My research on Machine Learning, Chemometrics and Spectroscopy

Here are some of my research publications

Schmidinger, Jonas, Sebastian Vogel, Viacheslav Barkov, et al. 2025. “LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping.” Geoderma 459: 117337. https://doi.org/10.1016/j.geoderma.2025.117337.

Summerauer, Laura, Fernando Bamba, Bendicto Akoraebirungi, et al. 2025. “Rapid Soil Degradation Following Deforestation in Eastern Africa.” EGUsphere 2025: 1–52. https://doi.org/10.5194/egusphere-2025-4625.

Wadoux, Alexandre MJ-C, and Leonardo Ramirez-Lopez. 2025. “Uncertainty of Predictions in Absorption Spectroscopy: Modelling with Quantile Regression Forest.” Chemometrics and Intelligent Laboratory Systems, 105473. https://doi.org/10.1016/j.chemolab.2025.105473.

Wadoux, A, L Ramirez-Lopez, Y Ge, I Barra, and Y Peng. 2025. A Course on Applied Data Analytics for Soil Analysis with Infrared Spectroscopy. https://openknowledge.fao.org/items/8bc82bdb-a140-490b-adae-1a2870c20347.

Rossel, Raphael A Viscarra, Zefang Shen, Leonardo Ramirez Lopez, et al. 2024. “An Imperative for Soil Spectroscopic Modelling Is to Think Global but Fit Local with Transfer Learning.” Earth-Science Reviews 254: 104797. https://doi.org/10.1016/j.earscirev.2024.104797.

Summerauer, Laura, Fernando Bamba, Bendicto Akoraebirungi, et al. 2024. “Parent Material Modulated Effects of Soil Degradation on Fertility and Organic Carbon of Tropical Cropland Soils in Eastern Africa.” EGUsphere, EGU24–15313. https://doi.org/10.5194/egusphere-egu24-15313.

Behrens, Thorsten, Raphael A Viscarra Rossel, Leonardo Ramirez-Lopez, and Philipp Baumann. 2022. “Soil Spectroscopy with the Gaussian Pyramid Scale Space.” Geoderma 426: 116095. https://doi.org/10.1016/j.geoderma.2022.116095.

Shen, Zefang, Leonardo Ramirez-Lopez, Thorsten Behrens, et al. 2022. “Deep Transfer Learning of Global Spectra for Local Soil Carbon Monitoring.” ISPRS Journal of Photogrammetry and Remote Sensing 188: 190–200.

Viscarra Rossel, Raphael A, Thorsten Behrens, Eyal Ben-Dor, et al. 2022. “Diffuse Reflectance Spectroscopy for Estimating Soil Properties: A Technology for the 21st Century.” European Journal of Soil Science 73 (4): e13271. https://doi.org/10.1016/j.isprsjprs.2022.04.009.

Summerauer, L, P Baumann, L Ramirez-Lopez, et al. 2021. The Central African Soil Spectral Library: A New Soil Infrared Repository and a Geographical Prediction Analysis. SOIL 7 (2), 693–715. https://doi.org/10.5194/soil-7-693-2021.

Dı́az Rangel, César Augusto, Nathalia Marı́a Forero Cabrera Forero Cabrera, Leonardo Ramı́rez López Ramı́rez López, Alexis González Dı́az, and Carlos Alberto Fernández Botı́a. 2020. NIR Technology for Palm Oil Mills: Optimization of Quality Results of Oils and by-Products to Take Strategic Decisions During Fruit Processing. https://repositorio.fedepalma.org/handle/123456789/145363.

Stevens, A, and L Ramirez-Lopez. 2020. An Introduction to the Prospectr Package (r Package Vignette r Package Version 0.2. 0). Comprehensive R Archive Network. https://cran. rproject. org/web/packages ….

Stevens, A, L Ramirez-Lopez, and LR Lopez. 2020. Package “Prospectr”: Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data. https://cran.r-project.org/web/packages/prospectr/vignettes/prospectr.html.

