2021
DOI: 10.1080/10106049.2021.1996639
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Spatial prediction of soil surface properties in an arid region using synthetic soil image and machine learning

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Cited by 37 publications
(6 citation statements)
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References 93 publications
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“…Based on the variables importance results, the most important variables in the RF-OK prediction model for soil texture fractions were included B5, MSAVI and elevation. Our results are in line with the results of previous studies, which reported that RS data such as different bands and elevation variable were the most important predictors to predict soil texture fractions (Shahriari et al 2019, Naimi et al 2021. Topography factor and elevation variation play an important role in prediction of soil texture fractions by influencing soil erosion and sedimentation process.…”
supporting
confidence: 92%
“…Based on the variables importance results, the most important variables in the RF-OK prediction model for soil texture fractions were included B5, MSAVI and elevation. Our results are in line with the results of previous studies, which reported that RS data such as different bands and elevation variable were the most important predictors to predict soil texture fractions (Shahriari et al 2019, Naimi et al 2021. Topography factor and elevation variation play an important role in prediction of soil texture fractions by influencing soil erosion and sedimentation process.…”
supporting
confidence: 92%
“…Nas publicac ¸ões onde foram aplicadas técnicas de regressão, a maioria dos trabalhos utiliza, além das variáveis ambientais (ex. : textura, rugosidade, vegetac ¸ão, etc), dados de sensoriamento remoto, demostrando que a combinac ¸ão destes dados produz resultados promissores, com um aumento considerável na acurácia e economia de tempo e custo de pesquisa [Matinfar et al 2021, Rostaminia et al 2021, Naimi et al 2021.…”
Section: Análise E Discussõesunclassified
“…On the other hand, few studies account for the accuracy assessment of predicted maps in digital soil mapping [32]. Previous studies have generally focused on the predictions of soil properties at regional [42][43][44][45][46] or within a single field scale [47,48] rather than heterogeneous clustered fields.…”
Section: Introductionmentioning
confidence: 99%