German farmland market. Land Use Policy, 73, 138-146.
  • Garcia-Melon, M., Ferris-Onate, J., Aznar-Bellver, J., Aragonés-Beltran, P., & Poveda-Bautista, R. (2008). Farmland appraisal based on the analytic network process. Journal of Global Optimization, 42, 143-155.
  • Odabaşı, G. (2020). Examination of real estate valuation methods and application areas in Turkey (MSc thesis). Gebze Technical University, Kocaeli, Turkey (in Turkish).
  • Özdemir, O. (2019) Investigation of the judicial decisions and the compliance with the legislation in the implementation of the imports in agriculture (MSc thesis). Zonguldak Bülent Ecevit University, Zonguldak, Turkey (in Turkish).
  • Öztürk, K., & Şahin, M.E. (2018). Yapay sinir ağları ve yapay zekâ’ya genel bir bakış. Takvim-i Vekayi, 6(2), 25-36.
  • Selçuk, S.A., Sorguç, A.G., & Akan, A.E. (2009). Altın oranla tasarlamak: doğada, mimarlıkta ve yapısal tasarımda Φ dizini. Trakya Üniversitesi Fen Bilimleri Dergisi, 10(2), 149-157.
  • Soni, A.K., & Sadiq, A.A. (2015). Real estate valuatıon usıng artıfıcıal neural network (AAN). International Journal of Science, Technology & Management, 4, 99-105
  • Ünel, F.B. (2017). Development of geography data model for criteria of real estate valuation (PhD thesis). Selçuk University, Konya, Turkey (in Turkish).
  • Yalpır, Ş. (2007). he development and application of a real-estate valuation model with fuzzy logic methodology: Konya case study (PhD thesis). Selçuk University, Konya, Turkey (in Turkish).
  • Yiğit, F. (2019). Valuation of agricultural lands in urban sprawl by using hedonic price modelling (MSc thesis). Selçuk Üniversitesi, Konya, Turkey (in Turkish).
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  • Url-4: https://www.usgs.gov (last accessed 11 December 2022)

