ESA CCI Land Cover - Sentinel-2A Prototype Land Cover 20 meter Map of Africa 2016

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The CCI Land Cover (LC) team is proud to announce the successful development of a prototype high resolution LC map at 20m over Africa based on 1 year of Sentinel-2A observations from December 2015 to December 2016. The main objective of the 'S2 prototype LC map at 20m of Africa 2016' release is to collect users feedback for further improvements.

The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid.

The legend of the S2 prototype LC 20m map of Africa 2016 was built after reviewing various existing typologies (e.g. LCCS, LCML…), global (e.g. GLC-share, GlobeLand30) and national experiences (Africover, SERVIR-RMCD). The legend includes 10 generic classes that appropriately describe the land surface at 20m: "trees cover areas", "shrubs cover areas", "grassland", "cropland", "vegetation aquatic or regularly flooded", "lichen and mosses / sparse vegetation", "bare areas", "built up areas", "snow and/or ice" and "open water".

Among the Land Cover classes, two of them were largely identified thanks to external dataset: the "open water" class was based on the Global Surface Water product from JRC/EC and the "urban areas" relied both on the Global Human Settlement Layer from JRC/EC and on the Global Urban Footprint from DLR.

Two classification algorithms, the Random Forest (RF) and Machine Learning (ML), were chosen to transform the cloud-free reflectance composites generated by the pre-processing module into a land cover map. The two maps resulting from both approaches are then combined either to select the best representation of a land cover class which will be part of the final S2 prototype LC 20m map of Africa 2016 or, in case of unreliable LC class delineation, the reference layer is used to consolidate the land cover classification.

Type: 
Geospatial
Topics: 
Climate Change
Environment and Natural Resources
Urban Development
Water
Economy Coverage: 
Blend
Languages Supported: 
English
Geographical Coverage: 
Algeria
Egypt, Arab Rep.
Djibouti
Libya
Morocco
Tunisia
Sub-Saharan Africa
Angola
Benin
Botswana
Burkina Faso
Burundi
Cabo Verde
Cameroon
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d'Ivoire
Ethiopia
Eritrea
Equatorial Guinea
Gabon
Gambia, The
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
Namibia
Niger
Nigeria
Rwanda
São Tomé and Principe
Seychelles
Senegal
Sierra Leone
Somalia
South Africa
South Sudan
Sudan
Eswatini
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Access Options:
Download
Data Notes: 
We invite you to contact us at [email protected] for: •questions regarding the content and usage of the above-mentioned products •general comments, feedback or questions about the S2 prototype LC 20m map of Africa 2016
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ESA CCI Land Cover - Sentinel-2A Prototype Land Cover 20 meter Map of Africa 2016

The CCI Land Cover (LC) team is proud to announce the successful development of a prototype high resolution LC map at 20m over Africa based on 1 year of Sentinel-2A observations from December 2015 to December 2016. The main objective of the 'S2 prototype LC map at 20m of Africa 2016' release is to collect users feedback for further improvements. The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid. The legend of the S2 prototype LC 20m map of Africa 2016 was built after reviewing various existing typologies (e.g. LCCS, LCML…), global (e.g. GLC-share, GlobeLand30) and national experiences (Africover, SERVIR-RMCD). The legend includes 10 generic classes that appropriately describe the land surface at 20m: "trees cover areas", "shrubs cover areas", "grassland", "cropland", "vegetation aquatic or regularly flooded", "lichen and mosses / sparse vegetation", "bare areas", "built up areas", "snow and/or ice" and "open water". Among the Land Cover classes, two of them were largely identified thanks to external dataset: the "open water" class was based on the Global Surface Water product from JRC/EC and the "urban areas" relied both on the Global Human Settlement Layer from JRC/EC and on the Global Urban Footprint from DLR. Two classification algorithms, the Random Forest (RF) and Machine Learning (ML), were chosen to transform the cloud-free reflectance composites generated by the pre-processing module into a land cover map. The two maps resulting from both approaches are then combined either to select the best representation of a land cover class which will be part of the final S2 prototype LC 20m map of Africa 2016 or, in case of unreliable LC class delineation, the reference layer is used to consolidate the land cover classification.
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The CCI Land Cover (LC) team is proud to announce the successful development of a prototype high resolution LC map at 20m over Africa based on 1 year of Sentinel-2A observations from December 2015 to December 2016. The main objective of the 'S2 prototype LC map at 20m of Africa 2016' release is to collect users feedback for further improvements.

The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid.

The legend of the S2 prototype LC 20m map of Africa 2016 was built after reviewing various existing typologies (e.g. LCCS, LCML…), global (e.g. GLC-share, GlobeLand30) and national experiences (Africover, SERVIR-RMCD). The legend includes 10 generic classes that appropriately describe the land surface at 20m: "trees cover areas", "shrubs cover areas", "grassland", "cropland", "vegetation aquatic or regularly flooded", "lichen and mosses / sparse vegetation", "bare areas", "built up areas", "snow and/or ice" and "open water".

Among the Land Cover classes, two of them were largely identified thanks to external dataset: the "open water" class was based on the Global Surface Water product from JRC/EC and the "urban areas" relied both on the Global Human Settlement Layer from JRC/EC and on the Global Urban Footprint from DLR.

Two classification algorithms, the Random Forest (RF) and Machine Learning (ML), were chosen to transform the cloud-free reflectance composites generated by the pre-processing module into a land cover map. The two maps resulting from both approaches are then combined either to select the best representation of a land cover class which will be part of the final S2 prototype LC 20m map of Africa 2016 or, in case of unreliable LC class delineation, the reference layer is used to consolidate the land cover classification.

FieldValue
Modified Date
2018-03-19
Release Date
Periodicity
Other
Identifier
fcbadd0a-0811-45d0-8258-f8c1f8aa9a29
License
License Not Specified
Contact Email
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Type: 
Languages Supported: 
Economy Coverage: 
Data Classification of a Dataset: 
GTK
Data Notes: 
We invite you to contact us at [email protected] for: •questions regarding the content and usage of the above-mentioned products •general comments, feedback or questions about the S2 prototype LC 20m map of Africa 2016
Modified date: 
97
Primary Dataset: 
Yes

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