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Zhao, T., Zhang, X., Gao, Y., Mi, J., Liu, W., Wang, J. et al. (2023). Assessing the Accuracy and Consistency of Six Fine-Resolution Global Land Cover Products Using a Novel Stratified Random Sampling Validation Dataset. Remote Sensing, 15, Article 2285.
https://doi.org/10.3390/rs15092285

has been cited by the following article:

• TITLE: Modeling Soil Erodibility Based on Silt Content: A Predictive Equation Proposal for Soils of Sorocaba (SP), Brazil

  AUTHORS: Sandra Mauren Ell, Lucas Hubacek Tsuchiya, Alexandre Marco Da Silva

  KEYWORDS: Erodibility, Silt, Pedotransfer Functions, Soil Degradation, Predictive Modeling

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.13 No.9, September 26, 2025

  ABSTRACT: Soil erodibility is a fundamental property associated with its susceptibility to particle detachment and transport by erosive agents such as water, wind, or anthropogenic disturbances. Its quantification is essential to support conservation management, land-use planning, and modeling of environmental degradation processes. However, direct laboratory determination of erodibility can be costly and time-consuming, limiting its application in regional studies. This study aimed to develop a pedotransfer function (PTF) to estimate soil erodibility based on the silt fraction, using data from 65 sampling points distributed across the municipality of Sorocaba (SP), Brazil. Samples underwent granulometric characterization, and erodibility values were estimated following the parameters of the EPIC model, which considers intrinsic soil variables such as texture and organic carbon content, derived from the Universal Soil Loss Equation (USLE). The relationship between silt content and erodibility was analyzed through simple linear regression, resulting in a statistically significant model (R2 = 83%, p