Fabio Veronesi
Fabio Veronesi
Senior Data Scientist, Rezatec
Verified email at rezatec.com - Homepage
Cited by
Cited by
Mapping soil compaction in 3D with depth functions
F Veronesi, R Corstanje, T Mayr
Soil and Tillage Research 124, 111-118, 2012
Landscape scale estimation of soil carbon stock using 3D modelling
F Veronesi, R Corstanje, T Mayr
Science of the total environment 487, 578-586, 2014
Automatic selection of weights for GIS-based multicriteria decision analysis: site selection of transmission towers as a case study
F Veronesi, J Schito, S Grassi, M Raubal
Applied Geography 83, 78-85, 2017
Statistical learning approach for wind resource assessment
F Veronesi, S Grassi, M Raubal
Renewable and Sustainable Energy Reviews 56, 836-850, 2016
A geostatistical analysis of soil properties in the Davis Pond Mississippi freshwater diversion
F Kral, R Corstanje, JR White, F Veronesi
Soil Science Society of America Journal 76 (3), 1107-1118, 2012
Estimation of the global solar energy potential and photovoltaic cost with the use of open data
A Korfiati, C Gkonos, F Veronesi, A Gaki, S Grassi, R Schenkel, ...
International Journal of Sustainable Energy Planning and Management 9, 17-30, 2016
Comparison between geostatistical and machine learning models as predictors of topsoil organic carbon with a focus on local uncertainty estimation
F Veronesi, C Schillaci
Ecological Indicators 101, 1032-1044, 2019
Online hate interpretation varies by country, but more by individual: A statistical analysis using crowdsourced ratings
J Salminen, F Veronesi, H Almerekhi, SG Jung, BJ Jansen
2018 Fifth International Conference on Social Networks Analysis, Management …, 2018
A GIS tool to increase the visual quality of relief shading by automatically changing the light direction
F Veronesi, L Hurni
Computers & Geosciences 74, 121-127, 2015
Random Forest with semantic tie points for classifying landforms and creating rigorous shaded relief representations
F Veronesi, L Hurni
Geomorphology 224, 152-160, 2014
Changing the light azimuth in shaded relief representation by clustering aspect
F Veronesi, L Hurni
The Cartographic Journal 51 (4), 291-300, 2014
A comparative analysis of the precipitation extremes obtained from tropical rainfall‐measuring mission satellite and rain gauges datasets over a semiarid region
M Mahbod, A Shirvani, F Veronesi
International Journal of Climatology 39 (1), 495-515, 2019
Phylogenetic clustering of wingbeat frequency and flight‐associated morphometrics across insect orders
MPTG Tercel, F Veronesi, TW Pope
Physiological entomology 43 (2), 149-157, 2018
Assessing accuracy and geographical transferability of machine learning algorithms for wind speed modelling
F Veronesi, A Korfiati, R Buffat, M Raubal
The Annual International Conference on Geographic Information Science, 297-310, 2017
Mapping of the global wind energy potential using open source GIS data
S Grassi, F Veronesi, R Schenkel, C Peier, J Neukom, S Volkwein, ...
2nd International Conference on Energy and Environment: Bringing Together …, 2015
Comparison of hourly and daily wind speed observations for the computation of Weibull parameters and power output
F Veronesi, S Grassi
2015 3rd International Renewable and Sustainable Energy Conference (IRSEC), 1-6, 2015
An evaluative study of TRMM precipitation estimates over multi-day scales in a semi-arid region, Iran
M Mahbod, F Veronesi, A Shirvani
International Journal of Remote Sensing 40 (11), 4143-4174, 2019
Statistical learning approach for wind speed distribution mapping: the UK as a case study
F Veronesi, S Grassi, M Raubal, L Hurni
AGILE 2015, 165-180, 2015
Foreword to the special issue on machine learning for geospatial data analysis
JD Wegner, R Roscher, M Volpi, F Veronesi
ISPRS International Journal of Geo-Information 7 (4), 147, 2018
Generation and validation of spatial distribution of hourly wind speed time-series using machine learning
F Veronesi, S Grassi
Journal of Physics: Conference Series 749 (1), 012001, 2016
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