Minimizing soil moisture variations in multi-temporal airborne imaging spectrometer data for digital soil mapping

After minimizing the effect of soil moisture variability, the airborne spectrometer data better approximate the reference dry-soil spectra (up to 21.3%). Then, the corrected data were tested for soil properties prediction (soil organic matter (SOM), sand silt and clay). The soil moisture corrected spectra performed marginally better for SOM (RMSE from 3.13 to 3.10) and silt (RMSE from 5.74 to 5.72), although not for clay (RMSE from 9.14 to 9.33) and sand (RMSE from 5.98 to 6.31). The methodology shows that field spectra can be corrected to better match laboratory conditions, focusing on soil moisture as main varying factor. Next step should include the various types of soil surface variation and their interactions. A better understanding of these interactions is needed and can be achieved by field-scale experiments and by modelling the different processes.