Use of Spectral Data From on-the-go Multispectral Cameras to Monitor Soil Surface Moisture: The Partial Least-Square Regression for Data Mining, Analysis, and Prediction
This study highlighted several important issues that illustrate the potential of the spectra to hold information useful for the management. In addition, these findings demonstrate that by using partial least-square regression for data mining, it is possible to isolate regions of the NIR spectra that pose relevant information for prediction of soil moisture. Several regions of wavelengths were found that allow developing a simple index to assess the soil water content status. Therefore, several important and useful tasks could be performed with spectral reflectance that could contribute substantially with the irrigation management in daily operations.