Deep transfer learning of global spectra for local soil carbon monitoring

Transfer Learning of a Deep Learning Model for Exploring Tourists’ Urban Image Using Geotagged Photos

(2021) Youngok Kang et al.   ISPRS International Journal of Geo-Information

Improving the predictions of soil properties from VNIR–SWIR spectra in an unlabeled region using semi-supervised and active learning

(2021) Nikolaos L. Tsakiridis et al.   GEODERMA

The cost‐effectiveness of reflectance spectroscopy for estimating soil organic carbon

(2021) Shuo Li et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Transfer learning to localise a continental soil vis-NIR calibration model

(2019) J. Padarian et al.   GEODERMA

Semantic segmentation of slums in satellite images using transfer learning on fully convolutional neural networks

(2019) Michael Wurm et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Quantifying carbon for agricultural soil management: from the current status toward a global soil information system

(2019) Keith Paustian et al.   Carbon Management

Strategies for the efficient estimation of soil organic carbon at the field scale with vis-NIR spectroscopy: Spectral libraries and spiking vs. local calibrations

(2019) Michael Seidel et al.   GEODERMA

The Brazilian Soil Spectral Library (BSSL): A general view, application and challenges

(2019) José A.M. Demattê et al.   GEODERMA

How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal

(2019) Pete Smith et al.   GLOBAL CHANGE BIOLOGY

Transferring deep learning models for cloud detection between Landsat-8 and Proba-V

(2019) Gonzalo Mateo-García et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Transfer Learning for Soil Spectroscopy Based on Convolutional Neural Networks and Its Application in Soil Clay Content Mapping Using Hyperspectral Imagery

(2018) Lanfa Liu et al.   SENSORS

Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands

(2018) Fabio Castaldi et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Soil bacterial abundance and diversity better explained and predicted with spectro-transfer functions

(2018) Yuanyuan Yang et al.   SOIL BIOLOGY & BIOCHEMISTRY

LUCAS Soil, the largest expandable soil dataset for Europe: a review

(2017) A. Orgiazzi et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

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

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

A global spectral library to characterize the world's soil

(2016) R.A. Viscarra Rossel et al.   EARTH-SCIENCE REVIEWS

National calibration of soil organic carbon concentration using diffuse infrared reflectance spectroscopy

(2016) Michaël Clairotte et al.   GEODERMA

Do we really need large spectral libraries for local scale SOC assessment with NIR spectroscopy?

(2016) César Guerrero et al.   SOIL & TILLAGE RESEARCH

Prediction of Soil Carbon in the Conterminous United States: Visible and Near Infrared Reflectance Spectroscopy Analysis of the Rapid Carbon Assessment Project

(2016) Nuwan K. Wijewardane et al.   SOIL SCIENCE SOCIETY OF AMERICA JOURNAL

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

The contentious nature of soil organic matter

(2015) Johannes Lehmann et al.   NATURE

Deep learning

(2015) Yann LeCun et al.   NATURE

Assessment of soil organic carbon at local scale with spiked NIR calibrations: effects of selection and extra-weighting on the spiking subset

(2014) C. Guerrero et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

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

The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties

(2013) José M. Soriano-Disla et al.   APPLIED SPECTROSCOPY REVIEWS

The spectrum-based learner: A new local approach for modeling soil vis–NIR spectra of complex datasets

(2013) Leonardo Ramirez-Lopez et al.   GEODERMA

Which strategy is best to predict soil properties of a local site from a national Vis–NIR database?

(2013) Fabien Gogé et al.   GEODERMA

Predicting Soil Organic Carbon at Field Scale Using a National Soil Spectral Library

(2013) Yi Peng et al.   JOURNAL OF NEAR INFRARED SPECTROSCOPY

Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy

(2013) Antoine Stevens et al.   PLoS One

Predicting soil properties from the Australian soil visible-near infrared spectroscopic database

(2012) R. A. Viscarra Rossel et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Optimization criteria in sample selection step of local regression for quantitative analysis of large soil NIRS database

(2011) F. Gogé et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Near-infrared spectroscopy for within-field soil characterization: small local calibrations compared with national libraries spiked with local samples

(2010) J. Wetterlind et al.   EUROPEAN JOURNAL OF SOIL SCIENCE

Engineering hybrid nanotube wires for high-power biofuel cellspace

(2010) Feng Gao et al.   Nature Communications

In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy

(2009) R.A. Viscarra Rossel et al.   GEODERMA

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Comparing local vs. global visible and near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) calibrations for the prediction of soil clay, organic C and inorganic C

(2008) Joel B. Sankey et al.   GEODERMA