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Enhancing Soil Mapping with a Transfer Learning Approach Without External Data Inputs

https://doi.org/10.2139/ssrn.4679271
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Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran
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Combination of Convolutional Neural Networks and Recurrent Neural Networks for predicting soil properties using Vis–NIR spectroscopy
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Deep transfer learning of global spectra for local soil carbon monitoring
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Improved daily SMAP satellite soil moisture prediction over China using deep learning model with transfer learning
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Soil Organic Carbon Across Mexico and the Conterminous United States (1991–2010)
inferredcites →https://doi.org/10.1038/s41598-021-85639-yopenalex-extracted
African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning
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Applying statistical methods to map soil organic carbon of agricultural lands in northeastern coastal areas of China
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A global map of mangrove forest soil carbon at 30 m spatial resolution
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GANs-LSTM Model for Soil Temperature Estimation From Meteorological: A New Approach
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Distant Domain Transfer Learning for Medical Imaging
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A Cost-Sensitive Deep Learning-Based Approach for Network Traffic Classification
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rs‐local data‐mines information from spectral libraries to improve local calibrations
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Soil Carbon Sequestration Impacts on Global Climate Change and Food Security
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SoilGrids250m: Global gridded soil information based on machine learning
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Assessment of Carbon Stocks in the Topsoil Using Random Forest and Remote Sensing Images
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Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics
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Using deep learning for digital soil mapping
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