| Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables T Hengl, M Nussbaum, MN Wright, GBM Heuvelink, B Gräler PeerJ 6, e5518, 2018 | 706 | 2018 |
| Evaluation of digital soil mapping approaches with large sets of environmental covariates M Nussbaum, K Spiess, A Baltensweiler, U Grob, A Keller, L Greiner, ... Soil 4 (1), 1-22, 2018 | 236 | 2018 |
| Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables, PeerJ, 6, e5518 T Hengl, M Nussbaum, MN Wright, GBM Heuvelink, B Gräler | 135 | 2018 |
| Mapping the geogenic radon potential for Germany by machine learning E Petermann, H Meyer, M Nussbaum, P Bossew Science of The Total Environment 754, 142291, 2021 | 53 | 2021 |
| Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging M Nussbaum, A Papritz, A Baltensweiler, L Walthert Geoscientific Model Development 7 (3), 1197-1210, 2014 | 52 | 2014 |
| Machine learning based soil maps for a wide range of soil properties for the forested area of Switzerland A Baltensweiler, L Walthert, M Hanewinkel, S Zimmermann, M Nussbaum Geoderma Regional 27, e00437, 2021 | 38 | 2021 |
| Assessment of soil multi-functionality to support the sustainable use of soil resources on the Swiss Plateau L Greiner, M Nussbaum, A Papritz, M Fraefel, S Zimmermann, P Schwab, ... Geoderma Regional 14, e00181, 2018 | 30 | 2018 |
| Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models M Nussbaum, L Walthert, M Fraefel, L Greiner, A Papritz Soil 3 (4), 191-210, 2017 | 28 | 2017 |
| Evaluation of the potential for soil organic carbon content monitoring with farmers C Deluz, M Nussbaum, O Sauzet, K Gondret, P Boivin Frontiers in Environmental Science 8, 113, 2020 | 27 | 2020 |
| Uncertainty indication in soil function maps–transparent and easy-to-use information to support sustainable use of soil resources L Greiner, M Nussbaum, A Papritz, S Zimmermann, A Gubler, ... Soil 4 (2), 123-139, 2018 | 26 | 2018 |
| Organic carbon stocks of swiss forest soils M Nussbaum, AJ Papritz, A Baltensweiler, L Walthert ETH Zurich, 2012 | 17 | 2012 |
| 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 Y Garosi, S Ayoubi, M Nussbaum, M Sheklabadi Geoderma Regional 29, e00513, 2022 | 15 | 2022 |
| The relevance of scale in soil maps M Nussbaum, L Ettlin, A Çöltekin, B Suter, M Egli Bulletin BGS 32, 63-70, 2011 | 15 | 2011 |
| Pedotransfer function to predict density of forest soils in Switzerland M Nussbaum, A Papritz, S Zimmermann, L Walthert Journal of Plant Nutrition and Soil Science 179 (3), 321-326, 2016 | 10 | 2016 |
| 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 Y Garosi, S Ayoubi, M Nussbaum, M Sheklabadi, M Nael, I Kimiaee International Journal of Remote Sensing 43 (18), 6856-6880, 2022 | 9 | 2022 |
| Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging, Geosci. Model Dev., 7, 1197–1210 M Nussbaum, A Papritz, A Baltensweiler, L Walthert | 9 | 2014 |
| Estimating soil organic carbon stocks of Swiss forest soils by robust external-drift kriging M Nussbaum, A Papritz, A Baltensweiler, L Walthert Geosci. Model Dev. Discuss 6, 7077-7116, 2013 | 6 | 2013 |
| geoGAM: Select Sparse Geoadditive Models for Spatial Prediction M Nussbaum, AJ Papritz ETH Zurich, 2017 | 5 | 2017 |
| Transferfunktionen Nährstoffmesswerte M Nussbaum, AJ Papritz ETH Zurich, 2015 | 4 | 2015 |
| Benefits of hierarchical predictions for digital soil mapping—An approach to map bimodal soil pH M Nussbaum, S Zimmermann, L Walthert, A Baltensweiler Geoderma 437, 116579, 2023 | 3 | 2023 |
