2024
Viscarra Rossel, R.A., Zhang, M., Behrens, T., Webster, R (2024). A warming climate will make Australian soil a net emitter of atmospheric CO2. Nature npj Clim Atmos Sci 7, 79. https://doi.org/10.1038/s41612-024-00619-z
2022
Behrens, T., Viscarra Rossel, R. A., Ramirez-Lopez, L., Baumann, P.(2022): Soil spectroscopy with the Gaussian pyramid scale space. Geoderma 426(5):116095.
Viscarra Rossel, R. A., Behrens, T., Ben-Dor, E., Chabrillat, S., Demattê, J. A. M., Ge, Y., Gomez, C., Guerrero, C., Peng, Y., Ramirez-Lopez, L., Shi, Z., Stenberg, B., Webster, R., Winowiecki, L., Shen, Z., (2022): Diffuse reflectance spectroscopy for estimating soil properties: a technology for the 21st century. European Journal of Soil Science, e13271.
Rentschler, T., Bartelheim, M., Behrens, T. et al. (2022) Contextual spatial modelling in the horizontal and vertical domains. Sci Rep 12, 9496.
Viscarra Rossel, R., Yang, Y., Bissett, A., Behrens, T., Dixon, K., Nevil, P., Li, S. (2022): Environmental controls of soil fungal abundance and diversity in Australia’s diverse ecosystems. Soil Biology and Biochemistry, 170, 108694,
Shen, Z., Ramirez-Lopez, L., Behrens, T., Cui, L., Zhang, M., Walden, L., Wetterlind, J., Shi, Z., Sudduth, K., Baumann, P., Song, Y., Catambay, K., Viscarra Rossel, R. (2022): Deep transfer learning of global spectra for local soil carbon monitoring. Journal of Photogrammetry and Remote Sensing, 188.
Baumann, P., Lee, J., Behrens, T., Biswas, A., Six, J., McLachlan, G., Viscarra Rossel, R. A. (2022): Modelling soil water retention and water-holding capacity with visible–near-infrared spectra and machine learning. European Journal of Soil Science, 73( 2), e13220.
2021
Taghizadeh-Mehrjardi, R., Schmidt, K., Toomanian, N., Heung, B., Behrens, T., Mosavi, A., Band, S., Amirian-Chakan, A., Fathabadi, A., Scholten, T. (2021): Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models. Geoderma, 383, 114793.
2020
Behrens, T., Viscarra Rossel, R. A. (2020): On the interpretability of predictors in spatial data science: the information horizon. Scientific Reports 10: 16737.
Taghizadeh-Mehrjardi, R., Schmidt, K., Toomanian, N., Heung, B., Behrens, T., Mosavi, A., Band, S., Amirian, A., Fathabadi, A., Scholten, T. (2020): Improving the spatial prediction of soil salinity in arid regions using wavelet transformation and support vector regression models. Geoderma 383, 114793.
Rentschler, T., Werban, U., Ahner, M., Behrens, T., Gries, P., Scholten, T., Teuber, S., Schmidt, K. (2020): 3D mapping of soil organic carbon content and soil moisture with multiple geophysical sensors and machine learning. Vadose zone journal 19, 1.
Taghizadeh-Mehrjardi, R., Mahdianpari, M., Mohammadimanesh, F., Behrens, T., Toomanian, N., Scholten, T., Schmidt, K. (2020): Multi-task convolutional neural networks outperformed random forest for mapping soil particle size fractions in central Iran. Geoderma 376, 114552.
Taghizadeh-Mehrjardi, R., Schmidt, K., Amirian-Chakan, A., Rentschler, T., Zeraatpisheh, M., Sarmadian, F., Valavi, R., Davatgar, N., Behrens, T., Scholten, T. (2020): Improving the Spatial Prediction of Soil Organic Carbon Content in Two Contrasting Climatic Regions by Stacking Machine Learning Models and Rescanning Covariate Space. Remote Sensing 12, 1095.