Year 2023, Volume: 4 Issue: 1, 1 - 12, 24.10.2023

Kamil Karataş Hakan Karaduman

https://doi.org/10.48053/turkgeo.1213142

Abstract

References

  • Akın, Y., Çelen, B., Çelen, M.F., & Karagöz, A. (2016) Tarım ve Pandemi: Covid-19 sonrası Türk tarımı nasıl değişmeli? EJONS International Journal on Mathematic, Engineering and Natural Sciences, 16, 904-916
  • Başer, U. (2015). Factors affecting land prices in Ladik district of Samsun province (MSc thesis). Ondokuz Mayıs University, Samsun, Turkey (in Turkish).
  • Bilgilioğlu, S.S. (2018). Development of spatial decision support systems with machine learning techniques: Case of Aksaray province (PhD thesis). Aksaray University, Aksaray, Turkey (in Turkish).
  • Choumert, J., & Phélinas, P. (2015). Determinants of agricultural land values in Argentina. Ecological Economics, 110, 134-140.
  • Cupal, M. (2014). The Comparative approach theory for real estate valuation. Procedia-Social and Behavioral Sciences, 109, 19-23.
  • Çınar, G., Altınok, A.C, Özcan, H., & Aslan, F. (2018) Aydın ilinde tarımsal arazi değerini etkileyen faktörlerin hedonik fiyatlandırma modeli ile tahmin edilmesi. Ahtamara 1. Uluslararası Multidisipliner Çalışmalar Kongresi, 25-26 Ağustos 2018, 58-67.
  • Çoșar, G.Ö., & Engindeniz, S. (2013). Hedonic analysis of agricultural land values: the case of Menemen, Izmir. Ege Üniversitesi Ziraat Fakültesi Dergisi, 50(3), 241-250.
  • Doğrama, E. (2020). Present land use situation and sustainable management of balikesir plain lands (MSc thesis). Uludağ University, Bursa, Turkey (in Turkish).
  • Erdem, N. (2016). An approach for Turkish real estate valuation system (PhD thesis). Erciyes University, Kayseri, Turkey (in Turkish).
  • Ertas, M. (2014). Using bare valuation method in valuation of rural area. In FIG Congress.
  • Bilal, E.R., Kurugöllü, S., & Ünel, F.B. (2022). Tarım arazilerinin yapay sinir ağları ve çoklu lineer regresyon analizi ile toplu taşınmaz değerlemesi: Mersin, Mezitli-Bozön mahallesi örneği. Türkiye Coğrafi Bilgi Sistemleri Dergisi, 4(1), 5-14.
  • Ge, B., Ishaku, M.M., & Lewu, H.I. (2021). Research on the effect of artificial intelligence real estate forecasting using multiple regression analysis and artificial neural network: a case study of Ghana. Journal of Computer and Communications, 9(10), 1-14.
  • Han, G., Sönmez, E.F., Avcı, S., & Aladağ, Z. (2022). Uygun normalizasyon tekniği ve yapay sinir ağları analizi ile otomobil satış tahminlemesi. İşletme Ekonomi ve Yönetim Araştırmaları Dergisi, 5(1), 19-45.
  • IAAO, (2013). International Association of Assessing Officers, Standard on Ratio Studies. Retrieved 23 December 2022 from https://www.iaao.org/media/standards/Standard_on_Ratio_Studies.pdf
  • İban M.C. (2021). Taşınmaz mal değeri kestiriminde topluluk algoritmalarının doğruluk analizi. 1. Uluslararası Yapay Zeka ve Veri Bilimi Kongresi, İzmir.
  • İlhan, A.T. (2019). Investigation of applicability of artificial neural networks on mass valuation of real estates: The case of Gölbaşi district (MSc thesis). Ankara University, Ankara, Turkey (in Turkish).
  • Karakayacı, Z. (2011). Using geographic information systems in agricultural land valuation: The case of Konya province Çumra, (PhD thesis). Selçuk University, Konya, Turkey (in Turkish).
  • Küsek, G. (2014). Arazi toplulaştırmasının parsel şekli ve tarımsal mekanizasyon uygulamalarına etkileri: Konya-Ereğli-Acıkuyu ve Özgürler Köyleri örnekleri. Çukurova Üniversitesi, Ziraat Fakültesi Dergisi, 29(2),1-4.
  • Kontrimas, V., & Verikas, A. (2011). The mass appraisal of the real estate by computational intelligence. Applied Soft Computing, 11(1), 443-448.
  • Koç, M. (2011). Econometric analysis of factors affecting farmland prices: A case study in Keskin district of Kirikkale province (PhD thesis). Ankara University, Ankara, Turkey (in Turkish).
  • Lehn, F., & Bahrs, E. (2018). Analysis of factors influencing standard farmland values with regard to stronger interventions in the German farmland market. Land Use Policy, 73, 138-146.
  • Garcia-Melon, M., Ferris-Onate, J., Aznar-Bellver, J., Aragonés-Beltran, P., & Poveda-Bautista, R. (2008). Farmland appraisal based on the analytic network process. Journal of Global Optimization, 42, 143-155.
  • Odabaşı, G. (2020). Examination of real estate valuation methods and application areas in Turkey (MSc thesis). Gebze Technical University, Kocaeli, Turkey (in Turkish).
  • Özdemir, O. (2019) Investigation of the judicial decisions and the compliance with the legislation in the implementation of the imports in agriculture (MSc thesis). Zonguldak Bülent Ecevit University, Zonguldak, Turkey (in Turkish).
  • Öztürk, K., & Şahin, M.E. (2018). Yapay sinir ağları ve yapay zekâ’ya genel bir bakış. Takvim-i Vekayi, 6(2), 25-36.
  • Selçuk, S.A., Sorguç, A.G., & Akan, A.E. (2009). Altın oranla tasarlamak: doğada, mimarlıkta ve yapısal tasarımda Φ dizini. Trakya Üniversitesi Fen Bilimleri Dergisi, 10(2), 149-157.
  • Soni, A.K., & Sadiq, A.A. (2015). Real estate valuatıon usıng artıfıcıal neural network (AAN). International Journal of Science, Technology & Management, 4, 99-105
  • Ünel, F.B. (2017). Development of geography data model for criteria of real estate valuation (PhD thesis). Selçuk University, Konya, Turkey (in Turkish).
  • Yalpır, Ş. (2007). he development and application of a real-estate valuation model with fuzzy logic methodology: Konya case study (PhD thesis). Selçuk University, Konya, Turkey (in Turkish).
  • Yiğit, F. (2019). Valuation of agricultural lands in urban sprawl by using hedonic price modelling (MSc thesis). Selçuk Üniversitesi, Konya, Turkey (in Turkish).
  • Url-1: https://slideplayer.com/slide/5939205/ (last accessed 23 October 2022)
  • Url-2: https://www.kgm.gov.tr/Sayfalar/KGM/SiteTr/Uzakliklar/illerArasiMesafe.asp (last accessed 23 October 2022)
  • Url-3: https://www.harita.gov.tr/il-ve-ilce-yuzolcumleri (last accessed 20 October 2022)
  • Url-4: https://www.usgs.gov (last accessed 11 December 2022)
There are 34 citations in total.

Details

Primary Language English
Subjects Geological Sciences and Engineering (Other)
Journal Section Research Articles
Authors

Kamil Karataş 0000-0001-5174-7153

Hakan Karaduman 0000-0003-1808-9501

Publication Date October 24, 2023
Submission Date December 1, 2022
Acceptance Date January 14, 2023
Published in Issue Year 2023 Volume: 4 Issue: 1

Cite

APA Karataş, K., & Karaduman, H. (2023). Real estate assessment of agricultural lands outside the zoning plan with artificial neural networks and multiple regression analysis methods: The case of Aksaray, Bahçesaray and Kırımlı rural districts. Turkish Journal of Geosciences, 4(1), 1-12. https://doi.org/10.48053/turkgeo.1213142
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