Thonfeld, F., Gessner, U., Holzwarth, S., Kriese, J., da Ponte, E., Huth, J., Kuenzer, C., 2022. A First Assessment of Canopy Cover Loss in Germany’s Forests after the 2018-2020 Drought Years. Remote Sensing 14, 562.
Show PublicationHealey, S., Cohen, W., Zhiqiang, Y., Krankina, O., 2005. Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection. Remote Sensing of Environment 97, 301-310.
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The product shows tree canopy cover loss in Germany between January 2018 and April 2021 at monthly temporal and 10 m spatial resolution. The basic principle behind this map is to compute monthly composites of the disturbance index (DI, Healey et al. 2005), a spectral index sensitive to forest disturbance, from all available Sentinel-2 and Landsat-8 data with less than 80 % cloud cover. These monthly composites are then compared to a median composite of the DI for 2017, which serves as a reference. After applying a threshold to the difference image, the time series of detected losses is checked for consistency. Only losses recorded continuously in all observations of a pixel until the end of the time series are considered. The dataset does not differentiate between the drivers of the losses. It depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest. The full description of the method and results can be found in Thonfeld et al. (2022).
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The product shows tree canopy cover loss in Germany between January 2018 and April 2021 at monthly temporal and 10 m spatial resolution. The basic principle behind this map is to compute monthly composites of the disturbance index (DI, Healey et al. 2005), a spectral index sensitive to forest disturbance, from all available Sentinel-2 and Landsat-8 data with less than 80 % cloud cover. These monthly composites are then compared to a median composite of the DI for 2017, which serves as a reference. After applying a threshold to the difference image, the time series of detected losses is checked for consistency. Only losses recorded continuously in all observations of a pixel until the end of the time series are considered. The dataset does not differentiate between the drivers of the losses. It depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest. The full description of the method and results can be found in Thonfeld et al. (2022).
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The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.
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The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.
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The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.
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The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.
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The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.
Copied Record ID
The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.
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EOC Land Map Service
This Web Map Service provides access to land coverage products within the Earth Observation Center (EOC).
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The products depicts per-pixel tree canopy cover loss at 10 m spatial resolution from January 2018 till April 2021.
Copied Layer
This is a vector data set showing per-district statistics of all forests tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of all forests tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of coniferous tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of coniferous tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of deciduous tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of deciduous tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
EOC Land Map Service
This Web Map Service provides access to land coverage products within the Earth Observation Center (EOC).
Copied Endpoint
Layers
The products depicts per-pixel tree canopy cover loss at 10 m spatial resolution from January 2018 till April 2021.
Copied Layer
This is a vector data set showing per-district statistics of all forests tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of all forests tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of coniferous tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of coniferous tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of deciduous tree canopy cover loss in ha in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
This is a vector data set showing per-district statistics of deciduous tree canopy cover loss in % in Germany between January 2018 and April 2021 on annual basis and as sum of all years. Statistics are available for coniferous and deciduous forests as well as across both forest types.
Copied Layer
Further Datasets from Datagroup Forest & Vegetation Products
The EOC provides comprehensive information on the structure and composition of forest areas and vegetation.
Further Datasets of Topic Biosphere
Data related to vegetation parameters, biodiversity and ecological processes.