2019
Behrens, T., MacMillan, R.A., Viscarra Rossel, R.A., Schmidt, K., Lee, J. (2019): Teleconnections in spatial modelling. Geoderma, Volume 354, 113854. doi: 10.1016/j.geoderma.2019.07.012
Behrens, T., Viscarra Rossel, R. A., Kerry, R., MacMillan, R., Schmidt, K., Lee, J., Scholten, T., Zhu, A-X. (2019): The relevant range of scales for multi-scale contextual spatial modelling. Scientific Reports. 9: 14800.
Taghizadeh-Mehrjardi, R., Schmidt, K., Eftekhari, K., Behrens, T., Jamshidi, M., Davatgaar, N., Toomanian, N., Scholten, T. (2019): Synthetic resampling strategies and machine learning for digital soil mapping in Iran. European Journal of Soil Science.
Rentschler, T., Gries, P., Behrens, T., Bruelheide, H., Kühn, P., Seitz, S., Shi, X., Trogisch, S., Scholten, T., Schmidt, K. (2019): Comparison of catchment scale 3D and 2.5D modelling of soil organic carbon stocks in Jiangxi Province, PR China. PLoS ONE 14(8): e0220881.
Viscarra Rossel, R., Lee, J., Behrens, T., Luo, Z., Baldock, J., Richards, A. (2019): Continental-scale soil carbon composition and vulnerability modulated by regional environmental controls. Nature Geoscience, 12, 547–552.
2018
Behrens, T., Schmidt, K., MacMillan, R.A., Viscarra Rossel, R. (2018): Multi-scale Digital Soil Mapping with deep learning. Scientific Reports 8: 15244.
Yang, Y, Viscarra Rossel, R.A., Li, S., Bissett, A., Lee, J., Shi, Z., Behrens, T., Court, L., (2018): Soil bacterial abundance and diversity better explained and predicted with spectro-transfer functions. Soil Biology & Biochemistry Vol. 129, pp. 29–38.
Huang, Y., Chen, Y., Castro-Izaguirre, N., Baruffol, M., Brezzi, M., Lang, A., Li, Y., Härdtle, W., von Oheimb, G., Yang, X., Liu, X., Pei, K., Both, S., Yang, B., Eichenberg, D., Assmann, T., Bauhus, J., Behrens, T., et al. (2018): Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science, Vol. 362, Issue 6410, pp. 80–83.
Behrens, T., Schmidt, K., Rossel, R.A., Gries, P., Scholten, T., MacMillan, R.A. (2018): Spatial modelling with Euclidean distance fields and machine learning. Eur J Soil Sci.69/5.
Hounkpatin, O.K.L., Schmidt, K., Stumpf, F., Forkuor, G., Behrens, T., Scholten, T., Amelung, W., Welp, G. (2018): Predicting reference soil groups using legacy data: a data pruning and Random Forest approach for tropical environment (Dano catchment, Burkina Faso). Scientific Reports 8:9959.
Teng H., Viscarra Rossel, R.A., Shi, Z., Behrens, T. (2018): Updating a national soil classification with spectroscopic predictions and digital soil mapping. Catena 164.
2017
Behrens, T., Schmidt, K., MacMillan, R.A., Viscarra Rossel, R.A. (2017): Multiscale contextual spatial modelling with the Gaussian scale space. Geoderma 310: 128–137.
Stumpf, F., Schmidt, K., Goebes, P., Behrens, T., Schönbrodt-Stitt, S., Wadoux, A., Xiang, W., Scholten, T. (2017): Uncertainty-guided sampling to improve digital soil maps. Catena 153, 30–38.
2016
Viscarra Rossel, R.A., Behrens, T., Ben-Dor, E., Brown, D.J., Dematte, J.A.M., Shepherd, K.D., Shi, Z., Stenberg, B., Stevens, A., Adamchuk, V., et al. (2016): A global spectral library to characterize the world’s soil. Earth-Sci. Rev. 2016, 155, 198–230.
Teng H., Viscarra Rossel, R.A., Shi, Z., Behrens, T., Chappell, A., Bui, E. (2016): Assimilating satellite imagery and visible–near infrared spectroscopy to model and map soil loss by water erosion in Australia. Environmental Modelling and Software 77:156–167.
