Establishing and verifying soil quality index model based on GIS and remote sensing for cultivated lands under semi-humid terrestrial ecosystem

Sustainable and efficient use of agricultural land depends on the potential characteristics of the soil. This potential directly affects the phenological growth and development of the crop to be grown. For these reasons, soil quality studies are of great importance in determining the products to be grown and the sustainability of the agriculture to be carried out. In this study, carried out in the Engiz Basin, a semi-humid terrestrial ecosystem of the Black Sea region, 250 soil samples were sampled from agricultural areas throughout the basin and a total of 26 soil physical, chemical and biological criteria were measured. Using Geographic Information Systems, Remote Sensing, Fuzzy-Analytical Hierarchy Process and Standard Scoring Function, soil quality models were constructed according to the obtained soil criteria. In addition, principal component analysis was used to select a minimum data set of the most sensitive indicators. The main physical criterion has the highest weight value with 0.611. The weight values for the highest sub-criteria of each main criterion - physical, chemical, biological, and fertility - were determined as slope (0.226), organic matter (0.425), microbial biomass carbon (0.512), and nitrogen (0.245), respectively. Geostatistical models were also used to produce maps of the spatial distribution of soil quality index values for the study area. Moreover, satellite image analysis and field studies (such as; data was collected from a face-to-face survey conducted with 51 farmers) were carried out to verify the obtained SQI distribution maps. The highest r 2 values of 0.9004 were found between the SQI TDS-L model and NDVI biomass reflectance values. Furthermore, when analyzing the statistical relationship between soil quality classes and yield and economic values obtained from the field, the high r 2 value (0.8209) was determined.