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CHANGES IN THE SPATIAL DISTRIBUTION OF VEGETATION COVER CLASSES IN UKRAINE BASED ON TEMPORAL DATA FROM SPACE SURVEY UNDER MODERN CLIMATE CONDITIONS

Lesya Yelistratova, Igor Onopchuk, Alexander Apostolov, Yulia Zakharchuk

First published: 2025-08-15https://doi.org/10.5593/sgem2025/2.1/s09.15View metrics

Abstract

The article presents the results of using multi-zone space survey materials from different spacecraft to distinguish different types of land cover and establish their boundaries and changes in their sizes over time. Space images from Sentinel, Landsat, Proba V, and TERRA/MODIS devices were used, which differ in spatial resolution, rotation frequency, and orbital period. Changes in the sizes of the established types of land cover over time are an indicator that allows assessing the nature and intensity of the impact of anthropogenic and natural climatic factors, which is necessary for the rational use of natural resources and the prevention of environmental disasters. The studies were carried out at two scale levels - at the level of Ukraine as a whole and the level of known natural zones. Images from the TERRA/MODIS satellite for 2001-2023 were mainly use. To identify changes in the vegetation cover of Ukraine, various classifications were used, compiled by various international organizations. The results of the research were obtained in quantitative form. In general, the results of the classification of land covers within the territory of Ukraine do not contradict ground observations but only complement them. The established changes in the areas occupied by different classes of vegetation allowed us to calculate changes in CO2 absorption by different classes of land covers during the study period.

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Publication details

Title
CHANGES IN THE SPATIAL DISTRIBUTION OF VEGETATION COVER CLASSES IN UKRAINE BASED ON TEMPORAL DATA FROM SPACE SURVEY UNDER MODERN CLIMATE CONDITIONS
Authors
Lesya Yelistratova, Igor Onopchuk, Alexander Apostolov, Yulia Zakharchuk
Proceedings
25th International Multidisciplinary Scientific GeoConference Proceedings SGEM 2025, Geoinformatics, Remote Sensing, and Artificial Intelligence (AI), Vol 25, Issue 2.1
Publisher
STEF92 Technology
Year
2025
Pages
119-126
SWS Citekey
Yelistratova20259119126
ISSN
1314-2704; 13142704
ISBN
9786197603897
Language
en
Publication type
Conference Paper
Proceedings contents
Open official contents
Keywords
References14
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