The UBBG dataset provides easily access and leverage to researchers and analysts, which is stored in the following Zenodo repository (https://doi.org/10.5281/zenodo.8053333). The UBBG dataset consists of two main components: UBGG-3m: the fine-grained UBGG map product of 36 metropolises in China. The UBGG-3m dataset captures the intricate urban landscape features with remarkable precision, providing a detailed representation at an impressive 3-meter resolution. Fig. 1 shows the classification results for 36 Chinese metropolises. Researchers can delve into the nuances of the UBBG continuum, gaining invaluable insights into the interplay between the blue, green, and gray elements of urban environments in each metropolis. UBGGset: the large-volume sample dataset to support the UGBB deep learning research. Complementing the UBGG-3m dataset, UBGGset serves as a large-volume sample dataset specifically tailored to support and foster UBBG research endeavors (Fig. 2). The UBGGset consists of 14,627 sample images (without data augmentation), with dimensions of 256 pixels in length and width, covering an urban area of approximately 2,272 km2. The UBGGset was constructed with co-registered pairs of 3 m Planet images and fine-annotated urban landscapes labeled on 1 m Google Earth image. This dataset encompasses 15 typical cities, offering researchers a rich and diverse resource to drive exploration, analysis, and innovation in the field of urban landscape studies.