Determination of the economic potential of stone fields using remote sensing and photogrammetry

This study examines the transformation of rocky areas in the Siverek district of Şanlıurfa into agricultural potential. The research involves the detection of rocky areas and their conversion into agricultural land using remote sensing and photogrammetry techniques. The methods used include Sentinel-2 satellite imagery and high-resolution aerial photographs. The rocky areas within the study site were analyzed using an object-based classification method. The research area covers approximately 2024 hectares, with 591.99 hectares identified as rocky regions. These areas were determined using Sentinel-2 satellite images and high-resolution orthophotos. The classification process was carried out with SVM, resulting in an overall accuracy of 82% and a Kappa coefficient of 0.76. According to the cost analysis, the cleaning cost of 1 decare of rocky land in 2021 was calculated as 1500 TL. In the same period, the annual net income from a cleaned decare used for wheat farming was 520 TL, with an amortization period of 2.8 years. Calculations for 2023 showed an annual net income of 2102 TL from the cleaned land, with an amortization period of 5.7 years. In 2024, calculations indicated an annual net income of 4313 TL from lentil farming, with an amortization period of 3.48 years. In conclusion, this study demonstrates the effectiveness of remote sensing and photogrammetry techniques in transforming rocky areas into agricultural potential and highlights their role in strategic decision-making for agricultural land evaluation. Today, food security and sustainable agriculture are of critical importance due to the increasing global population and decreasing agricultural lands. In this context, the study's findings emphasize the importance of efficiently using existing agricultural lands and provide significant information for identifying new agricultural areas that may be needed in the future.