Please also find a list of publications at Google Scholar. Four most important publications are marked with two asterisk **.

Peer-reviewed articles

Baltensweiler, A., Walthert, L., Hanewinkel, M., Zimmermann, S., and Nussbaum, M.: Machine learning based soil maps for a wide range of soil properties for the forested area of Switzerland, Geoderma Regional, 27, e00 437, doi:10.1016/j.geodrs.2021.e00437, 2021.

Deluz, C., Nussbaum, M., Sauzet, O., Gondret, K., and Boivin, P.: Evaluation of the Potential for Soil Organic Carbon Content Monitoring With Farmers, Frontiers in Environmental Science, 8, doi:10.3389/fenvs.2020.00113, 2020.

Garosi, Y., Ayoubi, S., Nussbaum, M., and Sheklabadi, M.: Effects of different sources and spatial resolutions of environmental covariates on predicting soil organic carbon using machine learning in a semi-arid region of Iran, Geoderma Regional, 29, e00 513, doi:10.1016/j.geodrs.2022.e00513, 2022a.

Garosi, Y., Ayoubi, S., Nussbaum, M., Sheklabadi, M., Nael, M., and Kimiaee, I.: Use of the time series and multi-temporal features of Sentinel-1/2 satellite imagery to predict soil inorganic and organic carbon in a low-relief area with a semi-arid environment, International Journal of Remote Sensing, 43, 6856–6880, doi:10.1080/01431161.2022.2147037, 2022b.

Greiner, L., Nussbaum, M., Papritz, A., Fraefel, M., Zimmermann, S., Schwab, P., Grêt-Regamey, A., and Keller, A.: Assessment of soil multi-functionality to support the sustainable use of soil resources on the Swiss Plateau, Geoderma Regional, 14, e00 181, doi:10.1016/j.geodrs.2018.e00181, 2018a.

Greiner, L., Nussbaum, M., Papritz, A., Zimmermann, S., Gubler, A., Grêt-Regamey, A., and Keller, A.: Uncertainty indication in soil function maps – transparent and easy-to-use information to support sustainable use of soil resources, SOIL, 4, 123–139, doi:10.5194/soil-4-123-2018, 2018b.

** Hengl, T., Nussbaum, M., Wright, M. N., Heuvelink, G. B. M., and Gräler, B.: Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables, PeerJ, 6, e5518, doi:10.7717/peerj.5518, 2018.

Herholz, C., Siegwart, J., Nussbaum, M., Studer, M. H.-P., Burgos, S.: Large temporal variations of functional properties of outdoor equestrian arena surfaces and a new concept of evaluating reactivity with light weight deflectometer settlement curves. Journal of Equine Veterinary Science, 104909, doi: 10.1016/j.jevs.2023.104909, 2023.

Nussbaum, M., Papritz, A., Baltensweiler, A., and Walthert, L.: Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging, Geoscientific Model Development, 7, 1197–1210, doi:10.5194/gmd-7-1197-2014, 2014.

Nussbaum, M., Papritz, A., Zimmerman, S., and Walthert, L.: Pedotransfer function to predict density of forest soils in Switzerland, Journal of Plant Nutrition and Soil Science, 179, 321–326, doi:10.1002/jpln.201500546, 2016.

Nussbaum, M., Walthert, L., Fraefel, M., Greiner, L., and Papritz, A.: Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models, SOIL, 3, 191–210, doi:10.5194/soil-3-191-2017, 2017.

** Nussbaum, M., Zimmermann, S., Walthert, L., Baltensweiler, A.:  Benefits of hierarchical predictions for digital soil mapping -- An approach to map bimodal soil pH,  Geoderma,
Volume 437/116579, doi: 10.1016/j.geoderma.2023.116579, 2023.

** Nussbaum, M., Spiess, K., Baltensweiler, A., Grob, U., Keller, A., Greiner, L., Schaepman, M. E., and Papritz, A.: Evaluation of digital soil mapping approaches with large sets of environmental covariates, SOIL, 4, 1–22, doi:10.5194/soil-4-1-2018, 2018.

Petermann, E., Meyer, H., Nussbaum, M., and Bossew, P.: Mapping the geogenic radon potential for Germany by machine learning, Science of the Total Environment, 754, 142 291, doi:10.1016/j.scitotenv.2020.142291, 2021.

Theses and book chapters

Nussbaum, M.: Modelling of organic carbon content and stocks for forest soils in Switzerland (in German), Master Thesis, University of Zurich, Institute for Geography, Zürich, doi:10.3929/ethz-a-006785593, 2011.

Nussbaum, M.: Preliminary study to assess the impact of the soil promotion program of the Canton of Berne, by analysing the cantonal soil monitoring Berne (in German), diploma thesis for Diploma of Advanced Studies in Applied Statistics, Institute of Mathematical Statistics and Actuarial Science, University of Berne, 2014.

Nussbaum, M.: Digital Soil Mapping for Switzerland, Evaluation of Statistical Approaches and Mapping of Soil Properties, Ph.D. thesis, ETH Zurich, Zurich, Switzerland, doi:10.3929/ethz-b-000193154, 2017.

** Nussbaum, M.: Machine Learning and Processing of Large Data in Soil Science. Invited contribution, in: Encyclopedia of Soils in the Environment, Elsevier, Oxford, doi:10.1016/B978-0-12-822974-3.00065-3, 2022.

Applied research reports (selection)

Baltensweiler, A., Walthert, L., Zimmermann, S., and Nussbaum, M.: High resolution soil maps for Swiss forest soils (in German), Schweizerische Zeitschrift fur Forstwesen, 173, 288–291, doi:10.3188/szf.2022.0288, 2022.

Nussbaum, M. and Burgos, S.: Pedotransferfunctions to predict potential cation exchange capacity from laboratory methods FAC to AAE (in German), project report to the client Soil Protection Agency of Canton of Zurich, BFH, 2017.

Nussbaum, M. and Burgos, S.: Concept to survey detailed soil information for the complete Canton of Berne, technical report (in German), project report to the client Canton of Berne, BFH, 2019.

Nussbaum, M. and Papritz, A.: Validation of conventional soil maps with independent soil data – general approach and case study, unpublished article manuscript, 2017.

Nussbaum, M., Ettlin, L., Cöltekin, A., Suter, B., and Egli, M.: The Relevance of Scale in Soil Maps, Bulletin BGS, 32, 63–70, 2011.

Nussbaum, M., Burgos, S., Keller, A., Carrizoni, M., and Papritz, A.: Soil information systems and (digital) soil mapping in Europe. What can Switzerland learn from this? (in German), report, BFH and ETH Zurich, 2018.

Oechslin, S., Nussbaum, M., and Burgos, S.: Soil mapping St. Rheintal, final report to the client Verein St. Galler Rheintal (in German), project report to the Canton of St. Gallen, BFH, 2020.