Stumpf, F., Schmidt, K., Behrens, T., Schönbrodt-Stitt, S., Buzzo, G., Dumperth, C., Wadoux, A., Xiang, W., Scholten, T. (2016): Incorporating limited field operability and legacy soil samples in a Hypercube Sampling design for Digital Soil Mapping. J Plant Nutr Soil Sci 179, 499–509.
2015
Martini, E., Wollschläger, U., Kögler, S., Behrens, T., Dietrich, P., Reinstorf, F., Schmidt, K., Weiler, M., Werban, U., Zacharias, S. (2015): Spatial and temporal dynamics of hillslopescale soil moisture patterns: characteristic states and transition mechanisms. Vadose Zone Journal 14, 4.
Strehmel, A., Schönbrodt-Stitt, S., Buzzo, G., Dumperth, C., Stumpf F., Zimmermann, K., Bieger, K., Behrens, T., Schmidt, K., Bi, R., Rohn, J., Hill, J., Udelhoven, T., Wei, X., Shi, XZ., Cai, Q., Jiang, T., Fohrer, N., Scholten, T. (2015): Assessment of Geo-Hazards in a Rapidly Changing Landscape: The Three Gorges Reservoir Region in China. Environmental Earth Sciences, 74, 6, 4939–4960.
Zhu, A.-X., Liu, J., Du, F., Zhang, S., Qin, C.-Z., Burt, J., Behrens, T., Scholten, T. (2015): Predictive soil mapping with limited sample data. European Journal of Soil Science.
2014
Ramirez-Lopez, L., Schmidt, K., Behrens, T., van Wesemael, B., Dematte, J.A.M., Scholten, T. (2014): Sampling optimal calibration sets in soil infrared spectroscopy. Geoderma 226-227, 140–150.
Schmidt, K., Behrens, T., Daumann, J., Ramirez-Lopez, L., Werban, U., Dietrich, P., Scholten, T. (2014): A comparison of calibration sampling schemes at the field scale. Geoderma 232-234, 243–256.
Behrens, T., Schmidt, K., Ramirez-Lopez, L., Gallant, J., Zhu, A-X., Scholten, T. (2014): Hyper-scale digital soil mapping and soil formation analysis. Geoderma 213, 578–588.
2013
Schönbrodt, S., Behrens, T., Schmidt, K., Scholten, T. (2013): Degradation of cultivated bench terraces in the Three Gorges Area – field mapping and data mining. Ecological Indicators 34, 478–493.
Schönbrodt-Stitt, S., Bosch, A., Behrens, T., Hartmann, H., Shi, X., Scholten, T. (2013): Approximation und Spatial Regionalization of Rainfall Erosivity based on Sparse Data in a Mountainous Catchment of the Yangtze River in Central China. Environmental Science and Pollution Research 20, 10, 6917–6933.
Ramirez-Lopez, L., Behrens, T., Schmidt, K., Viscarra Rossel, R., Demattê, J.A.M., Scholten, T. (2013): Distance and similarity-search metrics for use with soil vis-NIR spectra. Geoderma 199, 43–53.
Ramirez-Lopez, L., Behrens, T., Schmidt, K., Stevens, A., Demattê, J.A.M., Scholten, T. (2013): The spectrum-based learner: a new local approach for modeling soil vis-NIR spectra. Geoderma 195, 268–279.
2011
Qin, C., Zhu, A-X., Pei, T., Li, B., Behrens, T., Scholten, T., Zhou, C. (2011): An approach to computing topographic wetness index based on maximum downslope gradient. Precision Agriculture 12, 32–43.
2010
Behrens, T., Schmidt, K., Zhu, A. X. und Scholten, T. (2010): The ConMap approach for terrain-based digital soil mapping. European Journal of Soil Science 61, 1, 133–143.
Schönbrodt, S., Saumer, P., Behrens, T., Seeber, C., Scholten, T. (2010): Assessing the USLE Crop and Management Factor C for Soil Erosion Modeling in a Large Mountainous Watershed in Central China. Journal of Earth Science 21, 6, 835–845.
