ERC Advanced Grant · 2024
This project begins with a “book:” eight historical case studies detailing environmental change will serve to produce 8 machine learning training data sets to develop a methodology for the automatic analysis of quantitative and visual environmental data from historical aerial photographs. This will allow for a new approach to study the 1940s-1990s Great Acceleration, which caused unprecedented environmental change. Becoming ubiquitous in the 1940s, aerial photography has a sub-1-meter resolution which is key to identifying non-linear, non-monumental, and pre-industrial rural environmental infrastructure (e.g. trees, waterholes, fields) and how it has changed over time. Since satellite…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.