Causal inference for climate change events from satellite image time series using computer vision and deep learning

Understand

We propose a method for causal inference using satellite image time series, in order to determine the treatment effects of interventions which impact climate change, such as deforestation.

• Simply put, the aim is to quantify the 'before versus after' effect of climate related human driven interventions, such as urbanization; as well as natural disasters, such as hurricanes and forest fires.
• As a concrete example, we focus on quantifying forest tree cover change/ deforestation due to human led causes.
• The proposed method involves the following steps.