Tobias Benedikt Hank
Tobias Benedikt Hank
Associate Professor, Dept. of Geography, Faculty of Geosciences, LMU Munich
Verified email at - Homepage
Cited by
Cited by
The EnMAP spaceborne imaging spectroscopy mission for earth observation
L Guanter, H Kaufmann, K Segl, S Foerster, C Rogass, S Chabrillat, ...
Remote Sensing 7 (7), 8830-8857, 2015
Evaluation of the PROSAIL model capabilities for future hyperspectral model environments: A review study
K Berger, C Atzberger, M Danner, G D’Urso, W Mauser, F Vuolo, T Hank
Remote Sensing 10 (1), 85, 2018
Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions
K Berger, J Verrelst, JB Féret, Z Wang, M Wocher, M Strathmann, ...
Remote Sensing of Environment 242, 111758, 2020
Global biomass production potentials exceed expected future demand without the need for cropland expansion
W Mauser, G Klepper, F Zabel, R Delzeit, T Hank, B Putzenlechner, ...
Nature communications 6 (1), 8946, 2015
Derivation of biophysical variables from Earth observation data: validation and statistical measures
K Richter, C Atzberger, TB Hank, W Mauser
Journal of Applied Remote Sensing 6 (1), 063557-063557, 2012
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method
K Berger, J Verrelst, JB Féret, T Hank, M Wocher, W Mauser, ...
International Journal of Applied Earth Observation and Geoinformation 92, 102174, 2020
Optimal exploitation of the Sentinel-2 spectral capabilities for crop leaf area index mapping
K Richter, TB Hank, F Vuolo, W Mauser, G D’Urso
Remote Sensing 4 (3), 561-582, 2012
Spaceborne imaging spectroscopy for sustainable agriculture: Contributions and challenges
TB Hank, K Berger, H Bach, JGPW Clevers, A Gitelson, P Zarco-Tejada, ...
Surveys in Geophysics 40, 515-551, 2019
Using a remote sensing-supported hydro-agroecological model for field-scale simulation of heterogeneous crop growth and yield: Application for wheat in central Europe
TB Hank, H Bach, W Mauser
Remote Sensing 7 (4), 3934-3965, 2015
Efficient RTM-based training of machine learning regression algorithms to quantify biophysical & biochemical traits of agricultural crops
M Danner, K Berger, M Wocher, W Mauser, T Hank
ISPRS Journal of Photogrammetry and Remote Sensing 173, 278-296, 2021
Retrieval of seasonal leaf area index from simulated EnMAP data through optimized LUT-based inversion of the PROSAIL model
M Locherer, T Hank, M Danner, W Mauser
Remote Sensing 7 (8), 10321-10346, 2015
Large potential for crop production adaptation depends on available future varieties
F Zabel, C Müller, J Elliott, S Minoli, J Jägermeyr, JM Schneider, ...
Global Change Biology 27 (16), 3870-3882, 2021
Spectral Sampling with the ASD FIELDSPEC 4
M Danner, M Locherer, T Hank, K Richter
GFZ Data Services, 2015
Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios
C Müller, J Franke, J Jägermeyr, AC Ruane, J Elliott, E Moyer, J Heinke, ...
Environmental Research Letters 16 (3), 034040, 2021
Retrieval of biophysical crop variables from multi-angular canopy spectroscopy
M Danner, K Berger, M Wocher, W Mauser, T Hank
Remote Sensing 9 (7), 726, 2017
Fitted PROSAIL parameterization of leaf inclinations, water content and brown pigment content for winter wheat and maize canopies
M Danner, K Berger, M Wocher, W Mauser, T Hank
Remote Sensing 11 (10), 1150, 2019
Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review
K Berger, M Machwitz, M Kycko, SC Kefauver, S Van Wittenberghe, ...
Remote sensing of environment 280, 113198, 2022
The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
JA Franke, C Müller, J Elliott, AC Ruane, J Jägermeyr, J Balkovic, P Ciais, ...
Geoscientific Model Development 13 (5), 2315-2336, 2020
Measuring leaf chlorophyll content with the Konica Minolta SPAD-502Plus
A Süß, M Danner, C Obster, M Locherer, T Hank, K Richter, ...
GFZ Data Services, 2015
A survey of active learning for quantifying vegetation traits from terrestrial earth observation data
K Berger, JP Rivera Caicedo, L Martino, M Wocher, T Hank, J Verrelst
Remote Sensing 13 (2), 287, 2021
The system can't perform the operation now. Try again later.
Articles 1–20