M

M. Cavagna

Fondazione Edmund Mach

Publishes on Gamma-ray bursts and supernovae, Astro and Planetary Science, Pulsars and Gravitational Waves Research. 34 papers and 2.1k citations.

34Publications
2.1kTotal Citations

Is this you? Claim your profile.

Add your photo, update your bio, and get notified when your ranking changes.

Top publicationsby citations

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data
Gilberto Pastorello, Carlo Trotta, Eleonora Canfora et al.|Scientific Data|2020
Cited by 1.7kOpen Access

, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018
Bijan Seyednasrollah, Adam M. Young, Koen Hufkens et al.|Journal of the Arkansas Academy of Science|2019
Cited by 41Open Access

This data set provides a time series of vegetation phenological observations for 393 sites across diverse ecosystems of the world (mostly North America) from 2000-2018. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals.The PhenoCam data are released under a CC-BY license.

WhiteRef: A New Tower-Based Hyperspectral System for Continuous Reflectance Measurements
Cited by 28Open Access

Proximal sensing is fundamental to monitor the spatial and seasonal dynamics of ecosystems and can be considered as a crucial validation tool to upscale in situ observations to the satellite level. Linking hyperspectral remote sensing with carbon fluxes and biophysical parameters is critical to allow the exploitation of spatial and temporal extensive information for validating model simulations at different scales. In this study, we present the WhiteRef, a new hyperspectral system designed as a direct result of the needs identified during the EUROSPEC ES0903 Cost Action, and developed by Fondazione Edmund Mach and the Institute of Biometeorology, CNR, Italy. The system is based on the ASD FieldSpec Pro spectroradiometer and was designed to acquire continuous radiometric measurements at the Eddy Covariance (EC) towers and to fill a gap in the scientific community: in fact, no system for continuous spectral measurements in the Short Wave Infrared was tested before at the EC sites. The paper illustrates the functioning of the WhiteRef and describes its main advantages and disadvantages. The WhiteRef system, being based on a robust and high quality commercially available instrument, has a clear potential for unattended continuous measurements aiming at the validation of satellites' vegetation products.