Coğrafi bilgi sistemleri ile tarım arazilerinin değerlemesi: Aksaray örneği
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Tarih
2023
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Aksaray Üniversitesi Fen Bilimleri Enstitüsü
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Dünya nüfusundaki artış, iklim değişikliği, kuraklık vb. küresel sorunlarla birlikte gıdaya ve yerleşime olan ihtiyacın artmaktadır. Sürdürülebilir arazi yönetimine yönelik yapılacak çalışmalarda gerekli olan alanların üretilemeyen ve sınırlı bir kıt kaynak olan tarım arazilerinden karşılanıyor olması ülkeleri tarımsal arazilerinin korunmasına ve değerinin bilinmesi konusunda çalışmalar yapmaya ve kararlar almaya yöneltmiştir. Kamulaştırma, vergilendirme, sigortalama, alım-satım vb. amaçlarla tarım arazilerinin değerlemesinde en çok, geleneksel yöntemlerden olan gelir yöntemi kullanılmaktadır. Geniş alanlarda ise geleneksel yöntemlerden başka istatistiksel ve modern yöntemleri içeren toplu değerleme yöntemleriyle de taşınmaz değerlemesi yapılabilmektedir. Tez çalışması kapsamında, Aksaray İli Merkez İlçesini çevreleyen 22 Kasaba, Köy ve Mahalledeki tarım arazilerinin değerlemesinde, tarımsal arazilerinin değerine etki eden ana yola uzaklık, köy merkezine uzaklık, arazi sınıfı vb. 11 faktör kullanılmıştır. Yalın değerleme, Çoklu regresyon analizi ve yapay sinir ağları yöntemleri kullanılarak Coğrafi Bilgi sistemleri (CBS) ile değerleme yapılmıştır. Kullanılan değerleme yöntemleriyle tarım arazilerinin değer haritaları üretilerek yöntemler arasında karşılaştırmalar yapılmıştır. Piyasa değerine en çok yaklaşan ve performans analizinde en iyi sonucu veren yöntemlerin yapay sinir ağları ve yalın değerleme yöntemi olduğu görülmüştür. Tarım arazilerinin değerine en çok etki eden kriterlerin de sulama durumu ve ana yola, köy merkezine ve il merkezine olan uzaklıklarının olduğu belirlenmiştir.
Incidental to global problems such as the increase in the world population, climate change, drought, etc., the need for food and shelter is increasing. The fact that the areas required for the studies on sustainable land management are met from agricultural lands, which cannot be replenished and which are limited and scarce resources, has prompted countries to do scientific studies and take decisions regarding the protection and the valuation of agricultural lands. The income method, which is one of the conventional methods, is mostly used for the valuation of agricultural lands for expropriation, taxation, insurance, purchase, sale, and similar purposes. In large areas, real estate valuation can also be made using collective valuation methods that include statistical and modern methods other than conventional methods. Within the scope of the thesis study, 11 factors such as distance from the highway, distance from the village center, classification of the land, etc. which have an impact on the valuation of agricultural lands, were used for the valuation of agricultural lands in 22 Towns, Villages and Neighborhoods surrounding the Central District of Aksaray Province. The valuation was carried out with Geographic Information Systems (GIS) using bare valuation, multiple regression analysis, and artificial neural network methods. Comparisons were made between the methods by producing valuation maps of agricultural lands with the valuation methods used. It has been seen that the methods which correspond to the market value by far the most and give the best results during performance analysis are artificial neural networks and bare valuation methods. It has been determined that the criteria that most affect the value of agricultural lands are the irrigation status and the agricultural lands' distance from the highway, village center, and city center.
Incidental to global problems such as the increase in the world population, climate change, drought, etc., the need for food and shelter is increasing. The fact that the areas required for the studies on sustainable land management are met from agricultural lands, which cannot be replenished and which are limited and scarce resources, has prompted countries to do scientific studies and take decisions regarding the protection and the valuation of agricultural lands. The income method, which is one of the conventional methods, is mostly used for the valuation of agricultural lands for expropriation, taxation, insurance, purchase, sale, and similar purposes. In large areas, real estate valuation can also be made using collective valuation methods that include statistical and modern methods other than conventional methods. Within the scope of the thesis study, 11 factors such as distance from the highway, distance from the village center, classification of the land, etc. which have an impact on the valuation of agricultural lands, were used for the valuation of agricultural lands in 22 Towns, Villages and Neighborhoods surrounding the Central District of Aksaray Province. The valuation was carried out with Geographic Information Systems (GIS) using bare valuation, multiple regression analysis, and artificial neural network methods. Comparisons were made between the methods by producing valuation maps of agricultural lands with the valuation methods used. It has been seen that the methods which correspond to the market value by far the most and give the best results during performance analysis are artificial neural networks and bare valuation methods. It has been determined that the criteria that most affect the value of agricultural lands are the irrigation status and the agricultural lands' distance from the highway, village center, and city center.
Açıklama
Anahtar Kelimeler
Tarım Arazisi, Değerleme, Kapitalizasyon, Yalın Değerleme Yöntemi, Çoklu Regresyon Analizi, Yapay Sinir Ağları, Agricultural Land, Valuation, Capitalization, Bare Valuation Method, Multiple Regression Analysis, Artificial neural Networks
