Urban green spaces (UGSs) play a crucial role in mitigating climate change by offsetting carbon dioxide (CO2) emissions. Despite their importance, the carbon storage (CS) function and spatiotemporal mapping of residential green spaces have received limited research attention. This study examines three newly developed residential areas in the Budapest Agglomeration. Using very highresolution orthophotography imagery and stereophotographic vegetation height data, combined with a tree height-carbon storage model, the study mapped the spatiotemporal characteristics of CS in residential green spaces from 2015 to 2022. The findings reveal notable variations in CS across newly developed residential areas over the seven years. It provides landscape planners with valuable theoretical guidance on how to accurately understand, locate and enhance the CS function of residential green spaces. The study also identifies a significant positive correlation between green space percentage changes and CS overall. However, poorly planned increases in green space percentage can adversely affect CS capacity. In the context of global warming, this research presents a high-precision, transferable methodology for spatiotemporal monitoring of CS, which can be adapted to other urban areas. This approach provides a robust framework for supporting sustainable urban development and informing climate change mitigation strategies. In Hungary this study contributes to the introduction of the instrument called “green certificate” which is planned to be the tool that makes green space planning more relevant and efficient.