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Scientific Reports
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October 8, 2020
On the interpretability of predictors in spatial data science: the information horizon
Thorsten Behrens, Raphael A Viscarra Rossel
Scientific Reports
|
October 17, 2018
Multi-scale digital soil mapping with deep learning
Thorsten Behrens, Karsten Schmidt, Robert A MacMillan, et al.
Environmental Science and Pollution Research International
|
January 24, 2013
Approximation and spatial regionalization of rainfall erosivity based on sparse data in a mountainous catchment of the Yangtze River in Central China
Sarah Schönbrodt-Stitt, Anna Bosch, Thorsten Behrens, et al.
Scientific Reports
|
June 10, 2022
Contextual spatial modelling in the horizontal and vertical domains
Tobias Rentschler, Martin Bartelheim, Thorsten Behrens, et al.
Scientific Reports
|
July 4, 2018
Predicting reference soil groups using legacy data: A data pruning and Random Forest approach for tropical environment (Dano catchment, Burkina Faso)
Kpade O L Hounkpatin, Karsten Schmidt, Felix Stumpf, et al.
Scientific Reports
|
October 17, 2019
The relevant range of scales for multi-scale contextual spatial modelling
Thorsten Behrens, Raphael A Viscarra Rossel, Ruth Kerry, et al.
Plos One
|
August 21, 2019
Comparison of catchment scale 3D and 2.5D modelling of soil organic carbon stocks in Jiangxi Province, PR China
Tobias Rentschler, Philipp Gries, Thorsten Behrens, et al.
Analytica Chimica Acta
|
June 4, 2026
Rethinking local spectral modelling: From per-query refitting to model libraries
Leonardo Ramirez-Lopez, Maxime Metz, Matthieu Lesnoff, et al.
Analytica Chimica Acta
|
June 1, 2026
When spectral libraries are too complex to search: Evolutionary subset selection for domain-adaptive calibration
Leonardo Ramirez-Lopez, Raphael Viscarra Rossel, Claudio Orellano, et al.
Science (New York, N.Y.)
|
October 6, 2018
Impacts of species richness on productivity in a large-scale subtropical forest experiment
Yuanyuan Huang, Yuxin Chen, Nadia Castro-Izaguirre, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 10) with videos related to
Sort By:
Page
of 1
Scientific Reports
|
October 8, 2020
On the interpretability of predictors in spatial data science: the information horizon
Thorsten Behrens, Raphael A Viscarra Rossel
Scientific Reports
|
October 17, 2018
Multi-scale digital soil mapping with deep learning
Thorsten Behrens, Karsten Schmidt, Robert A MacMillan, et al.
Environmental Science and Pollution Research International
|
January 24, 2013
Approximation and spatial regionalization of rainfall erosivity based on sparse data in a mountainous catchment of the Yangtze River in Central China
Sarah Schönbrodt-Stitt, Anna Bosch, Thorsten Behrens, et al.
Scientific Reports
|
June 10, 2022
Contextual spatial modelling in the horizontal and vertical domains
Tobias Rentschler, Martin Bartelheim, Thorsten Behrens, et al.
Scientific Reports
|
July 4, 2018
Predicting reference soil groups using legacy data: A data pruning and Random Forest approach for tropical environment (Dano catchment, Burkina Faso)
Kpade O L Hounkpatin, Karsten Schmidt, Felix Stumpf, et al.
Scientific Reports
|
October 17, 2019
The relevant range of scales for multi-scale contextual spatial modelling
Thorsten Behrens, Raphael A Viscarra Rossel, Ruth Kerry, et al.
Plos One
|
August 21, 2019
Comparison of catchment scale 3D and 2.5D modelling of soil organic carbon stocks in Jiangxi Province, PR China
Tobias Rentschler, Philipp Gries, Thorsten Behrens, et al.
Analytica Chimica Acta
|
June 4, 2026
Rethinking local spectral modelling: From per-query refitting to model libraries
Leonardo Ramirez-Lopez, Maxime Metz, Matthieu Lesnoff, et al.
Analytica Chimica Acta
|
June 1, 2026
When spectral libraries are too complex to search: Evolutionary subset selection for domain-adaptive calibration
Leonardo Ramirez-Lopez, Raphael Viscarra Rossel, Claudio Orellano, et al.
Science (New York, N.Y.)
|
October 6, 2018
Impacts of species richness on productivity in a large-scale subtropical forest experiment
Yuanyuan Huang, Yuxin Chen, Nadia Castro-Izaguirre, et al.
Page
of 1