6 Prediction models on Open Soil Spectral Library

Abstract:

We have received important feedback since the release of the first models and web services (Dec. 2021). The feedback was that the previous model versions were doing a great job, but for others not that much. Variable model performance may have happened due to the specific soil types not being well represented or due to the spectra not being well aligned with the OSSL instruments. This led us to improve the current outputs to include a flag that indicates if the new samples to be predicted are represented by the calibration set. In addition to that, we revised our uncertainty estimation method by switching to conformal predictions, a simple and robust method for delivering uncertainty bands. In addition to that, we conducted a systematic analysis of learning algorithms, compression strategies, and preprocessing using the OSSL database and external test sets, and the insights from ring trial experiment / a separate project that was developed to understand the dissimilarity across multiple soil spectroscopy laboratories.