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

Ayse Yavuz Ozalp () and Halil Akinci
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Ayse Yavuz Ozalp: Department of Geomatics Engineering, Faculty of Engineering, Artvin Coruh University, Artvin 08000, Turkey
Halil Akinci: Department of Geomatics Engineering, Faculty of Engineering, Artvin Coruh University, Artvin 08000, Turkey

Agriculture, 2023, vol. 13, issue 6, 1-22

Abstract: Many large dams built on the Çoruh 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.

Keywords: land suitability; olive cultivation; random forest; Artvin (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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