Phd in MODELS FOR ECONOMICS AND FINANCE

Research: When sustainability meets resilience: toward a socioeconomic indicator system for local forest resources under climate change

Personal Information
Alessia D’Agata is a Ph.D. Candidate in the Department of Methods and Models for Territory, Economy and Finance (MEMOTEF), where she holds a doctoral fellowship titled "Innovative approaches for urban, agricultural and forestry planning from the perspective of global change" (PNRR351, curriculum in Economic Geography). She holds a master’s degree in building engineering (LM-4) from the University of Catania and a Professional Master Program in GIScience and SPR for the integrated management of land and natural resources from the University of Padua. His research activity concerns spatial analysis and environmental monitoring and is based on the application of quantitative methods related to remote sensing, applied statistics and spatial econometrics.

Disciplinary fields
M-GGR/02 – Economic geography
SECS-S/03 – Economic statistics

Research interests
spatial analysis; environmental assessment; indication theory; LULC change

Research project title (temporary)
When sustainability meets resilience: Toward a socioeconomic indicator system for local forest resources under climate change

Research project abstract (temporary)
The implications of climate change are far-reaching and have highlighted the urgency of taking prompt, decisive action to mitigate and adapt to their impact. To monitor natural ecosystems, measure their economic value, or assess an area's potential for sustainable development, environmental laws and policies currently depend on indicators derived from multiple knowledge frameworks. Given the partiality of statistical data regarding the Italian forestry sphere and the need to face climate change, the research project intends to move toward the analysis of quantitative forestry information to propose a significant improvement to the data heritage made available to the present. The project aims to develop indicators able to provide a representation of the socio-economic state of national ecosystems at the local scale, with particular attention to the forest one, that can be innovative with respect to the sources and the computation methods used up to now, successfully bridging the gaps between various disciplines and specific information. The information gathered and the methodology used to process it will be multidisciplinary, encompassing statistics, spatial econometrics and remote sensing.