Articles | Volume 7, issue 2
https://doi.org/10.5194/soil-7-693-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-7-693-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
26 Oct 2021
Original research article |
| 26 Oct 2021
| 26 Oct 2021
The central African soil spectral library: a new soil infrared repository and a geographical prediction analysis
Laura Summerauer
CORRESPONDING AUTHOR
Department of Environmental Systems Science, ETH Zurich, Zurich Switzerland
Philipp Baumann
Department of Environmental Systems Science, ETH Zurich, Zurich Switzerland
Leonardo Ramirez-Lopez
Data Science Department, BUCHI Labortechnik AG, Flawil, Switzerland
Matti Barthel
Department of Environmental Systems Science, ETH Zurich, Zurich Switzerland
Marijn Bauters
Department of Green Chemistry and Technology, Ghent University, Ghent, Belgium
Department of Environment, Ghent University, Ghent, Belgium
Benjamin Bukombe
Institute of Geography, University of Augsburg, Augsburg, Germany
Mario Reichenbach
Institute of Geography, University of Augsburg, Augsburg, Germany
Pascal Boeckx
Department of Green Chemistry and Technology, Ghent University, Ghent, Belgium
Elizabeth Kearsley
Department of Environment, Ghent University, Ghent, Belgium
Kristof Van Oost
Earth and Life Institute, UCLouvain, Louvain-la-Neuve, Belgium
Bernard Vanlauwe
International Institute of Tropical Agriculture, Nairobi, Kenya
Dieudonné Chiragaga
International Institute of Tropical Agriculture, Bukavu, Democratic Republic of Congo
Aimé Bisimwa Heri-Kazi
Earth and Life Institute, UCLouvain, Louvain-la-Neuve, Belgium
Pieter Moonen
Department of Earth and Environmental Sciences, KU Leuven, Leuven, Belgium
Andrew Sila
World Agroforestry Centre, Nairobi, Kenya
Keith Shepherd
World Agroforestry Centre, Nairobi, Kenya
Basile Bazirake Mujinya
Department of General Agricultural Sciences, University of Lubumbashi, Lubumbashi, Democratic Republic of Congo
Eric Van Ranst
Department of Geology, Ghent University, Ghent, Belgium
Geert Baert
Department of Green Chemistry and Technology, Ghent University, Ghent, Belgium
Sebastian Doetterl
Department of Environmental Systems Science, ETH Zurich, Zurich Switzerland
Institute of Geography, University of Augsburg, Augsburg, Germany
Johan Six
Department of Environmental Systems Science, ETH Zurich, Zurich Switzerland
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- Monitoring Soil Copper in Urban Land Using Visibale and Near-Infrared Spectroscopy with Spatially Nearby Samples Y. Liu et al. 10.3390/s24175612
- Potential of globally distributed topsoil mid-infrared spectral library for organic carbon estimation Y. Hong et al. 10.1016/j.catena.2023.107628
- Can we use a mid-infrared fine-ground soil spectral library to predict non-fine-ground spectra? Y. Gamagedara et al. 10.1016/j.geoderma.2024.116799
- Quantifying soil properties relevant to soil organic carbon biogeochemical cycles by infrared spectroscopy: The importance of compositional data analysis P. Zhao et al. 10.1016/j.still.2023.105718
- Research Progress on Greenhouse Gas Emissions From Livestock in Sub-Saharan Africa Falls Short of National Inventory Ambitions M. Graham et al. 10.3389/fsoil.2022.927452
- Prediction of soil organic carbon fractions in tropical cropland using a regional visible and near-infrared spectral library and machine learning L. Dai et al. 10.1016/j.still.2024.106297
- An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter J. Safanelli et al. 10.1016/j.geoderma.2023.116724
- Diffuse reflectance mid-infrared spectroscopy is viable without fine milling J. Sanderman et al. 10.1016/j.soisec.2023.100104
- The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication J. Demattê et al. 10.3390/rs14030740
- Strategies for efficient estimation of soil organic content at the local scale based on a national spectral database H. Li et al. 10.1002/ldr.4223
- GLOBAL-LOCAL: A new approach for local predictions of soil organic carbon content using large soil spectral libraries M. St. Luce et al. 10.1016/j.geoderma.2022.116048
- Assessing the Role of Environmental Covariates and Pixel Size in Soil Property Prediction: A Comparative Study of Various Areas in Southwest Iran P. Khosravani et al. 10.3390/land13081309
- Optimised use of data fusion and memory‐based learning with an Austrian soil library for predictions with infrared data B. Ludwig et al. 10.1111/ejss.13394
- Relationships between geochemical properties and microbial nutrient acquisition in tropical forest and cropland soils L. Kidinda et al. 10.1016/j.apsoil.2022.104653
- Organic matter cycling along geochemical, geomorphic, and disturbance gradients in forest and cropland of the African Tropics – project TropSOC database version 1.0 S. Doetterl et al. 10.5194/essd-13-4133-2021
17 citations as recorded by crossref.
