Cargando…
Machine-learning-based quantitative estimation of soil organic carbon content by VIS/NIR spectroscopy
Soil organic carbon (SOC) is an important soil property that has profound impact on soil quality and plant growth. With 140 soil samples collected from Ebinur Lake Wetland National Nature Reserve, Xinjiang Uyghur Autonomous Region of China, this research evaluated the feasibility of visible/near inf...
Autores principales: | Ding, Jianli, Yang, Aixia, Wang, Jingzhe, Sagan, Vasit, Yu, Danlin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6195798/ https://www.ncbi.nlm.nih.gov/pubmed/30357023 http://dx.doi.org/10.7717/peerj.5714 |
Ejemplares similares
-
Combining UAV-based hyperspectral imagery and machine learning algorithms for soil moisture content monitoring
por: Ge, Xiangyu, et al.
Publicado: (2019) -
Quantitative estimation of soil salinity by means of different modeling methods and visible-near infrared (VIS–NIR) spectroscopy, Ebinur Lake Wetland, Northwest China
por: Wang, Jingzhe, et al.
Publicado: (2018) -
Comparison of Soil Total Nitrogen Content Prediction Models Based on Vis-NIR Spectroscopy
por: Wang, Yueting, et al.
Publicado: (2020) -
Prediction of soil organic carbon in a coal mining area by Vis-NIR spectroscopy
por: Sun, Wenjuan, et al.
Publicado: (2018) -
Effects of field-grown transgenic switchgrass carbon inputs on soil organic carbon cycling
por: Xu, Sutie, et al.
Publicado: (2019)