Impact of climate change on the area of major crops
Heading:
| 1Yemelyanov, MO, 2Shelestov, AYu., 2Yailymova, HO, 1Shumilo, LL 1Space Research Institute of the NAS of Ukraine and SSA of Ukraine, Kyiv, Ukraine 2National Technical University of Ukraine «Igor Sikorsky Kyiv Polytechnic Institute», Kyiv, Ukraine |
| Space Sci. & Technol. 2022, 28 ;(2):30-38 |
| https://doi.org/10.15407/knit2022.02.030 |
| Publication Language: Ukrainian |
Abstract: In this work, a statistical analysis of the time series of areas of majoritarian crops for 20 years (from 1998 to 2020) is carried out, and the influence of agro-climatic zones on the area of cultivation of major crops is analyzed. Climate change is acutely felt in the southern regions of Ukraine, increasing the production risk in the agricultural sector through changes in temperature, precipitation, and other extreme weather events. Historical climatic data indicate an increase in temperature on the territory of Ukraine, and climate forecasts suggest further warming, especially in the south of Ukraine.
Using satellite and statistical data, changes in the earth’s surface are investigated for certain areas, which are characterized by the greatest changes in crop areas for the main types of crops. To analyze the dynamics of cultivated areas in relation to climatic zones, we used national statistical data for 1998–2019, maps of the classification of land cover from 2016—2020, data on climatic zones on the territory of Ukraine for 2000 and 2020, as well as the contours of administrative units of the NUTS2 level. Since statistical data for many districts are not available for the period 2019 – 2020 due to the reform of territorial boundaries, we used instead cultivated areas obtained from open satellite records. As additional and alternative information for the analysis of acreage, crop classification maps for 2016–2020 were used, obtained by specialists of the Space Research Institute of the National Academy of Sciences of Ukraine and the State Space Agency of Ukraine from their own in-depth training technologies.
We used classification maps obtained using open satellite data of the Copernicus program: SAR Sentinel-1 and Sentinel-2 with a spatial resolution of 10 m. A comparison of statistical data and crop areas obtained from satellite data was carried out by applying the metric of statistical analysis of the correlation coefficient (r). To assess the accuracy, the coefficient of determination R2 between the statistical area of the main crops and the area according to satellite data was also applied.
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| Keywords: classification maps, climate change, deep learning, satellite data, Sentinel-1, Sentinel-2 |
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