Dangal, S, J Sanderman, S Wills, and L Ramirez-Lopez. 2019. Accurate and Precise Prediction of Soil Properties from a Large Mid-Infrared Spectral Library, Soil Systems, 3, 11. https://doi.org/10.3390/soilsystems3010011.

Jaconi, Angelica, Christopher Poeplau, L Ramirez-Lopez, B Van Wesemael, and Axel Don. 2019. “Log-Ratio Transformation Is the Key to Determining Soil Organic Carbon Fractions with Near-Infrared Spectroscopy.” European Journal of Soil Science 70 (1): 127–39. https://doi.org/10.1111/ejss.12761.

Ramirez-Lopez, Leonardo, AMJ-C Wadoux, Marston HD Franceschini, et al. 2019. “Robust Soil Mapping at the Farm Scale with Vis–NIR Spectroscopy.” European Journal of Soil Science 70 (2): 378–93. https://doi.org/10.1111/ejss.12752.

VASQUES, G de M, JAM DEMATTÊ, RA VISCARRA ROSSEL, FS RAMÍREZ-LÓPEZ, FS TERRA, and R RIZZO. 2019. Enhancing Digital Soil Mapping in Southeastern Brazil: Incorporating Stream Density and Soil Reflectance from Multiple Depths.

Jaconi, A, C Poeplau, L Ramirez-Lopez, Bas van Wesemael, and A Don. 2018. “Log-Ratio Transformation Is the Key to Determining Soil Organic Carbon Fractions with Near-Infrared Spectroscopy: Determining SOC Fractions Using NIRS.” European Journal of Soil Science 70: 127. https://doi.org/10.1111/ejss.12761.

Demattê, José AM, L Ramirez-Lopez, Karina Patricia Prazeres Marques, and Arnaldo Antonio Rodella. 2017. “Chemometric Soil Analysis on the Determination of Specific Bands for the Detection of Magnesium and Potassium by Spectroscopy.” Geoderma 288: 8–22. https://doi.org/10.1016/j.geoderma.2016.11.013.

Demattê, José AM, Julianne de Castro Oliveira, Tiago Rodrigues Tavares, et al. 2016. “Soil Chemical Alteration Due to Slaughterhouse Waste Application as Identified by Spectral Reflectance in são Paulo State, Brazil: An Environmental Monitoring Useful Tool.” Environmental Earth Sciences 75 (18): 1277. https://doi.org/10.1007/s12665-016-6042-2.

Demattê, José AM, Leonardo Ramirez-Lopez, Rodnei Rizzo, et al. 2016. “Remote Sensing from Ground to Space Platforms Associated with Terrain Attributes as a Hybrid Strategy on the Development of a Pedological Map.” Remote Sensing 8 (10): 826. https://doi.org/10.3390/rs8100826.

Ramirez-Lopez, Leonardo, Antoine Stevens, R Viscarra Rossel, C Lobsez, A Wadoux, and T Breure. 2016. “Resemble: Regression and Similarity Evaluation for Memory-Based Learning in Spectral Chemometrics.” R Package Version 1 (2). https://cran.r-project.org/web/packages/resemble/vignettes/resemble.html.

Rossel, RA Viscarra, T Behrens, E Ben-Dor, et al. 2016. “A Global Spectral Library to Characterize the World’s Soil.” Earth-Science Reviews 155: 198–230. https://doi.org/10.1016/j.earscirev.2016.01.012.

Walthert, L, M Scherler, M Stähli, et al. 2016. Böden Und Wasserhaushalt von wäldern Und Waldstandorten Der Schweiz Unter Heutigem Und Zukünftigem Klima (BOWA-CH). ETH-Zürich. https://www.research-collection.ethz.ch/entities/publication/9f12502d-6ed0-47d6-878a-e40bfc2ada39.

Nocita, Marco, Antoine Stevens, Bas van Wesemael, et al. 2015. “Soil Spectroscopy: An Alternative to Wet Chemistry for Soil Monitoring.” Advances in Agronomy 132: 139–59. https://doi.org/10.1016/bs.agron.2015.02.002.

