Supervised LULC Classification – Kyiv, Ukraine

 This self-directed Land Use/Land Cover (LULC) classification project was developed using QGIS and the Semi-Automatic Classification Plugin (SCP) to demonstrate my proficiency in satellite image analysis. The map presents a supervised classification of Sentinel-2 imagery over Kyiv, Ukraine, highlighting distinct land cover types such as built-up areas, vegetation, and water bodies. I sourced the raster data from an open-access satellite imagery platform, collected training samples based on visual interpretation and known land cover features, and performed the classification to produce a clean and informative thematic map.