Leadership Team

This project aims to i) create landscape-scale Agent-Based modelling (ABM) of anthropogenic fire for case study locations (e.g. Mediterranean Basin, Tropical Africa), ii) develop methods to emulate results from (i) to apply at broader scales. Outcomes will improve our understanding about how ABM may contribute to improving representation of anthropogenic fire in wildfire models and DGVMs.

Leadership Team

The proposed project (a) assesses the socioeconomic drivers of wildfire risk and (b) quantifies the impact of wildfire at the individual and aggregate levels. Specifically, at the first stage the project will develop an analytical framework to assess the influence of human economic activity on wildfire occurrence and extent. At the second stage it will quantify and appropriately monetize the welfare impact of wildfire focusing ecosystem services provision, productivity, health and social capital. It involves econometric modelling, stated and revealed preference valuation techniques and combines individual level data from large social, time use and economic surveys, aggregate economic data, land use, meteorological and Earth Observation data.

Leadership Team

Leadership Team

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