Stevens, Antoine, Leonardo Ramirez-Lopez, Maintainer Antoine Stevens, and LinkingTo Rcpp. 2015. “Package ‘Prospectr’.” In Package “Prospectr.” https://cran.r-project.org/web/packages/prospectr/vignettes/prospectr.html.

Vasques, Gustavo M, José AM Demattê, Raphael A Viscarra Rossel, et al. 2015. “Integrating Geospatial and Multi-Depth Laboratory Spectral Data for Mapping Soil Classes in a Geologically Complex Area in Southeastern b Razil.” European Journal of Soil Science 66 (4): 767–79. https://doi.org/10.1111/ejss.12255.

Wesemael, Bas van, Antoine Stevens, Carole Noon, et al. 2015. Soil Spectroscopy: An Alternative to Wet Chemistry for Soil Monitoring. https://doi.org/10.1016/bs.agron.2015.02.002.

Behrens, Thorsten, Karsten Schmidt, Leonardo Ramirez-Lopez, John Gallant, A-Xing Zhu, and Thomas Scholten. 2014. “Hyper-Scale Digital Soil Mapping and Soil Formation Analysis.” Geoderma 213: 578–88. https://doi.org/10.1016/j.geoderma.2013.07.031.

Ramirez-Lopez, Leonardo, Karsten Schmidt, Thorsten Behrens, Bas Van Wesemael, Jose AM Demattê, and Thomas Scholten. 2014. “Sampling Optimal Calibration Sets in Soil Infrared Spectroscopy.” Geoderma 226: 140–50. https://doi.org/10.1016/j.geoderma.2014.02.002.

Ramirez-Lopez, L, and A Stevens. 2014. “Pre-Processing, Sampling and Modelling (Soil) Vis-IR Data Using the ‘Prospectr’ and ‘Resemble’ Packages.” Pedometron 34: 9–14.

Ramı́rez López, Leonardo, Andreas Jürg Papritz, Madlene Nussbaum, Lorenz Walthert, and Andri Baltensweiler. 2014. “Modeling Soil Density in Swiss Forests: From Pedotransfer Functions to High-Resolution Digital Maps.” Digital Soil Mapping Workshop.

Schmidt, K, Thorsten Behrens, J Daumann, et al. 2014. “A Comparison of Calibration Sampling Schemes at the Field Scale.” Geoderma 232: 243–56. https://doi.org/10.1016/j.geoderma.2014.05.013.

Stevens, Antoine, and Leonardo Ramirez-Lopez. 2014. An Introduction to the Prospectr Package. February. https://cran.r-project.org/web/packages/prospectr/vignettes/prospectr.html.

Vasques, GM, José Alexandre Melo Demattê, Raphael A Viscarra Rossel, L Ramirez-Lopez, and FS Terra. 2014. “Soil Classification Using Visible/Near-Infrared Diffuse Reflectance Spectra from Multiple Depths.” Geoderma 223: 73–78. https://doi.org/10.1016/j.geoderma.2014.01.019.

Ramirez-Lopez, Leonardo. 2013. “Sampling Design and Machine Learning Optimization for the Application of Soil Sensing Data in Digital Soil Mapping.” PhD thesis, Dissertation, Tübingen, Universität Tübingen, 2013.

Ramirez-Lopez, Leonardo, Thorsten Behrens, Karsten Schmidt, Antoine Stevens, Jose Alexandre M Demattê, and Thomas Scholten. 2013. “The Spectrum-Based Learner: A New Local Approach for Modeling Soil Vis–NIR Spectra of Complex Datasets.” Geoderma 195: 268–79. https://doi.org/10.1016/j.geoderma.2012.12.014.

Ramirez-Lopez, Leonardo, T Behrens, K Schmidt, RA Viscarra Rossel, José Alexandre Melo Demattê, and T Scholten. 2013. “Distance and Similarity-Search Metrics for Use with Soil Vis–NIR Spectra.” Geoderma 199: 43–53. https://doi.org/10.1016/j.geoderma.2012.08.035.