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Matteo Ziliani
Matteo Ziliani
Hydrosat
Verified email at kaust.edu.sa - Homepage
Title
Cited by
Cited by
Year
Intra-season crop height variability at commercial farm scales using a fixed-wing UAV
MG Ziliani, SD Parkes, I Hoteit, MF McCabe
Remote Sensing 10 (12), 2007, 2018
832018
Predicting biomass and yield in a tomato phenotyping experiment using UAV imagery and random forest
K Johansen, MJL Morton, Y Malbeteau, B Aragon, S Al-Mashharawi, ...
Frontiers in Artificial Intelligence 3, 28, 2020
622020
Unmanned aerial vehicle-based phenotyping using morphometric and spectral analysis can quantify responses of wild tomato plants to salinity stress
K Johansen, MJL Morton, YM Malbeteau, B Aragon, SK Al-Mashharawi, ...
Frontiers in Plant Science 10, 449457, 2019
602019
Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model
MG Ziliani, MU Altaf, B Aragon, R Houborg, TE Franz, Y Lu, J Sheffield, ...
Agricultural and forest meteorology 313, 108736, 2022
482022
The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield
TE Franz, S Pokal, JP Gibson, Y Zhou, H Gholizadeh, FA Tenorio, ...
Field Crops Research 252, 107788, 2020
462020
Assimilation of soil moisture and canopy cover data improves maize simulation using an under-calibrated crop model
Y Lu, TP Chibarabada, MG Ziliani, JMK Onema, MF McCabe, J Sheffield
Agricultural Water Management 252, 106884, 2021
382021
Enhanced flood forecasting through ensemble data assimilation and joint state-parameter estimation
MG Ziliani, R Ghostine, B Ait-El-Fquih, MF McCabe, I Hoteit
Journal of Hydrology 577, 123924, 2019
332019
CubeSats deliver new insights into agricultural water use at daily and 3 m resolutions
B Aragon, MG Ziliani, R Houborg, TE Franz, MF McCabe
Scientific reports 11 (1), 12131, 2021
232021
CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals
K Johansen, MG Ziliani, R Houborg, TE Franz, MF McCabe
Scientific reports 12 (1), 5244, 2022
182022
Combining nadir, oblique, and fašade imagery enhances reconstruction of rock formations using unmanned aerial vehicles
YH Tu, K Johansen, B Aragon, BM Stutsel, Y ┴ngel, OAL Camargo, ...
IEEE Transactions on Geoscience and Remote Sensing 59 (12), 9987-9999, 2021
182021
Predicting biomass and yield at harvest of salt-stressed tomato plants using UAV imagery
K Johansen, MJL Morton, Y Malbeteau, BJL Aragon Solorio, ...
Copernicus GmbH, 2019
162019
Corn-Yield Estimation through Assimilation of Remotely Sensed LAI Data into APSIM
MG Ziliani, A Ershadi, B Zheng, B Ait-El-Fquih, MU Altaf, B Aragon, I Hoteit, ...
AGU Fall Meeting Abstracts 2018, GC43I-1653, 2018
32018
Revisiting the spatial scale effects on remotely sensed evaporation
B Aragon, MG Ziliani, MF McCabe
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 6579á…, 2021
22021
Thermal infrared earth observation for operational irrigation management
F Werner, M Ziliani, A Abello
EGU General Assembly Conference Abstracts, EGU-15023, 2023
2023
Toward high resolution and daily thermal infrared measurements for agricultural water management
MG Ziliani, F Werner, A Abellˇ
EGU General Assembly Conference Abstracts, EGU-16403, 2023
2023
Solanum pimpinellifolium input data collected from the TPA-used for GWAS
M Morton, G Fiene, H Ahmed, E Rey, M Abrouk, Y Angel, K Johansen, ...
Zenodo, 2023
2023
Deciphering Salt Stress Responses in Solanum pimpinellifolium through High-Throughput Phenotyping.
MM Morton, G Fiene, HI Ahmed, E Rey, M Abrouk, Y Angel, K Johansen, ...
bioRxiv, 2023.08. 15.553433, 2023
2023
Corn yield prediction: from sub-field to regional level
M Ziliani, B Changaival, A Abellˇ
AGU Fall Meeting Abstracts 2022, B43B-03, 2022
2022
Intra-field crop yield variability by assimilating cubesat lai in the apsim crop model
MG Ziliani, MU Altaf, B Aragon, R Houborg, TE Franz, Y Lu, J Sheffield, ...
The International Archives of the Photogrammetry, Remote Sensing and Spatialá…, 2022
2022
Improving Crop Yield Predictions By Combining Crop Models And High-Resolution Remote Sensing Technologies
M U Altaf, I Hoteit, M F McCabe, M Ziliani
2022
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