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DATASET

GHS-BUILT-S2 R2020A - GHS built-up grid, derived from Sentinel-2 global image composite for reference year 2018 using Convolutional Neural Networks (GHS-S2Net)

Collection: GHSL : Global Human Settlement Layer 

Description

This dataset corresponds to global map of built-up areas expressed in terms of a probability grid at 10 m spatial resolution derived from a Sentinel-2 global image composite (GHS_composite_S2_L1C_2017-2018_GLOBE_R2020A_UTM_10_v1_0) for reference year 2018. It builds on a new Deep Learning framework for pixel-wise large-scale classification of built-up areas named GHS-S2Net (GHS stands for Global Human Settlements, S2 refers to the Sentinel-2 satellite).

Contact

Email
jrc-ghsl-data (at) ec.europa.eu

Contributors

How to cite

Corbane, Christina; Sabo, Filip; Politis, Panagiotis; Syrris, Vasileios (2020): GHS-BUILT-S2 R2020A - GHS built-up grid, derived from Sentinel-2 global image composite for reference year 2018 using Convolutional Neural Networks (GHS-S2Net). European Commission, Joint Research Centre (JRC) [Dataset] doi: 10.2905/016D1A34-B184-42DC-B586-E10B915DD863 PID: http://data.europa.eu/89h/016d1a34-b184-42dc-b586-e10b915dd863

Keywords

Artificial Intelligence Built-up areas Big Data Copernicus GHS-BUILT Global Sentinel-2 Remote Sensing GHSL

Data access

GHS_BUILT_S2comp2018_GLOBE_R2020A_UTM_10
Use conditions
Creative Commons Attribution 4.0 International 
Access conditions
No limitations 
URL 

  • This dataset corresponds to global map of built-up areas expressed in terms of a probability grid at 10 m spatial resolution derived from a Sentinel-2 global image composite (GHS_composite_S2_L1C_2017-2018_GLOBE_R2020A_UTM_10_v1_0) for reference year 2018. It builds on a new Deep Learning framework for pixel-wise large-scale classification of built-up areas named GHS-S2Net (GHS stands for Global Human Settlements, S2 refers to the Sentinel-2 satellite). Projection: Local UTM Data type:

    uint 8bit Built-up probability values rescaled in the range 0-100 Nodata value:

    255

GHS_BUILT_S2comp2018_GLOBE_R2020A Tiles schema
Use conditions
Creative Commons Attribution 4.0 International 
Access conditions
No limitations 
Download 

  • Tiles schema used to produce the GHS_BUILT_S2comp2018_GLOBE_R2020A

GHS_BUILT_S2comp2018_GLOBE_R2020A Metadata
Use conditions
Creative Commons Attribution 4.0 International 
Access conditions
No limitations 
Download 

  • GHS_BUILT_S2comp2018_GLOBE_R2020A products technical details

Voilà - JRC Big Data Plaform JEODPP
Access conditions
Registration required 
URL 

  • Visualization of the layer on JRC Big Data Plaform JEODPP (under Products/LandCover)

GHS_BUILT_S2comp2018_GLOBE_R2020A WMS
Use conditions
Creative Commons Attribution 4.0 International 
Access conditions
No limitations 
URL 

  • Web Mapping Service

Publications

Publication
Convolutional Neural Networks for Global Human Settlements Mapping from Sentinel-2 Satellite Imagery
Corbane, C., V. Syrris, F. Sabo, P. Politis, Michele Melchiorri, M. Pesaresi, P. Soille, and T. Kemper. “Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery". Neural Comput & Applic (2020). https://doi.org/10.1007/s00521-020-05449-7
URL 

Geographic areas

World

Spatial coverage

Type Value
WKT 
POLYGON((-179.99 84,179.99 84,179.99 -55.99,-179.99 -55.99,-179.99 84))

Temporal coverage

From date To date
2017-01-01 2018-12-31

Additional information

Published by
European Commission, Joint Research Centre
Created date
2020-10-22
Modified date
2020-10-28
Issued date
2020-10-31
Landing page
http://ghsl.jrc.ec.europa.eu/ 
Language(s)
English
Data theme(s)
Regions and cities, Population and society, Science and technology
Update frequency
irregular
Identifier
http://data.europa.eu/89h/016d1a34-b184-42dc-b586-e10b915dd863
Popularity