Alessio Patriarca

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Actual position: 
PhD Student in Agricultural and Forestry Sciences at the Department of Agricultural and Forestry Sciences (DAFNE) of the University of Tuscia (Viterbo, Italy), since November 2021
Project:
Spatial planning and rural areas: Regional Agricultural Plan as an innovative approach - Funded by Lazio Region


Short BIO:

Alessio Patriarca is a Ph.D. student in the field of Plant and Animal Production Sciences at the Department of Agricultural and Forestry Sciences (DAFNE) of the University of Tuscia, starting from November 2021.

In 2018, he graduated with honors in Agricultural and Environmental Sciences, presenting a thesis on the use of multispectral images for the classification of hazelnut crops in the province of Viterbo.

Since 2018, he has collaborated as an expert consultant in cartography and satellite remote sensing in the drafting of various fire prevention plans for protected areas at national and international levels.

In 2020, he graduated with honors in Agricultural and Environmental Sciences, specializing in Territory, Environment, and Landscape, presenting a thesis entitled "Satellite images as support for decision-making in the management of protected areas: case studies in the upper Lazio region."

In February 2021, he obtained a research scholarship focused on "Analysis of environmental risks in agriculture using field and/or watershed-scale models."

Since November 2021, he has been collaborating with Professor Maria Nicolina Ripa and Professor Fabio Recanatesi in the Land Use Planning and Remote sensing courses at the Department of Agricultural and Forestry Sciences of the University of Tuscia.

During his doctoral studies, he spent six months conducting research at the Division of Forests, Environment, and Landscape of KU Leuven, deepening his knowledge of the use of remotely sensed Big Data to obtain information useful for the planning process.

His research focuses on the definition of geo-indices useful for the planning process of rural areas, using geospatial analysis and data from satellite remote sensing.