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Published paper in MDPI’s Remote Sensing Journal

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I am pleased to announce that our paper regarding the computation of Indicator 11.7.1 was published in Remote Sensing this week!

Our paper was part of the Special Issue Artificial Intelligence and Earth Observation in Support of the UN Sustainable Development Goals and is entitled A Cloud-Based Mapping Approach Using Deep Learning and Very-High Spatial Resolution Earth Observation Data to Facilitate the SDG 11.7.1 Indicator Computation.

Check it out at: https://www.mdpi.com/2072-4292/14/4/1011

Citation:

Verde, N.; Patias, P.; Mallinis, G. A Cloud-Based Mapping Approach Using Deep Learning and Very-High Spatial Resolution Earth Observation Data to Facilitate the SDG 11.7.1 Indicator Computation. Remote Sens.2022, 14, 1011. https://doi.org/10.3390/rs14041011

Map produced from the study: Urban extent of the Athens Metropolitan Area, according to the UN methodology, land allocated to streets
(LAS) and urban open spaces (UOS)
Maps produced from the study: Urban open spaces (UOS) mapped in experiment 1 (a,b) and in experiment 2 (c,d), in
densely built‐up areas (a,c) and in green suburbs of the city (b,d).
Maps produced from the study: Omission errors in the LAS product in (a) the industrial region of Athens, (b) in the old
city (Plaka).

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