Maryam Ao developed and integrated the Pandora Converter Site Classification feature for the JCSDA-internal/ioda-converters repository. She enhanced the converter to read a site classification CSV and assign urban classification and percentage urban values to Pandora observations based on geographic proximity, enriching the dataset with contextual information for downstream analytics. This work involved data conversion and processing using Python and Pandas, focusing on associating external classification data with observational records. Delivered as a single, end-to-end feature, the integration improved the utility of Pandora data for further analysis. The work demonstrated depth in data enrichment and contextual augmentation within scientific workflows.