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
Clear-cutting is the most drastic and wide-spread change that affects the hydrological and carbon-ba...
The study focuses on the detection of forest change in the boreal forest ecosystem caused by convent...
The purpose of this study is to develop a monitoring tool for boreal forest cover change on continen...
Within the widely investigated field of forest disturbance monitoring, the detection of forest storm...
The availability of free and open high resolution optical satellite imagery has greatly improved ove...
The majority of the boreal forests in Finland are regularly thinned or clear-cut, and these actions ...
This article presents a new unsupervised method (AutoChange) for change detection and identification...
Climate change has increased the occurrence of heavy storms that cause damage to forests. After a st...
Clear-cutting and logging operations are the most drastic and wide-spread changes that affects the h...
Although timber production in Russian forests is of great economic importance, forest logging is a m...
Several forest change detection algorithms are available for tracking and quantifying deforestation ...
Natural disasters are generally brutal and may affect large areas, which then need to be rapidly map...
International audienceNatural disasters are generally brutal and may affect large areas, which then ...
With climate change, extreme storms are expected to occur more frequently. These storms can cause se...
Time series analysis of Landsat data is widely used for assessing forest change at the large-area sc...
Clear-cutting is the most drastic and wide-spread change that affects the hydrological and carbon-ba...
The study focuses on the detection of forest change in the boreal forest ecosystem caused by convent...
The purpose of this study is to develop a monitoring tool for boreal forest cover change on continen...
Within the widely investigated field of forest disturbance monitoring, the detection of forest storm...
The availability of free and open high resolution optical satellite imagery has greatly improved ove...
The majority of the boreal forests in Finland are regularly thinned or clear-cut, and these actions ...
This article presents a new unsupervised method (AutoChange) for change detection and identification...
Climate change has increased the occurrence of heavy storms that cause damage to forests. After a st...
Clear-cutting and logging operations are the most drastic and wide-spread changes that affects the h...
Although timber production in Russian forests is of great economic importance, forest logging is a m...
Several forest change detection algorithms are available for tracking and quantifying deforestation ...
Natural disasters are generally brutal and may affect large areas, which then need to be rapidly map...
International audienceNatural disasters are generally brutal and may affect large areas, which then ...
With climate change, extreme storms are expected to occur more frequently. These storms can cause se...
Time series analysis of Landsat data is widely used for assessing forest change at the large-area sc...
Clear-cutting is the most drastic and wide-spread change that affects the hydrological and carbon-ba...
The study focuses on the detection of forest change in the boreal forest ecosystem caused by convent...
The purpose of this study is to develop a monitoring tool for boreal forest cover change on continen...