English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

A study of parkland in Abakan and Chernogorsk cities, located in the steppe zone and characterized by a high level of atmospheric pollution. Plant taxa are identified that make the greatest contribution to the purification of the urban environment. The most common tree plants in the parkland are adventitious species  Populus alba  L.,  P. balsamifera  L.,  Acer negundo  L.,  Sorbaria sorbifolia  (L.) A. Braun,  Syringa vulgaris  L.,  Ulmus pumila  L. et al. In the flora of parks and squares of Abakan, 288 species of higher vascular plants belonging to 59 families and 183 genera were identified. The flora of parkland in Chernogorsk totals 142 species belonging to 33 families and 105 genera. Leading position belongs to the largest families – Asteraceae, Poaceae, Rosaceae and Fabaceae. An analysis of satellite data made it possible to remotely determine the functional state, phenological changes, and weather sensitivity of green zone vegetation. As a result of the studies, the general and seasonal indicators of the vegetation and water index were analyzed according to the satellite data (Landsat 8) for the territories of Abakan and Chernogorsk located in the steppe zone of Khakasia. Abakan had higher values of the integral NDVI (45.1-57.9), in comparison with Chernogorsk (11.4-14.2), better water supply and earlier dates of the beginning of the growing season. Based on satellite data, the productivity of green zones was compared and the regression dependences of spectral and meteorological indicators were identified.