Yazar "Alaboz, Pelin" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    Different approaches to estimating soil properties for digital soil map integrated with machine learning and remote sensing techniques in a sub-humid ecosystem
    (Springer, 2023) Saygin, Fikret; Aksoy, Hasan; Alaboz, Pelin; Dengiz, Orhan
    Today, data mining has become a relevant topic in digital soil mapping. In this current study, prediction of some soil properties and their spatial distribution were examined by machine learning algorithms (Support Vector Machine, Artificial Neural Network) using reflectance values of Triplesat satellite image bands in Vezirkopru district of Samsun province. The band data obtained from different wavelengths revealed positive correlations between the electrical conductivity and calcium carbonate equivalent contents of the soils. The support vector machine algorithm was the most successful to estimate the textural fractions, organic matter, electrical conductivity, and calcium carbonate equivalent contents of the soils using the bands obtained from satellite images. The mean absolute error for estimating sand, silt, and clay contents by support vector machine was 4.05%, 3.05%, and 3.66%, respectively. Texture classes were determined with an accuracy of 82% with support vector machine and 60% with artificial neural network. In all estimations, the highest percentage of error was for calcium carbonate equivalent content with very low estimation reliability. The mean absolute percentage of error values for this property are 101.13% and 51.61% for artificial neural network and support vector machine, respectively. Also, in both algorithms, the most successfully estimated soil property was clay fraction of soils. It was also investigated the spatial distribution of actual and estimated values using various interpolation methods (Kriging, inverse distance weighting-, radial basis function). Considering the spatial distributions, it was determined that the most successful method was kriging for sand, silt, and clay contents and inverse distance weighting for electrical conductivity, calcium carbonate equivalent, and organic matter contents. According to our findings, it is concluded that successful estimations and spatial distributions can be made by the support vector machine algorithm using band data from different wavelengths.
  • [ X ]
    Öğe
    Evaluation of the relationship between indices obtained from different satellite data and soil erosion parameters
    (Ege Universitesi, 2023) Saygin, Fikret; Alaboz, Pelin; Aksoy, Hasan; Dengiz, Orhan; Imamoǧlu, Ali; Çaǧlar, Aykut; Koç, Yusuf
    Objective: The relationship between the indices and reflectances obtained by using different satellite images (Triplesat, Landsat 8), and soil erosion parameters (erosion rate, dispersion rate, structure stability, clay ratio, aggregate stability, and soil crust index) within the boundaries of Vezirköprü district of Samsun province. is to be revealed. Material and Methods: It was carried out in three stages: analyzing soil erosion sensitivity on a total of 32 soil samples taken at 100 x 100 m grid intervals from the study area, obtaining indices and reflectances of Triplesat and Landsat satellite images, and comparing the analysis results with the indices of satellite images." Results: The correlations between the reflectance values obtained from the Red, Green and Blue bands of the Landsat satellite data and the erosion rate were determined to be higher than the reflectances of the Triplesat satellite. No significant correlations were obtained between the aggregate stability and crust ratio properties of the soils and the indices. Higher positive correlations were determined between erosion rate and dispersion rate and indices. Conclusion: It has been seen that the aggregate stability (AS) contents of the soils are in a higher relationship with the indices obtained from Triplesat satellite images, and the erosion rate is higher with the indices obtained from Landsat satellite images. © 2023 The Author(s).