Forest Structure - Sentinel-1/2, GEDI - Germany, Yearly

The product shows forest structure information on canopy height, total canopy cover and Above-ground biomass density (AGBD) in Germany as annual products in 10 m spatial resolution. The products were generated using a machine learning modelling approach that combines complementary spaceborne remote sensing sensors, namely GEDI (Global Ecosystem Dynamics Investigation; NASA; full-waveform LiDAR), Sentinel-1 (Synthetic-Aperture-Radar; ESA, C-band) and Sentinel-2 (Multispectral Instrument; ESA; VIS-NIR-SWIR). Sample estimates on forest structure from GEDI were modelled in 10 m spatial resolution as annual products based on spatio-temporal composites from Sentinel-1 and -2. The derived products are the first consistent data sets on canopy height, total canopy cover and AGBD for Germany which enable a quantitative assessment of recent forest structure dynamics, e.g. in the context of repeated drought events since 2018. The full description of the method and results can be found in the publication of Kacic et al. (2023).

Date (Creation): 2023-11-16T12:48:00

Citation identifier: https://geoservice.dlr.de/catalogue/srv/metadata/a3c5b57f-8d87-42d2-a3b2-8f5a230964ae

Presentation form: Digital map

Purpose: This map shows the forest structure in Germany based on information on canopy height, total canopy cover and Above-ground biomass density (AGBD).

Status: Completed

Author

German Aerospace Center (DLR) -

Point of contact

German Aerospace Center (DLR)

Maintenance and update frequency: As needed

GEMET - INSPIRE themes, version 1.0

Land cover

Spatial scope

National

Keywords

DLR
EOC
Forest
Forest structure
Drought
Machine Learning Model
Germany
Yearly
Sentinel-1
Sentinel-2
GEDI
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

Other constraints: Es gelten keine Zugriffsbeschränkungen

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 Namensnennung - 4.0 International (CC BY 4.0)",

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

"quelle": "Copyright DLR (year of production)"}

Spatial representation type: Grid

Denominator: 20000

Language: English

Character set: UTF8

Topic category

Imagery base maps earth cover

Begin date: 2017-04-01T00:00:00

Unique resource identifier: EPSG:4326

Number of dimensions: 2

Dimension name: Column

Dimension size: 102120

Resolution: 10 m

Dimension name: Row

Dimension size: 86697

Resolution: 10 m

Cell geometry: Area

Transformation parameter availability: No

Distribution format

GeoTIFF ()

OnLine resource: EOC Geoservice Dataset ( WWW:LINK-1.0-http--link )

OnLine resource

FOREST_STRUCTURE_DE_AGBD_P1Y ( OGC:WMS )

Forest Structure Germany - Above-Ground Biomass Density - Yearly

OnLine resource

FOREST_STRUCTURE_DE_COVER_P1Y ( OGC:WMS )

Forest Structure Germany - Canopy Cover - Yearly

OnLine resource

FOREST_STRUCTURE_DE_RH95_P1Y ( OGC:WMS )

Forest Structure Germany - Canopy Height - Yearly

OnLine resource: https://geoservice.dlr.de/eoc/land/wms?SERVICE=WMS&REQUEST=GetCapabilities ( OGC:WMS-http-get-capabilities )

OnLine resource

EOC Download Service ( WWW:LINK-1.0-http--link )

EOC Download Service (Forest Structure Germany)

Hierarchy level: Dataset

Domain consistency

Measure identification: INSPIRE / Conformity_001

Conformance result

Date (Publication): 2010-12-08

Explanation: See the referenced specification.

Pass: Yes

Statement: Sentinel-1 and Sentinel-2 (less than 60 % cloud coverage) data for the months April to September available through the Google Earth Engine (GEE) were used. In addition, GEDI L2A, L2B, and L4A data from 2019 to 2022 for the months June to August were used. At the date of data processing GEDI data for 2022 was only available for the month June.

Description: Processing: The Sentinel-1 GRD dataset available from GEE was processed ARD using the methodology explained in Mullissa et al. 2021 ( https://doi.org/10.3390/rs13101954 ). Sentinel-2 L2A surface reflectance was processed using sen2cor in GEE.

Quality assurance: With regard to the modelling accuracy, a statistical comparison to independent samples of GEDI was calculated. According to the mean statistics for all years, the canopy height models reach a coefficient of variation (R2) of 64.6 % and a Mean-Absolute-Error (MAE) of 4.4 m. The mean accuracy of total canopy cover models for all years amounts to 67.0 % (R2) and 12.5 % (MAE). The Above-ground biomass density (AGBD) models have a accuracy of 58.8 % in R2 and 41.0 Mg/ha in MAE.