Spatial data science / multi-scale contextual machine learning / digital soil mapping
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.
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.
Behrens, T., MacMillan R., Viscarra Rossel, R., Schmidt, T., Lee, J. (2019). Teleconnections in spatial modelling. Geoderma, 354.
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).
Behrens, T., Schmidt, K., MacMillan, R.A., Viscarra Rossel, R. (2018). Multi-scale Digital Soil Mapping with deep learning. Scientific Reports, 8,15244.
Behrens, T., Schmidt, K., MacMillan, R.A., Viscarra Rossel, R. (2018). Multi-scale Digital Soil Mapping with deep learning. Scientific Reports, 8,15244.
Behrens, T., Schmidt, K., Rossel, R.A., Gries, P., Scholten, T., MacMillan, R.A. (2018). Spatial modelling with Euclidean distance fields and machine learning. European Journal of Soil Science, 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.
Behrens, T., Schmidt, K., MacMillan, R.A., Viscarra Rossel, R.A. (2017). Multiscale contextual spatial modelling with the Gaussian scale space. Geoderma, 310.
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, 66/3.
Behrens, T., Schmidt, K., Ramirez-Lopez, L., Zhu, A. X., Gallant, J., Scholten, T. (2014). Hyper-scale digital soil mapping and soil formation analysis. Geoderma, 213.
Schönbrodt-Stitt, S., Behrens, T., Schmidt, K., Shi, X., Scholten, T. (2013). Degradation of cultivated bench terraces in the Three Gorges Reservoir Area – field mapping and data mining. Ecological Indicators, 34.
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).
Behrens, T., Zhu, A. X., Schmidt, K. und Scholten, T. (2010b). Multi-scale digital terrain analysis and feature selection in digital soil mapping. Geoderma, 155(3-4).
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).
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.
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).
Behrens, T., Scholten, T. (2006). Digital soil mapping in Germany – a review. J. Plant Nutr. Soil Sci., 169(3).
Grimm, R., Behrens, T. (2010). Uncertainty analysis of sample locations within digital soil mapping approaches. Geoderma, 155(3-4).
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.
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.
Sampling design
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, doi: 10.1111/ejss.12893.
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.
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.
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.
Schmidt, K., Behrens, T., Friedrich, K., Scholten, T. (2010). A method to generating soilscapes from soil maps. J. Plant Nutr. Soil Sci. , 173(2).
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).
Behrens, T., Schmidt, K., Gerber, R., C. Albrecht, C., Felix-Henningsen, P., Scholten, T. (2008). Shortest representative transects for linear operated proximal soil sensing surveys. In: Viscarra-Rossel et al.: Proc. 1st Global Workshop on High Resolution Digital Soil Sensing and Mapping. Sydney, Australia.
Soil spectroscopy
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.
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.
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-Science Reviews, 155.
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.
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.
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 of complex datasets. Geoderma, 195-196.
Ramirez-Lopez, L., Behrens, T., Schmidt, K., Viscarra-Rossel, R.A., Demattê, J.A.M., Scholten, T. (2013). Distance and similarity-search metrics for use with soil vis-NIR spectra. Geoderma , 199.
Viscarra-Rossel, R., Behrens, T. (2010). Using data mining to model and interpret soil diffuse reflectance spectra. Geoderma , 158(1).
Viscarra-Rossel, R., Rizzo, R., Demattê, J.A.M., Behrens, T., (2010). Mapping soil fertility for crop production using soil spectra and terrain analyses. Soil Sci. Soc. Am. J., 74:2010.
Further publications
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.
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, 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.
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.
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.
Werban, U., Behrens, T., Cassiani, G., Dietrich, P. (2010). iSOIL – An EU-project for Integration of Geophysics, Digital Soil Mapping and Soil Science. In: Viscarra-Rossel, McBratney, and Minasny: High resolution Digital Soil Sensing and Mapping. Springer.
Qin, C., Zhu, A-X., Pei, T., Li, B., Behrens, T., Scholten, T., Zhou, C. (2010). An approach to computing topographic wetness index based on maximum downslope gradient. Precision Agriculture, 12/1.
Gerber, R., Felix-Henningsen, P., Behrens, T., Scholten, T. (2009): 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.
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.
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).
