Timely And Semi-Automatic Detection Of Forest Logging Events In Boreal Forest Using All Available Landsat Data

In this study, we utilized all available Landsat images over two adjacent orbits between 1997 and 2015 for the quasi automatic detection of clearcuts and storm damages in boreal forest of Finland. Landsat time series modelling and analysis was done utilizing the Continuous Change Detection and Classification (CCDC) algorithm with a slight modification for rapid operative conditions. The change maps derived from dense time series analysis showed a good agreement compared to reference maps of clearcuts and storm damages obtained from visual interpretation of Very High Resolution image pairs, by lack of reliable reference in temporal and or spatial domain.