Forest Canopy Cover Loss (FCCL) - Germany - Monthly, 10m

This raster dataset shows forest canopy cover loss (FCCL) in Germany at a monthly resolution from September 2017 to September 2024. It is similar to the product developed by Thonfeld et l. (2022) but was fully reprocessed and updated to reveal the most recent forest disturbance dynamics. The combination of Sentinel-2A/B and Landsat-8/9 data allows for a high temporal resolution while the pixel size of the product is 10 m. The results are clipped to the stocked area 2018 mapped by the Johann-Heinrich-von-Thünen Institute (Langner et al. 2022, https://doi.org/10.3220/DATA20221205151218 ). The dataset contains predominantly larger canopy openings resulting from different drivers but also larger clusters of standing deadwood. FCCL can result from abiotic (e.g. wind, fire, drought, hail) drivers, biotic (e.g. insects, funghi) drivers or a combination of both as well as from sanitary and salvage logging and planned harvest. The first version with canopy cover losses from January 2018 - April 2021 (Thonfeld et al. 2022) can be accessed here: https://geoservice.dlr.de/web/datasets/tccl.

Citation proposal
German Aerospace Center (DLR). Forest Canopy Cover Loss (FCCL) - Germany - Monthly, 10m. https://gdk.gdi-de.org/geonetwork/srv/api/records/cdb2c209-7e08-4f4c-b500-69de926e3023

Simple

Date ( Creation ): 2025-05-20T00:00:00

Edition

Identifier: https://geoservice.dlr.de/catalogue/srv/metadata/cdb2c209-7e08-4f4c-b500-69de926e3023

Presentation form: Digital map

Other citation details

Purpose: This data set shows recent-past FCCL dynamics. It can be used for future forest management and planning. It therefore addresses public authorities and several stakeholders in the forest, nature conservation and climate sector.

Status: ongoing

Author

German Aerospace Center (DLR) -

Point of contact

German Aerospace Center (DLR)

Maintenance and update frequency: As needed

GEMET - INSPIRE themes, version 1.0 ( Theme )

Land cover

Spatial scope ( Place )

National

Keywords

Forest
Canopy Cover Loss
Disturbance
Sentinel-2
Landsat
Multispectral
Germany
opendata

Use limitation: Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use.

Access constraints: Other restrictions

Use constraints: Other restrictions

Other constraints: Nutzungsbedingungen: Lizenz, https://creativecommons.org/licenses/by/4.0/ Terms of use: License, https://creativecommons.org/licenses/by/4.0/

Other constraints

{"id": "cc-by-4.0",

"name": "Creative-Commons - Attribution 4.0 International (CC BY 4.0)",

"url": "http://dcat-ap.de/def/licenses/cc-by/4.0",

"quelle": "Copyright DLR (2022)"}

Spatial representation type: Grid

Denominator: 20000

Metadata language: English English

Character set: UTF8

Topic category

Biota

Number of dimensions: 2

Dimension name: Column

Dimension size: 66822

Resolution: 10 m

Dimension name: Row

Dimension size: 88989

Resolution: 10 m

Cell geometry: Area

Transformation parameter availability: false

Distribution format

GeoTIFF ()

OnLine resource: FCCL_DE_P1M
EOC Land Map Service

OnLine resource: FCCL_DE_P1M_MASK
EOC Land Map Service

OnLine resource: FCCL_DE_P1M_CHANGES
EOC Land Map Service

OnLine resource: FCCL_DE_P1M_GAPS
EOC Land Map Service

OnLine resource: HTTP Download
HTTP Download

OnLine resource: EOC EO Products Service
EOC EO Products Service - STAC Collection: FCCL_DE_P1M

OnLine resource: EOC Geoservice Dataset
EOC Geoservice Dataset

OnLine resource: Sorge um den deutschen Wald
DLR News - Webpage

Hierarchy level: Dataset

Domain consistency

Measure identification: INSPIRE / Conformity_001

Conformance result

Date ( Publication ): 2010-12-08

Explanation: See the referenced specification.

Pass: true

Statement: The data set is based on time series of Sentinel-2A/B and Landsat-8/9 data.

Description

Processing:

The satellite data is aggregated to monthly composites of the disturbance index (DI, Healey et al. 2005) and compared to the median DI from 2017 as a reference. The algorithm applies a fixed threshold to the difference images and counts how often the threshold is exceeded. An anomaly is considered FCCL if the threshold is exceeded six times in a row.