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Dario Papale

Dario Papale

Dario Papale is Associate Professor of Remote Sensing and Modeling in Forestry at the University of Tuscia (Viterbo, Italy) where he also got his PhD in Forest Ecology in 2003, working on artificial neural networks and eddy covariance data. His interests are in data-model integrations, biogeochemical empirical and data oriented models to assess carbon, water and energy fluxes from terrestrial ecosystems and their uncertainty. Since 2004 he has been the responsible scientist for the European Fluxes Database Cluster (former ecosystem component database of the CarboEurope-IP project) where he mainly works in eddy covariance data standardization, quality control and uncertainty estimation, data policy and database services development. His interest is also focused on the use of carbon and energy fluxes in the context of empirical modeling and data mining, particularly in conjunction with other data sources such as remote sensing data. In this framework he is also responsible for the Airborne Remote Sensing Laboratory where new sensors and methodologies are developed for airborne multispectral remote sensing applications in environmental studies and monitoring.

In recent years his main activity and interest has been the development and coherent growth of the global network of eddy covariance sites (FLUXNET). In this context, he was one of the organizers and members of the FLUXNET synthesis activities, where fluxes measured using the eddy covariance technique in more than 250 sites worldwide are standardized, processed and made available to the scientific community. Since then, he has continued to work on the development of new methods and techniques to enhance the quality of the eddy covariance measurements, particularly in Europe and the US. He is in fact a member of the AmeriFlux Management Project Team and has been nominated for the 2013 Director of the Ecosystem Thematic Center of the Integrated Carbon Observation System (ICOS) in Europe.

Research areas: ecosystem fluxes, remote sensing, machine learning, eddy covariance, data sharing

Annual Journal Metrics

  • 2022 Citation Impact
    4.8 - 2-year Impact Factor
    4.6 - 5-year Impact Factor
    1.760 - SNIP (Source Normalized Impact per Paper)
    1.070 - SJR (SCImago Journal Rank)

    2022 Speed
    3 days submission to first editorial decision for all manuscripts (Median)
    130 days submission to accept (Median)

    2022 Usage 
    409 Altmetric mentions