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Urs Schulthess
Urs Schulthess
CIMMYT
Verified email at cgiar.org
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Cited by
Cited by
Year
Comparison of machine learning algorithms random forest, artificial neural network and support vector machine to maximum likelihood for supervised crop type classification
I Nitze, U Schulthess, H Asche
Proceedings of the 4th GEOBIA, Rio de Janeiro, Brazil 79, 3540, 2012
2992012
Broadband, red-edge information from satellites improves early stress detection in a New Mexico conifer woodland
JUH Eitel, LA Vierling, ME Litvak, DS Long, U Schulthess, AA Ager, ...
Remote Sensing of Environment 115 (12), 3640-3646, 2011
2952011
Evolution of CO2 and soil carbon dynamics in biologically managed, row-crop agroecosystems
EA Paul, D Harris, HP Collins, U Schulthess, GP Robertson
Applied Soil Ecology 11 (1), 53-65, 1999
2171999
Variable rate nitrogen fertilizer response in wheat using remote sensing
B Basso, C Fiorentino, D Cammarano, U Schulthess
Precision agriculture 17, 168-182, 2016
1212016
Sustainable crop intensification through surface water irrigation in Bangladesh? A geospatial assessment of landscape-scale production potential
TJ Krupnik, U Schulthess, ZU Ahmed, AJ McDonald
Land use policy 60, 206-222, 2017
1002017
Yield‐independent variation in grain nitrogen and phosphorus concentration among Ethiopian wheats
U Schulthess, B Feil, SC Jutzi
Agronomy Journal 89 (3), 497-506, 1997
991997
Vernalization in wheat I. A model based on the interchangeability of plant age and vernalization duration
SY Wang, RW Ward, JT Ritchie, RA Fischer, U Schulthess
Field Crops Research 41 (2), 91-100, 1995
751995
Role of modelling in international crop research: overview and some case studies
M Reynolds, M Kropff, J Crossa, J Koo, G Kruseman, A Molero Milan, ...
Agronomy 8 (12), 291, 2018
622018
Mapping field-scale yield gaps for maize: An example from Bangladesh
U Schulthess, J Timsina, JM Herrera, A McDonald
Field Crops Research 143, 151-156, 2013
622013
Multi-temporal and spectral analysis of high-resolution hyperspectral airborne imagery for precision agriculture: assessment of wheat grain yield and grain protein content
FA Rodrigues Jr, G Blasch, P Defourny, JI Ortiz-Monasterio, U Schulthess, ...
Remote Sensing 10 (6), 930, 2018
582018
Rapid estimation of canopy nitrogen of cereal crops at paddock scale using a Canopy Chlorophyll Content Index
EM Perry, GJ Fitzgerald, JG Nuttall, GJ O’Leary, U Schulthess, A Whitlock
Field Crops Research 134, 158-164, 2012
572012
Harnessing translational research in wheat for climate resilience
MP Reynolds, JM Lewis, K Ammar, BR Basnet, L Crespo-Herrera, ...
Journal of Experimental Botany 72 (14), 5134-5157, 2021
412021
Integrated wheat crop management based on generic task knowledge-based systems and CERES numerical simulation.
A Kamel, K Schroeder, J Sticklen, A Rafea, A Salah, U Schulthess, ...
40*1995
Increased ranking change in wheat breeding under climate change
W Xiong, MP Reynolds, J Crossa, U Schulthess, K Sonder, C Montes, ...
Nature plants 7 (9), 1207-1212, 2021
342021
Detecting mortality induced structural and functional changes in a piņon-juniper woodland using Landsat and RapidEye time series
DJ Krofcheck, JUH Eitel, LA Vierling, U Schulthess, TM Hilton, ...
Remote sensing of environment 151, 102-113, 2014
332014
Estimating adoption and impacts of agricultural management practices in developing countries using satellite data. A scoping review
C Kubitza, VV Krishna, U Schulthess, M Jain
Agronomy for Sustainable Development 40, 1-21, 2020
282020
NEPER‐Weed: A Picture‐Based Expert System for Weed Identification
U Schulthess, K Schroeder, A Kamel, AEGM AbdElGhani, ...
Agronomy journal 88 (3), 423-427, 1996
271996
Radiative transfer model inversion using high-resolution hyperspectral airborne imagery–Retrieving maize LAI to access biomass and grain yield
A Kayad, FA Rodrigues Jr, S Naranjo, M Sozzi, F Pirotti, F Marinello, ...
Field Crops Research 282, 108449, 2022
252022
Farming on the fringe: Shallow groundwater dynamics and irrigation scheduling for maize and wheat in Bangladesh’s coastal delta
U Schulthess, ZU Ahmed, S Aravindakshan, GM Rokon, ASMA Kurishi, ...
Field crops research 239, 135-148, 2019
252019
Detecting functional field units from satellite images in smallholder farming systems using a deep learning based computer vision approach: A case study from Bangladesh
R Yang, ZU Ahmed, UC Schulthess, M Kamal, R Rai
Remote Sensing Applications: Society and Environment 20, 100413, 2020
232020
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