2022-06-16, 13:30–13:50, Lobby - Poster session
If we simplify the picture of the world to an absolute minimum, we can say that there are only two remote sensing classes - urban areas and nature. A big part of the nature section is vegetation. Therefore, it is not a surprise that the vegetation detection, as well as the urban areas detection, constitutes a big part of remote sensing tasks, and very often these classes appear in remote sensing scenes together, side by side or within each other, separately or affecting one another. Such an effect can be seen in urban vegetated areas that could be either of natural or artificial origin and could serve different land use purposes. This talk focuses on seeing urban vegetation as one of two classes - for recreational purposes (such as public parks) and for other purposes (such as alleys or grass next to a road) - and explores whether we are able to determine such class from Sentinel-2 data using convolutional neural networks.
A PhD student at the CTU in Prague