As part of the ForestPaths project, researchers from the Technical University of Munich created the European Forest Disturbance Atlas (EFDA) and published a detailed paper on it in the Earth System Science Data journal. The publication documents the process of creating the atlas, examines its accuracy, describes the individual map products and discusses its possible role in forest monitoring. 

The EFDA is based on data from the Landsat satellite archive and maps annual forest disturbances across Europe from 1985 to 2023. It is currently the longest remote-sensing-based disturbance product available at the continental scale. The main goal of the atlas is to produce standardised disturbance information with consistent quality across all European forests. The EFDA relies on open-source data and is implemented in an open-access framework to ensure reproducibility and allow easy future updates. 

The atlas includes annual layers on disturbance occurrence, severity and most likely causal agent - such as windstorms, insects, fire, harvest or mixed causes. It also provides aggregated layers describing the number of disturbance events, as well as the most recent and most severe disturbance year. The authors developed an approach that allows annual detection of forest disturbances and accounts for multiple events per time series. The long temporal coverage of the dataset allows for a more comprehensive characterisation of disturbance regimes and can help improve modelling of future disturbance scenarios. 

Compared to previous state-of-the-art disturbance products, the EFDA has lower omission errors, which means it detects more true disturbances. At the same time, it maintains similar commission errors, indicating a comparable number of false detections, while reducing the delay in disturbance year detection compared to the reference data.  

The EFDA is an important advancement in forest disturbance monitoring from space and can significantly improve our understanding of European forest disturbance dynamics. 

Read the full study here.