Vis-NIR Spectroscopy Combined with GAN Data Augmentation for Predicting Soil Nutrients in Degraded Alpine Meadows on the Qinghai-Tibet Plateau.

ABSTRACT: Soil nutrients play vital roles in vegetation growth and are a key indicator of land degradation. Accurate, rapid, and non-destructive measurement of the soil nutrient content is important for ecological conservation, degradation monitoring, and precision farming. Currently, visible and near-infrared (Vis-NIR) spectroscopy allows for rapid and non-destructive monitoring of soil nutrients. However, the performance of Vis-NIR inversion models is extremely dependent on the number of samples. Limited samples may lead to low prediction accuracy of the models. Therefore, modeling and prediction based on a small sample size remain a challenge. This study proposes a method for the simultaneous augmentation of soil spectral and nutrient data (total nitrogen (TN), soil organic matter (SOM), total po

SUBMITTER: Jiang C 

PROVIDER: S-EPMC10098562 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature