Related references
Note: Only part of the references are listed.Improving spectral estimation of soil inorganic carbon in urban and suburban areas by coupling continuous wavelet transform with geographical stratification
Yongsheng Hong et al.
GEODERMA (2023)
Using carbonate absorbance peak to select the most suitable regression model before predicting soil inorganic carbon concentration by mid-infrared reflectance spectroscopy
Cecile Gomez et al.
GEODERMA (2022)
Assessing toxic metal chromium in the soil in coal mining areas via proximal sensing: Prerequisites for land rehabilitation and sustainable development
Jingzhe Wang et al.
GEODERMA (2022)
Digital mapping of GlobalSoilMap soil properties at a broad scale: A review
Songchao Chen et al.
GEODERMA (2022)
The Brazilian soil Mid-infrared Spectral Library: The Power of the Fundamental Range
Wanderson de Sousa Mendes et al.
GEODERMA (2022)
Deep transfer learning of global spectra for local soil carbon monitoring
Zefang Shen et al.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2022)
Using soil library hyperspectral reflectance and machine learning to predict soil organic carbon: Assessing potential of airborne and spaceborne optical soil sensing
Sheng Wang et al.
REMOTE SENSING OF ENVIRONMENT (2022)
Fusion of visible-to-near-infrared and mid-infrared spectroscopy to estimate soil organic carbon
Yongsheng Hong et al.
SOIL & TILLAGE RESEARCH (2022)
Global Soil Salinity Prediction by Open Soil Vis-NIR Spectral Library
Yin Zhou et al.
REMOTE SENSING (2022)
Data mining of urban soil spectral library for estimating organic carbon
Yongsheng Hong et al.
GEODERMA (2022)
An advanced soil organic carbon content prediction model via fused temporal-spatial-spectral (TSS) information based on machine learning and deep learning algorithms
Xiangtian Meng et al.
REMOTE SENSING OF ENVIRONMENT (2022)
African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning
Tomislav Hengl et al.
SCIENTIFIC REPORTS (2021)
Sentinel-2 Exposed Soil Composite for Soil Organic Carbon Prediction
Klara Dvorakova et al.
REMOTE SENSING (2021)
Environmental covariates improve the spectral predictions of organic carbon in subtropical soils in southern Brazil
Jean Michel Moura-Bueno et al.
GEODERMA (2021)
The central African soil spectral library: a new soil infrared repository and a geographical prediction analysis
Laura Summerauer et al.
SOIL (2021)
Developing the Swiss mid-infrared soil spectral library for local estimation and monitoring
Philipp Baumann et al.
SOIL (2021)
Mid-infrared spectroscopy for prediction of soil health indicators in the United States
Jonathan Sanderman et al.
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL (2020)
Exploring the potential of airborne hyperspectral image for estimating topsoil organic carbon: Effects of fractional-order derivative and optimal band combination algorithm
Yongsheng Hong et al.
GEODERMA (2020)
Simultaneous prediction of soil properties from VNIR-SWIR spectra using a localized multi-channel 1-D convolutional neural network
Nikolaos L. Tsakiridis et al.
GEODERMA (2020)
Is Standardization Necessary for Sharing of a Large Mid-Infrared Soil Spectral Library?
Shree R. S. Dangal et al.
SENSORS (2020)
The influence of training sample size on the accuracy of deep learning models for the prediction of soil properties with near-infrared spectroscopy data
Wartini Ng et al.
SOIL (2020)
Combination of fractional order derivative and memory-based learning algorithm to improve the estimation accuracy of soil organic matter by visible and near-infrared spectroscopy
Yongsheng Hong et al.
CATENA (2019)
Application of fractional-order derivative in the quantitative estimation of soil organic matter content through visible and near-infrared spectroscopy
Yongsheng Hong et al.
GEODERMA (2019)
Predicting the decomposability of arctic tundra soil organic matter with mid infrared spectroscopy
Roser Matamala et al.
SOIL BIOLOGY & BIOCHEMISTRY (2019)
Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra
Wartini Ng et al.
GEODERMA (2019)
The Brazilian Soil Spectral Library (BSSL): A general view, application and challenges
Jose A. M. Dematte et al.
GEODERMA (2019)
Soil organic carbon storage as a key function of soils - A review of drivers and indicators at various scales
Martin Wiesmeier et al.
GEODERMA (2019)
Application of Mid-Infrared Spectroscopy in Soil Survey
Cathy A. Seybold et al.
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL (2019)
Using deep learning to predict soil properties from regional spectral data
J. Padarian et al.
GEODERMA REGIONAL (2019)
Accurate and Precise Prediction of Soil Properties from a Large Mid-Infrared Spectral Library
Shree R. S. Dangal et al.
SOIL SYSTEMS (2019)
Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration
Chenhao Cui et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2018)
A systematic study on the application of scatter-corrective and spectral-derivative preprocessing for multivariate prediction of soil organic carbon by Vis-NIR spectra
Andre Carnieletto Dotto et al.
GEODERMA (2018)
Present and future Koppen-Geiger climate classification maps at 1-km resolution
Hylke E. Beck et al.
SCIENTIFIC DATA (2018)
A global spectral library to characterize the world's soil
R. A. Viscarra Rossel et al.
EARTH-SCIENCE REVIEWS (2016)
Linking soils to ecosystem services - A global review
Kabindra Adhikari et al.
GEODERMA (2016)
Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy
Said Nawar et al.
SOIL & TILLAGE RESEARCH (2016)
Prediction of Soil Carbon in the Conterminous United States: Visible and Near Infrared Reflectance Spectroscopy Analysis of the Rapid Carbon Assessment Project
Nuwan K. Wijewardane et al.
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL (2016)
Prediction of soil organic matter using a spatially constrained local partial least squares regression and the Chinese vis-NIR spectral library
Z. Shi et al.
EUROPEAN JOURNAL OF SOIL SCIENCE (2015)
A fractional calculus on arbitrary time scales: Fractional differentiation and fractional integration
Nadia Benkhettou et al.
SIGNAL PROCESSING (2015)
The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties
Jose M. Soriano-Disla et al.
APPLIED SPECTROSCOPY REVIEWS (2014)
Visible and near-infrared reflectance spectroscopy-An alternative for monitoring soil contamination by heavy metals
Tiezhu Shi et al.
JOURNAL OF HAZARDOUS MATERIALS (2014)
Prediction of soil organic carbon content by diffuse reflectance spectroscopy using a local partial least square regression approach
Marco Nocita et al.
SOIL BIOLOGY & BIOCHEMISTRY (2014)
Predicting contents of carbon and its component fractions in Australian soils from diffuse reflectance mid-infrared spectra
J. A. Baldock et al.
SOIL RESEARCH (2013)
Calibration of visible and near infrared spectroscopy for soil analysis at the field scale on three European farms
B. Kuang et al.
EUROPEAN JOURNAL OF SOIL SCIENCE (2011)
Prediction of Soil Fertility Properties from a Globally Distributed Soil Mid-Infrared Spectral Library
Thomas Terhoeven-Urselmans et al.
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL (2010)
Regional transferability of mid-infrared diffuse reflectance spectroscopic prediction for soil chemical properties
Budiman Minasny et al.
GEODERMA (2009)
Review of the most common pre-processing techniques for near-infrared spectra
Asmund Rinnan et al.
TRAC-TRENDS IN ANALYTICAL CHEMISTRY (2009)
Regression rules as a tool for predicting soil properties from infrared reflectance spectroscopy
Budiman Minasny et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2008)
Spectral reflectance based indices for soil organic carbon quantification
H. M. Bartholomeus et al.
GEODERMA (2008)
The pls package: Principal component and partial least squares regression in R
Bjorn-Helge Mevik et al.
JOURNAL OF STATISTICAL SOFTWARE (2007)
Performance of some variable selection methods when multicollinearity is present
IG Chong et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2005)
A simple method to extract spectral parameters using fractional derivative spectrometry
SS Kharintsev et al.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY (2004)