Aggregated hedonic dataset with a green index: Busan, South Korea

We provide an aggregated dataset for investigating the association between hedonic variables and property prices in the Busan Metropolitan City of South Korea. This hedonic dataset includes various factors that influence property prices such as property characteristics, environmental amenities, local built environments, local demographic characteristics, and seasonal controls. In this dataset, we introduce the green index, which quantifies the degree of urban street greenness exposed to residents and pedestrians using images from Google Street View. In addition, the spatial interpolation method is employed to resolve the nonuniform distribution issue of the source images. To encourage the reusability of the dataset, we provide data and code files in a convenient manner. Therefore, the aggregated hedonic dataset can be readily benchmarked in property appraisal and urban studies and utilized in geographic information system fields.