SOIL MOISTURE PREDICTION WITH MULTISPECTRAL VISIBLE AND NIR REMOTE SENSING

9 citations as recorded by crossref.

1. Relationships between Soil Moisture and Visible–NIR Soil Reflectance: A Review Presenting New Analyses and Data to Fill the Gaps S. McGuirk & I. Cairns https://doi.org/10.3390/geotechnics4010005
2. Recognizing and reducing effects of moisture-salt coexistence on soil organic matter spectral prediction：From laboratory to satellite D. Wang et al. https://doi.org/10.1016/j.still.2024.106397
3. Analysis of Hotspots and Trends in Soil Moisture Research since the 21st Century Y. Cai et al. https://doi.org/10.3390/atmos14101494
4. Prediction of soil moisture content using genetic algorithm-optimized backpropagation algorithm from spectral data J. Wang et al. https://doi.org/10.1007/s11368-024-03868-w
5. Effects of Sample Handling on Visible and Near-Infrared Soil Reflectance S. McGuirk et al. https://doi.org/10.1177/27551857241266855
6. Estimation of soil free Iron content using spectral reflectance and machine learning algorithms W. Ma et al. https://doi.org/10.1038/s41598-025-09301-7
7. Evaluating the impact of soil moisture variation on the performance of visible and near-infrared (Vis–NIR) spectroscopy for predicting soil organic carbon content A. Xie & W. Wu https://doi.org/10.1007/s10661-025-14726-8
8. UAV Monitoring Topsoil Moisture in an Alpine Meadow on the Qinghai–Tibet Plateau Y. Sang et al. https://doi.org/10.3390/agronomy13092193
9. Review: Application and research progress of near infrared spectroscopy for multidimensional assessment of coffee beans T. Li et al. https://doi.org/10.1177/09670335241291178