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  4. Combining Sentinel-1 and Sentinel-2 data for the identification of urban greenery

Combining Sentinel-1 and Sentinel-2 data for the identification of urban greenery

Remote Sensing & GIS for Environmental Monitoring

Authors

First and Last Name Academic degree E-mail Affiliation
Vadym Belenok Ph.D. belenok.vadim [at] nau.edu.ua National Aviation University
Kyiv, Ukraine
Liliia Hebryn-Baidy Ph.D. liliya.gebrinbaydi [at] gmail.com National Aviation University
Kyiv, Ukraine
Oles Zheleznyak No oles.zhelezniak [at] nau.edu.ua National Aviation University
Kyiv, Ukraine
Sofiia Alpert Ph.D. sonyasonet87 [at] gmail.com Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Science of the National Academy of Sciences of Ukraine
Kyiv, Ukraine

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 21.08.2023 - 13:09
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.

Keywords 
land use and land cover
Sentinel-1
Sentinel-2
urban greenery
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