Landcover classification map of Germany 2016 based on Sentinel-2 data

This landcover map was produced as an intermediate result in the course of the project incora (Inwertsetzung von Copernicus-Daten für die Raumbeobachtung, mFUND Förderkennzeichen: 19F2079C) in cooperation with ILS (Institut für Landes- und Stadtentwicklungsforschung gGmbH) and BBSR (Bundesinstitut für Bau-, Stadt- und Raumforschung) funded by BMVI (Federal Ministry of Transport and Digital Infrastructure). The goal of incora is an analysis of settlement and infrastructure dynamics in Germany based on Copernicus Sentinel data.


This classification is based on a time-series of monthly averaged, atmospherically corrected Sentinel-2 tiles (MAJA L3A-WASP: https://geoservice.dlr.de/web/maps/sentinel2:l3a:wasp ; DLR (2019): Sentinel-2 MSI - Level 2A (MAJA-Tiles)- Germany). It consists of the following landcover classes:

10: forest

20: low vegetation

30: water

40: built-up

50: bare soil

60: agriculture


Potential training and validation areas were automatically extracted using spectral indices and their temporal variability from the Sentinel-2 data itself as well as the following auxiliary datasets:

- OpenStreetMap (Map data copyrighted OpenStreetMap contributors and available from htttps://www.openstreetmap.org)

- Copernicus HRL Imperviousness Status Map 2018 (© European Union, Copernicus Land Monitoring Service 2018, European Environment Agency (EEA))

- S2GLC Land Cover Map of Europe 2017 (Malinowski et al. 2020: Automated Production of Land Cover/Use Map of Europe Based on Sentinel-2 Imagery. Remote Sens. 2020, 12(21), 3523; https://doi.org/10.3390/rs 12213523)

- Germany NUTS administrative areas 1:250000 (© GeoBasis-DE / BKG 2020 / dl-de/by-2-0 / https://gdz.bkg.bund.de/index.php/default/nuts-gebiete-1-250-000-stand-31-12-nuts250-31-12.html )

- Contains modified Copernicus Sentinel data (2016), processed by mundialis


Processing was performed for blocks of federal states and individual maps were mosaicked afterwards.

For each class 100,000 pixels from the potential training areas were extracted as training data.


An exemplary validation of the classification results was perfomed for the federal state of North Rhine-Westphalia as its open data policy allows for direct access to official data to be used as reference. Rules to convert relevant ATKIS Basis-DLM object classes to the incora nomenclature were defined. Subsequently, 5.000 reference points were randomly sampled and their classification in each case visually examined and, if necessary, revised to obtain a robust reference data set. The comparison of this reference data set with the incora classification yielded the following results:


overall accuracy: 88.4%


class: user's accuracy / producer's accuracy (number of reference points n)

forest: 96.7% / 94.3% (1410)

low vegetation: 70.6% / 84.0% (844)

water: 98.5% / 94.2% (69)

built-up: 98.2% / 89.8% (983)

bare soil: 19.7% / 58.5% (41)

agriculture: 91.7% / 85.3% (1653)


Incora report with details on methods and results: pending

INSPIRE

Identification

File identifier
db130a09-fc2e-421d-95e2-1575e7c4b45c XML
Hierarchy level
Dataset
Online resource
Protocol

WWW:DOWNLOAD-1.0-http--download
Protocol

WWW:DOWNLOAD-1.0-http--download
Resource identifier
code

dataset
Metadata language
English
Spatial representation type
Grid
Encoding
Format

GeoTIFF
Version

1.0
Projection
code

EPSG:32632 (UTM 32N)
 

Classification of data and services

Topic category
  • Geoscientific information
 

Classification of data and services

Coupled resource

Coupled resource
 
 

Classification of data and services

Coupled resource

Coupled resource
 
 

Keywords

GEMET - INSPIRE themes, version 1.0

  • Land cover

  • Land use

Other keywords

Theme

  • Sentinel-2

  • Classification

  • Land Cover

  • mFUND

  • MAJA

  • Infrastuktur

  • Umwelt

  • Regionen und Städte

  • mfund-projekt:incora

  • mfund-fkz:19F2079C

  • incora
Place

  • Germany
 
 

Geographic coverage

N
S
E
W
thumbnail


 

Temporal reference

Temporal extent
Begin
2016-01-01
End
2016-12-31
Temporal extent
Date (Publication)
2020-12-01
 

Quality and validity

Lineage

derived from Sentinel-2 MSI - Level 3A-WASP
Distance
10  meters
 

Conformity

Conformity
Conformity
 

Conformity

Conformity
Conformity
Explanation

See specified reference
 

Restrictions on access and use

Access constraints
no limitations to public access
Access constraints

Data licence Germany - attribution - version 2.0 or later (DL-DE->BY-2.0) | Datenlizenz Deutschland - Namensnennung - Version 2.0 oder neuer
Access constraints

{ "id": "dl-by-de/2.0", "name": "Datenlizenz Deutschland Namensnennung 2.0", "url": " https://www.govdata.de/dl-de/by-2-0 ", "quelle": "Source: mundialis GmbH & Co. KG" }

 

Responsible organization (s)

Contact for the resource
Organisation name

mundialis GmbH & Co. KG
Email

info@mundialis.de

 

Responsible organization (s)

Contact for the resource
Organisation name

mundialis GmbH & Co. KG
Email

info@mundialis.de

 

Metadata information

Contact for the metadata
Organisation name

mundialis GmbH & Co. KG
Email

info@mundialis.de

Date stamp
2023-02-28T10:32:47
Metadata language
English
Character set
UTF8
 
 

SDS

Conformance class 1: invocable

Access Point URL
Endpoint URL
Technical specification
 

Conformance class 2: interoperable

Access constraints

Limitation
 

Use constraints

Limitation
 

Responsible custodian

Contact for the resource
 
 
 

Overviews

overview

Spatial extent

N
S
E
W
thumbnail


Keywords

Classification Infrastuktur Land Cover MAJA Regionen und Städte Sentinel-2 Umwelt incora mFUND mfund-fkz:19F2079C mfund-projekt:incora
GEMET - INSPIRE themes, version 1.0
Land cover Land use

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Not available