Valuation of agricultural lands by geographical information systems: The case of Aksaray

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.