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oa Using Satellite Agricultural Monitoring Data for Assessing the Natural Afforestation of Farmlands at the Regional Level in Ukraine
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, International Conference of Young Professionals «GeoTerrace-2023», Oct 2023, Volume 2023, p.1 - 5
Abstract
The authors present a comprehensive assessment of the natural afforestation of farmlands at the regional level in Ukraine, utilizing Satellite Agricultural Monitoring Data (SAMD). Utilizing SAMD implemented in Ukraine since 2018 as part of the World Bank’s initiative “Supporting Transparent Land Governance in Ukraine,” we examine the scope, rate and spatial extent of afforestation occurring on former farmlands. This paper primarily focuses on the evaluation of land-use transitions resulting from the afforestation of previously cultivated farmlands, employing the SAMD. The study’s outcomes are validated at the regional level through a case study, specifically within the Myroslavska community of the Berdychiv District, Zhytomyr Region. Employing SAMD, the analysis demonstrates that from 1996 to 2019, within the Myroslavska community as a case study, the proportion of agricultural land decreased from 65% to 58%, while forested areas increased from 19% to 26%, primarily attributed to the process of natural afforestation of former farmlands. This research underscores the significance of utilizing satellite agricultural monitoring data for monitoring and assessing natural afforestation at a regional scale. The approach presented in this study can serve as a valuable tool for land managers, policymakers, and conservationists to make informed decisions regarding land use planning, afforestation incentives, and sustainable resource management. As Ukraine stands at the crossroads of agricultural transformation and environmental preservation, this study provides essential insights into the evolving landscape dynamics and points towards potential pathways for promoting natural afforestation within the region level.