Застосування ГІС-технологій для оцінювання лісорекреаційних площ урбанізованих територій

The present paper assesses the availability of woody vegetation in the regional centres of the Carpathian regions of Ukraine (Ivano-Frankivsk, Uzhhorod, Chernivtsi and Lviv) using geographic information technologies. The study was conducted using the Normalised Difference Vegetation Index, or NDVI, to identify areas covered by woody vegetation on satellite images. Multispectral (13 bands) images of the European Space Agency's Sentinel-2A satellite were selected for the study, with the data obtained from the official website of the Copernicus space programme. The social and recreational value of areas covered with woody vegetation is critically important for urbanised areas; however, the actual provision of green areas lags far behind the established standards in all the settlements studied. The analysis of the data revealed that, among the regional centres of the Carpathian region, Lviv demonstrated the highest levels of woody vegetation coverage, followed by Chernivtsi, and Uzhhorod and Ivano-Frankivsk exhibited the lowest. The investigation further revealed that Chernivtsi exhibited the highest level of tree cover within the city, although this was almost half of the recommended standard. The remaining regional centres exhibit a provision of less than 30 per cent of the recommended minimum. Such deviations from the normative values necessitate a re-evaluation and implementation of contemporary approaches to the formation of green areas within the urban context. These areas function as a natural framework for the urban planning structure, performing recreational, sanitary, aesthetic, and social functions aimed at creating a healthy environment for living, working, and recreation. It is imperative to prioritise the augmentation of public green spaces, as this is a pivotal aspect in enhancing the overall quality of life within the city. Keywords: forest recreation area, forested areas, remote sensing, GIS technologies, satellite images, Sentinel-2, NDVI, QGIS.