Modeling the biophysical condition of the Ukrainian steppe zone using remote sensing data
Heading:
| 1Lubskyi, MS, 2Khyzhniak, AV, 1Orlenko, TA, 1Golubov, SI 1Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine 2State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine |
| https://doi.org/10.15407/knit2025.02.020 |
| Publication Language: English |
Abstract: The steppe zone of Ukraine is facing significant pressure due to global climate change and anthropogenic activities related to agriculture and mining. In addition, the full-scale russian invasion has caused war crimes that have had catastrophic consequences for the steppe ecosystems and the nature reserves, making conservation efforts even more urgent. In this regard, an urgent scientific task arises to develop a comprehensive approach to geospatial modeling of the biophysical condition of the steppe zone and identifying areas most vulnerable to climate challenges and damage.
The paper introduces a robust methodology for multi-criteria assessment and forecasting the conditions in the study area. This methodology is based on the selection of biophysical indicators obtained from remote sensing data. These indicators are ranked by their impact on the vulnerability and integrated into a single multi-criteria condition assessment using the analytic hierarchy process (AHP). The area state forecast is also performed based on a time series of the data for the research period (2015-2024). Much of the processing of large geospatial data sets was carried out using the Google Earth Engine platform and cloud data processing, ensuring the reliability and accuracy of the results.
As a result, a geospatial distribution of the values of biophysical conditions of the Ukrainian steppe zone was obtained, which revealed several regions particularly vulnerable to adverse climatic factors, including the south of
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| Keywords: analytic hierarchy process, biophysical condition, climate change, geospatial modeling, remote sensing, vulnerability indicator |
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