Proceedings of International Conference on Applied Innovation in IT
2023/03/09, Volume 11, Issue 1, pp.67-73

Sustainable Development Goal 2.4.1 for Ukraine Based on Geospatial Data

Hanna Yailymova, Bohdan Yailymov, Yevhen Mazur, Nataliia Kussul and Andrii Shelestov

Abstract: In this work, the indicator of sustainable development goal (SDG) 2.4.1 for Ukraine is calculated based on geospatial and satellite data. The generally accepted technology for calculating the given indicator cannot be applied for the territory of Ukraine due to the lack of systematic collection of the necessary indicators. Therefore, the authors have developed the complex method for land degradation estimation that uses different schemes for separate land cover and crop types at the country level based on satellite and modeling data using WOFOST model. The paper describes the sources of information used to create crop type classification maps and the data required for leaf area index (LAI) modeling for the WOFOST model. Calculated indicators from 2018 to 2022 for each of the regions of Ukraine. In 2022, the decrease of the indicator is monitored in almost all regions of Ukraine, which is a direct result of military actions on the territory of Ukraine.

Keywords: Geospatial Data Analysis, Machine Learning, Land Degradation, Remote Sensing, Land Cover, SDG 2.4.1.

DOI: 10.25673/101915

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