Marco Nocita

TL;DR: In this article, the authors developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library, which is currently the largest and most diverse database of its kind, and showed that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability.

TL;DR: In this article, the authors describe the state of the art of soil spectroscopy as well as its potential to facilitate soil monitoring, and highlight that the widespread use of spectroscopes to monitor the status of the soil should be encouraged by the creation of a standard for the collection of laboratory soil spectra, to promote the sharing of spectral libraries, and to scan existing soil archives.

TL;DR: This study is a first step towards providing uniform continental-scale spectroscopic estimations of soil organic carbon, meeting an increasing demand for information on the state of the soil that can be used in biogeochemical models and the monitoring of soil degradation.

TL;DR: In this article, the authors proposed a method to determine soil organic carbon (SOC) content for moist samples with unknown moisture content using a normalized soil moisture index (NSMI) to estimate the soil moisture content of the samples.

TL;DR: In this article, a local partial least square regression approach was used to predict organic carbon (SOC) content of topsoil samples collected from 19,969 topsoils collected all over the European Union and scanned with a Vis-NIR spectrometer.