Abstract
In this work, we examined the accuracy of identifying various types of land use and land cover using the remote sensing data for Kyiv to determine the territory occupied by urban greenery. Sentinel-1 SAR data, Sentinel-2 MSI data, and a combination of both were used. Classes were assigned using three different Machine Learning Algorithms. The Enhanced Vegetation Index was used to divide urban greenery into zones depending on the amount of green biomass.
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