Evaluation of Land Suitability for Olive (Olea europaea L.) Cultivation Using the Random Forest Algorithm

Many large dams built on the coruh River have resulted in the inundation of olive groves in Artvin Province, Turkey. This research sets out to identify suitable locations for olive cultivation in Artvin using the random forest (RF) algorithm. A total of 575 plots currently listed in the Farmer Registration System, where olive cultivation is practiced, were used as inventory data in the training and validation of the RF model. In order to determine the areas where olive cultivation can be carried out, a land suitability map was created by taking into account 10 parameters including the average annual temperature, average annual precipitation, slope, aspect, land use capability class, land use capability sub-class, soil depth, other soil properties, solar radiation, and land cover. According to this map, an area of 53,994.57 hectares was detected as suitable for olive production within the study region. To validate the created model, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) were utilized. As a result, the AUC value was determined to be 0.978, indicating that the RF method may be successfully used in determining suitable lands for olive cultivation in particular, as well as crop-based land suitability research in general.

Automated summary

This research uses the random forest algorithm to create a land suitability map for olive cultivation in Artvin Province, Turkey. By considering 10 parameters including temperature, precipitation, slope, aspect, land use capability, soil properties, solar radiation, and land cover, an area of 53,994.57 hectares suitable for olive production was identified. The validation of the model indicates that the random forest method can successfully determine suitable lands for olive cultivation.