- Assessing the Information Potential of MIR Spectral Signatures for Prediction of Multiple Soil Properties Based on Data from the AfSIS Phase I Project S. Gruszczyński & W. Gruszczyński 10.3390/ijerph192215210
- Digital mapping to extrapolate the selected soil fertility attributes in calcareous soils of a semiarid region in Iran P. Khosravani et al. 10.1007/s11368-023-03548-1
- Using homosoils for quantitative extrapolation of soil mapping models A. Nenkam et al. 10.1111/ejss.13285
- Monitoring Soil Copper in Urban Land Using Visibale and Near-Infrared Spectroscopy with Spatially Nearby Samples Y. Liu et al. 10.3390/s24175612
- Potential of globally distributed topsoil mid-infrared spectral library for organic carbon estimation Y. Hong et al. 10.1016/j.catena.2023.107628
- Can we use a mid-infrared fine-ground soil spectral library to predict non-fine-ground spectra? Y. Gamagedara et al. 10.1016/j.geoderma.2024.116799
- Quantifying soil properties relevant to soil organic carbon biogeochemical cycles by infrared spectroscopy: The importance of compositional data analysis P. Zhao et al. 10.1016/j.still.2023.105718
- Research Progress on Greenhouse Gas Emissions From Livestock in Sub-Saharan Africa Falls Short of National Inventory Ambitions M. Graham et al. 10.3389/fsoil.2022.927452
- Prediction of soil organic carbon fractions in tropical cropland using a regional visible and near-infrared spectral library and machine learning L. Dai et al. 10.1016/j.still.2024.106297
- An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter J. Safanelli et al. 10.1016/j.geoderma.2023.116724
- Diffuse reflectance mid-infrared spectroscopy is viable without fine milling J. Sanderman et al. 10.1016/j.soisec.2023.100104
- The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication J. Demattê et al. 10.3390/rs14030740
- Strategies for efficient estimation of soil organic content at the local scale based on a national spectral database H. Li et al. 10.1002/ldr.4223
- GLOBAL-LOCAL: A new approach for local predictions of soil organic carbon content using large soil spectral libraries M. St. Luce et al. 10.1016/j.geoderma.2022.116048
- Assessing the Role of Environmental Covariates and Pixel Size in Soil Property Prediction: A Comparative Study of Various Areas in Southwest Iran P. Khosravani et al. 10.3390/land13081309
- Optimised use of data fusion and memory‐based learning with an Austrian soil library for predictions with infrared data B. Ludwig et al. 10.1111/ejss.13394
- Relationships between geochemical properties and microbial nutrient acquisition in tropical forest and cropland soils L. Kidinda et al. 10.1016/j.apsoil.2022.104653
Latest update: 18 Nov 2024
Short summary
We present a soil mid-infrared library with over 1800 samples from central Africa in order to facilitate soil analyses of this highly understudied yet critical area. Together with an existing continental library, we demonstrate a regional analysis and geographical extrapolation to predict total carbon and nitrogen. Our results show accurate predictions and highlight the value that the data contribute to existing libraries. Our library is openly available for public use and for expansion.
We present a soil mid-infrared library with over 1800 samples from central Africa in order to...
