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

Author

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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)

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.

Suggested Citation

  • Ayse Yavuz Ozalp & Halil Akinci, 2023. "Evaluation of Land Suitability for Olive ( Olea europaea L.) Cultivation Using the Random Forest Algorithm," Agriculture, MDPI, vol. 13(6), pages 1-22, June.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:6:p:1208-:d:1165779
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    References listed on IDEAS

    as
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