The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data G Pastorello, C Trotta, E Canfora, H Chu, D Christianson, YW Cheah, ... Scientific data 7 (1), 225, 2020 | 906 | 2020 |
Eddy covariance raw data processing for CO2 and energy fluxes calculation at ICOS ecosystem stations S Sabbatini, I Mammarella, N Arriga, G Fratini, A Graf, L Hörtnagl, A Ibrom, ... International agrophysics 32 (4), 495-515, 2018 | 84 | 2018 |
Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems: a review D Franz, M Acosta, N Altimir, N Arriga, D Arrouays, et al International Agrophysics 32 (4), 439-455, 2018 | 73 | 2018 |
Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands J Irvin, S Zhou, G McNicol, F Lu, V Liu, E Fluet-Chouinard, Z Ouyang, ... Agricultural and Forest Meteorology 308, 108528, 2021 | 52 | 2021 |
A statistical analysis of factors affecting higher education dropouts P Perchinunno, M Bilancia, D Vitale Social Indicators Research 156, 341-362, 2021 | 45 | 2021 |
Towards a flux-partitioning procedure based on the direct use of high-frequency eddy-covariance data L Palatella, G Rana, D Vitale Boundary-layer meteorology 153, 327-337, 2014 | 36 | 2014 |
Time trend in reference evapotranspiration: analysis of a long series of agrometeorological measurements in Southern Italy AD Palumbo, D Vitale, P Campi, M Mastrorilli Irrigation and Drainage Systems 25, 395-411, 2011 | 30 | 2011 |
Carbon assimilation and water use efficiency of a perennial bioenergy crop (Cynara cardunculus L.) in Mediterranean environment G Rana, RM Ferrara, D Vitale, L D’Andrea, AD Palumbo Agricultural and forest meteorology 217, 137-150, 2016 | 25 | 2016 |
Trends and extremes analysis of daily weather data from a site in the Capitanata plain (southern Italy) D Vitale, G Rana, P Soldo Italian Journal of Agronomy 5 (2), 133-144, 2010 | 25 | 2010 |
A comparison of different methods for assessing leaf area index in four canopy types C Ariza-Carricondo, F Di Mauro, MO de Beeck, M Roland, B Gielen, ... Central European Forestry Journal 65 (2), 67-80, 2019 | 24 | 2019 |
A robust data cleaning procedure for eddy covariance flux measurements D Vitale, G Fratini, M Bilancia, G Nicolini, S Sabbatini, D Papale Biogeosciences 17, 1367-1391, 2020 | 23 | 2020 |
A Multiple Imputation Strategy for Eddy Covariance Data D Vitale, M Bilancia, D Papale Journal of Environmental Informatics 34 (2), 2019 | 19 | 2019 |
Modelling random uncertainty of eddy covariance flux measurements D Vitale, M Bilancia, D Papale Stochastic environmental research and risk assessment 33, 725-746, 2019 | 7 | 2019 |
Eddy covariance flux errors due to random and systematic timing errors during data acquisition G Fratini, S Sabbatini, K Ediger, B Riensche, G Burba, G Nicolini, D Vitale, ... Biogeosciences, 2018 | 7 | 2018 |
Near Real Time Data Processing In ICOS RI M Hellström, A Vermeulen, O Mirzov, S Sabbatini, D Vitale, D Papale, ... Proceedings of 2nd International Workshop on Interoperable infrastructures …, 2016 | 7 | 2016 |
Role of the natural and anthropogenic radiative forcings on global warming: evidence from cointegration–VECM analysis D Vitale, M Bilancia Environmental and ecological statistics 20, 413-444, 2013 | 7 | 2013 |
FLUXNET2015 IT-Ro1 Roccarespampani 1 R Valentini, G Tirone, D Vitale, D Papale, N Arriga, L Belelli, S Dore, ... | 5 | 2016 |
Anthropogenic CO2 Emissions and Global Warming: Evidence from Granger Causality Analysis M Bilancia, D Vitale Advanced statistical methods for the analysis of large data-sets, 229-239, 2012 | 5 | 2012 |
Climate Change and Irrigation Water Consumption: a Case Study of the Olive and Tomato in Apulia AD Palumbo, D Vitale, P Campi, M Mastrorilli Multi-functional Agriculture-Agriculture as a Resource for Energy and …, 2008 | 5 | 2008 |
A performance evaluation of despiking algorithms for eddy covariance data D Vitale Scientific Reports 11 (1), 11628, 2021 | 3 | 2021 |