GHS built-up grid, derived from Sentinel-2 global image composite for reference year 2018 using Convolutional Neural Networks (GHS-S2Net)
built-up grid derived from Sentinel-2 global image composite for reference year 2018 using Convolutional Neural Networks (GHS-S2Net).
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).
Download the GHS-BUILT-S2 R2020A dataset.
Dataset:
Corbane, Christina; Sabo, Filip; Politis, Panagiotis; Syrris Vasileos:
GHS-BUILT-S2 R2020A - 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) (2020)
PID:
http://data.europa.eu/89h/016d1a34-b184-42dc-b586-e10b915dd863
,
doi:10.2905/016D1A34-B184-42DC-B586-E10B915DD863
Concept & Methodology:
Corbane, C., Syrris, V., Sabo, F. et al.
Convolutional neural networks for global human settlements mapping from Sentinel-2 satellite imagery. Neural Comput & Applic (2020).
doi:10.1007/s00521-020-05449-7