Sakız Ağacı Dikimi için Uygun Alanların Coğrafi Bilgi Teknolojileri ile Belirlenmesi: Çeşme Örneği
Özet
With the growing population, the effective use of resources has become increasingly important, making the implementation of accurate policies essential for urban studies. This study aims to present an open-source, reproducible, and accessible method that evaluates multiple criteria based on expert opinions to determine suitable planting areas for mastic trees.
In this context, Geographic Information Systems (GIS) and the Analytical Hierarchy Process (AHP), a Multi-Criteria Decision-Making (MCDM) method, were utilized together. To ensure reproducibility, an AHP plugin was developed using the open-source GIS software QGIS. Open-access datasets, freely available to all users, were preferred in the study. Additionally, a second dataset obtained from various public institutions was used to compare the impact of different datasets on the results.
The suitability maps were created based on the internationally recognized suitability classes of the Food and Agriculture Organization (FAO): S1 (Highly suitable), S2 (Suitable), S3 (Marginally suitable), and N (Not suitable). This classification system aims to standardize analysis results and enable comparisons on an international level.
A total of 12 criteria influencing the suitability of planting areas for mastic trees were analyzed under the categories of climate characteristics, topographic features, soil properties, and accessibility. An area of 61.66 km², including urban settlements, highways, and lakes, where mastic tree planting is not feasible, was excluded from the analyses to achieve more accurate results. The analyses were conducted in the selected study area, a 280 km² area within the boundaries of Çeşme district. A comparison between the suitability classes derived from open-access datasets and those obtained from public institutions revealed differences of 15.7% for S1, 11.2% for S2, and 4.8% for N. These discrepancies were attributed to the lower precision of open-access data. It was observed that 68.37% of the results from the two datasets are aligned.
The GIS-based AHP plugin developed in this study was designed as a flexible tool that can be used not only for determining planting locations for mastic trees but also for various other planning applications. Thanks to its flexibility, the plugin offers potential applications in agriculture, urban development, natural resource management, and environmental planning. This flexibility, combined with its open-source structure, makes the plugin a valuable tool for a broad range of users while allowing for continuous improvement and enhancement.