Viscarra-Rossel, R., Behrens, T. (2010): A comparison of data mining techniques to model and interpret soil diffuse reflectance spectra. Geoderma 158, 1-2, 46–54.
Grimm, R., Behrens, T. (2010): Uncertainty analysis of sample locations within digital soil mapping approaches. Geoderma, 155, 3-4, 154–163.
Behrens, T., Zhu, A. X., Schmidt, K. und Scholten, T. (2010): Multi-scale digital terrain analysis and feature selection in digital soil mapping. Geoderma 155, 3–4, 175–185.
Werban, U., Behrens, T., Cassiani, G., Dietrich, P. (2010): iSOIL: An EU Project to Integrate Geophysics, Digital Soil Mapping, and Soil Science. In: Viscarra-Rossel, McBratney, and Minasny: Proximal Soil Sensing. pp. 103–110.
Viscarra-Rossel, R., Rizzo, R., Demattê, J.A.M., Behrens, T., (2010): Spatial Modeling of a Soil Fertility Index using Visible–Near-Infrared Spectra and Terrain Attributes. Soil Science Society of America Journal 74, 4, 1293–1300.
Schmidt, K., Behrens, T., Friedrich, K., Scholten, T. (2010): A method to generating soilscapes from soil maps. J. Plant Nutr. Soil Sci., 173, 2, 163–172.
Gerber, R., Felix-Henningsen, P., Behrens, T., Scholten, T. (2010): Applicability of Ground Penetrating Radar as a tool for non-destructive soil depth mapping on Pleistocene Periglacial Slope Deposits. J. Plant Nutr. Soil Sci., 173, 2.
2009
Dahlke, H.E., Behrens, T., Seibert, J., Andersson, L. (2009): Test of statistical means for the extrapolation of soil depth point information using overlays of spatial environmental data and bootstrapping techniques. Hydrological Processes 23, 21, 3017-3029.
Behrens, T., Schneider, O., Lösel, G., Scholten, T., Hennings, V., Felix-Henningsen, P., Hartwich, R. (2009): Analysis on pedodiversity and spatial subset representativity – The German soil map 1:1.000.000. J. Plant Nutr. Soil Sci., 172, 1, 91–100.
Grimm, R, Behrens, T., Märker, M., Elsenbeer, A. (2008): Soil organic carbon concentrations and stocks on Barro Colorado Island – Digital soil mapping using Random Forests analysis. Geoderma, 146, 1–2, 102–113.
2008
Behrens, T., Schmidt, K., Scholten, T. (2008): An approach to removing uncertainties in nominal environmental covariates and soil class maps. In: Hartemink, A., McBratney, A. and Mendoca-Santos, M.L.: Digital Soil Mapping with Limited Data. Springer, Berlin. pp. 213–224.
Schmidt, K., Behrens, T., Scholten, T. (2008): Instance selection and classification tree analysis for large spatial datasets in digital soil mapping. Geoderma 146, 1–2.
2006
Behrens, T., Scholten, T. (2006): Digital soil mapping in Germany – a review. J. Plant Nutr. Soil Sci. 169, 3, 434–443.
Behrens, T., Scholten, T. (2006): A Comparison of Data Mining Approaches in Predictive Soil Mapping. In: Lagacherie, P., McBratney, A.B, Voltz, M.: Digital Soil Mapping. Developments in Soil Science 31. Elsevier. pp. 353–364.
2005
Behrens, T., Förster, H., Scholten, T., Steinrücken, U., Spies, E.-D., Goldschmitt, M. (2005): Digital Soil Mapping using Artificial Neural Networks. J. Plant Nutr. Soil Sci. 168, 21–33.
1999
Szibalski, M., Behrens, T., Felix-Henningsen, P. (1999): Regionalisierung bodenkundlicher Kennwerte peripherer Regionen am Beispiel des pH-Wertes. Zeitschrift für Kulturtechnik und Landentwicklung, 40, 5–6.
