CBRA: The first multi-annual (2016-2021) and high-resolution (2.5 m) building rooftop area dataset in China derived with Super-resolution Segmentation from Sentinel-2 imagery
Description
Large-scale and up-to-date maps of building rooftop area (BRA) are crucial for addressing policy decisions and sustainable development. In addition, as a fine-grained indicator of human activities, BRA could contribute to urban planning and energy modeling to provide benefits to human well-being. However, existing large-scale BRA datasets, such as those from Microsoft and Google, do not include China, hence there are no full-coverage maps of BRA in China. To this end, we produce the multi-annual China building rooftop area dataset (CBRA) with 2.5 m resolution from 2016-2021 Sentinel-2 images. The CBRA is the first full-coverage and multi-annual BRA data in China. The CBRA achieves good performance with the F1 score of 62.55% (+10.61% compared with the previous BRA data in China) based on 250,000 testing samples in urban areas, and the recall of 78.94% based on 30,000 testing samples in rural areas.
The CBRA is organized as GeoTIFF (.tif) raster file format with a single band and GCS_WGS_1984 coordinate system. The pixel values are 0 and 255, with 0 representing the background and 255 representing the building rooftop area. Furthermore, to facilitate the use of the data, the CBRA is split into 215 tiles of spatial grid, named “CBRA_year_E/W**N/S**.tif”, where “year” is the sampling year, the “E/W**N/S**” is the latitude and longitude coordinates found in the upper left corner of the tile data.
The code to generate CBRA can be found here: https://github.com/zpl99/STSR-Seg
Files
CBRA_2016.zip
Files
(23.1 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:4483fb1b3aaa7f4a25402163ee0dd468
|
3.4 GB | Preview Download |
|
md5:5f48a0f4fc0569dda478417304a48466
|
3.6 GB | Preview Download |
|
md5:d7fd8ad988975e4b8ca178f4029163fa
|
3.6 GB | Preview Download |
|
md5:a84af46b4bdd7cfaf87f6a069c232984
|
3.9 GB | Preview Download |
|
md5:8726f018a77f42697a96378dc80febfa
|
4.1 GB | Preview Download |
|
md5:10cbc07861623011541bdd13693baed2
|
4.5 GB | Preview Download |