Soil total nitrogen inversion and interpretability analysis using vis-NIR spectroscopy and transfer learning

The use of Vis-NIR Spectroscopy for soil component inversion has increased, driven by its advantages in non-destructive, large-scale monitoring. However, it often faces challenges in model generalization. Transfer learning, leveraging large existing soil sample datasets, is considered an effective s...

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Principais autores:	Ping He, Yu Chen, Xingping Wen, Xiaohua Zhou, Zailin Chen, Zhongchang Sun, Xianfeng Cheng
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Taylor & Francis Group 2025-08-01
סדרה:	International Journal of Digital Earth
נושאים:	Soil total nitrogen Vis-NIR spectroscopy transfer learning spectral preprocessing ResNet model
גישה מקוונת:	https://www.tandfonline.com/doi/10.1080/17538947.2025.2528621
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