This repository contains the code developed for mapping urban open spaces (UOS) and land allocated to streets (LAS) at the city level, using Planetscope and Sentinel-1 imagery and deep learning, for aiding the calculation of SDG indicator 11.7.1.
Urban open spaces (UOS) mapped using only Planetscope imagery (a,b) and using both Planetscope and Stneinl-1 (c,d), in densely built-up areas (a,c) and in green suburbs of the Athens metropolitan area (b,d)
Land Allocated to Streets (LAS) mapped in (a) the industrial region of Athens, (b) in the old city of Athens
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 Sensing. 2022; 14(4):1011. https://doi.org/10.3390/rs14041011
Verde N. Calculation and mapping of sustainable development goal indicators, using open-source earth observation data and cloud computing services. Dissertation. Aristotle University of Thessaloniki; 2023. http://dx.doi.org/10.12681/eadd/56272