UNITUS Università degli Studi della Tuscia - Department for innovation in biological, agro-food and forest systems (DIBAF)

The University of Tuscia (UNITUS) leads WP3 and participates in BACI through its Department for Innovation in Biological, Agro-food and Forest systems DIBAF

The Department covers three complementary scientific sectors:

• Biological and Chemical Systems for Environment
• Food Science and Technology
• Agricultural and Forest Resources Management

The environmental and agro-forestry area is composed by scientists interested in the plant-soil-atmosphere relationships, in greenhouse gases monitoring, in forest conservation and monitoring, in forest modeling, in remote sensing and geomatics.

OUR ROLE IN BACI

UNITUS will lead WP3 on ground measurements and their organization and standardization, ensuring links with the others existing databases and data collections. In addition UNITUS will contribute to WP2 with the processing of very high resolution optical data and to WP4 for the empirical upscaling of EEVs.

KEY PEOPLE

• Prof. Dario Papale: is a forest ecologist interested GHGs exchanges between ecosystems and atmosphere, data-model integration, and the use of GHGs flux data together with remote sensing data in empirical modeling and data mining. Dario is the ICOS Ecosystem Thematic Center director and scientific responsible in several international networks and projects.
• Dr. Gaia Vaglio Laurin: is a biologist, specialized in ecological remote sensing, interested in monitoring ecosystems resources and dynamics as a tool to improve conservation science. She has several years of experience in developing countries, and worked for different institutions including research centers, international organizations, private sector. Her last published research deals with natural resources estimation and monitoring (forests, soil, biodiversity) using different remotely sensed data.
• Dr. Gianluca Tramontana: is a post-doc researcher at University of Tuscia (DIBAF). He works on the spatial upscaling of carbon and energy fluxes by empirical models , machine learning methods and remote sensing data. He also studied: a) relationships between the biophysical properties of vegetation and the remote sensing variables; b) vegetation health/status by remote sensing data; c) land use mapping.