Deep Learning Application for Predicting Soil Organic Matter Content by VIS-NIR Spectroscopy

Combining Fractional Order Derivative and Spectral Variable Selection for Organic Matter Estimation of Homogeneous Soil Samples by VIS–NIR Spectroscopy

(2018) Yongsheng Hong et al.   Remote Sensing

Quantitative analysis of soil nutrition based on FT-NIR spectroscopy integrated with BP neural deep learning

(2018) Huazhou Chen et al.   Analytical Methods

A combination strategy of random forest and back propagation network for variable selection in spectral calibration

(2018) Huazhou Chen et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

rs-local data-mines information from spectral libraries to improve local calibrations

(2017) C. R. Lobsey et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Biochemically altered charcoal residues as an important source of soil organic matter in subsoils of fire-affected subtropical regions

(2016) Marta Velasco-Molina et al.   GEODERMA

Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy

(2016) Said Nawar et al.   SOIL & TILLAGE RESEARCH

Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis-NIR spectral library

(2015) Z. Shi et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Deep learning

(2015) Yann LeCun et al.   NATURE

Development of a national VNIR soil-spectral library for soil classification and prediction of organic matter concentrations

(2014) Zhou Shi et al.   Science China-Earth Sciences

VIS-NIR reflectance spectroscopy of the organic matter in several types of soils

(2012) Wen-Jun JI et al.   JOURNAL OF INFRARED AND MILLIMETER WAVES