Department of History2024-12-292023979-835030351-310.1109/Agro-Geoinformatics59224.2023.102336782-s2.0-85172206965https://doi.org/10.1109/Agro-Geoinformatics59224.2023.10233678https://hdl.handle.net/20.500.14288/21896Global Land Cover (LC) datasets are important geo-information sources for environmental, climate, agriculture, and landscape applications. The ESA WorldCover project (2020 and 2021) provides a global scale land cover map with the predefined 11 generic classes for almost the current state. This study aims to evaluate the accuracy of the ESA LC data for a local region in Lalapasa/Edirne to provide insights into this data for possible local-level applications. Our study revealed that while the grassland, shrubland, and bare classes have inaccuracies that need to be further addressed, tree cover, water bodies, and cropland LC classified were correctly mapped for the studied region. We proposed strategies to improve the accuracy of some classes in the ESA LC map with integrated usage of open geospatial datasets and object-based classification. We encourage merging segments with their best-fitting surrounding segments if they are smaller than a minimum mapping unit of 1 ha. By doing this, we aim to improve the representation of the integrity and compactness of built-up regions and agricultural lands. © 2023 IEEE.Land useFarmlandLand cover changeConference proceedingN/A40010