Earth Observation and Machine Learning for Climate Change

Climate change has a multitude of direct and indirect effects on natural habitats, availability and accessibility of resources, human life and communities, and economy. Earth observation data plays a crucial role in informing about these effects, observing and modeling the corresponding processes, identifying corresponding drivers, and monitoring and forecasting climate-related events including natural disasters such as droughts, wildfires, and floods. Machine learning aids in processing and analyzing the multitude of available data to automate the creation of informative products that are of use to local communities and authorities and first responders to develop efficient mitigation strategies and observe the success or failure of corresponding measures. This paper provides an overview of the current state of the art of the different aspects of how the combination of Earth observation data and machine learning help addressing climate-change related issues.