Green space is an important part of urban ecology, and green space data will be used in many analyzes! We have shared the green area data of prefecture-level cities before (see the previous article for details), but many times we only know how many green areas a city has is not enough, we also need to know the spatial distribution of these green areas!
This time we bring you the green space data of 31 major cities in China ! The data was drawn by Shi Qian and other researchers from Sun Yat-sen University through deep learning methods based on Google Earth images and city boundary data! The data format is raster format (.tif).
The following is a detailed introduction to the data:
01 Visual display of urban green spaces
Let's take Beijing and Shanghai as examples to preview the data:
02 City List
The research scope of this data set is 31 major cities in China, including:
① Four municipalities directly under the central government: Beijing, Shanghai, Tianjin and Chongqing
②Capital cities of five autonomous regions: Hohhot, Nanning, Lhasa, Yinchuan and Urumqi
③The capital cities of 22 provinces in mainland China: Harbin, Changchun, Shenyang, Shijiazhuang, Taiyuan, Hefei, Lanzhou, Xining, Xi'an, Zhengzhou, Jinan, Changsha, Wuhan, Nanjing, Chengdu, Guiyang, Kunming, Hangzhou, Nanchang, Guangzhou, Fuzhou and Haikou
The thumbnails of the 31 major urban green areas are as follows:
03Data indicators
Data coordinates: WGS1984
Data format: .tif
Data download website: https://www.scidb.cn/en/detail?dataSetId=36af2aed281e4c82aa8a3cd3f1211a37
Data Introduction Paper: https://essd.copernicus.org/articles/15/555/2023/
数据引用方式：Shi, Q., Liu, M., Marinoni, A., and Liu, X.: UGS-1m: fine-grained urban green space mapping of 31 major cities in China based on the deep learning framework, Earth Syst. Sci. Data, 15, 555–577, https://doi.org/10.5194/essd-15-555-2023, 2023.
Data visualization method: The data includes two values of 0 and 255. Set the 0 value to no color, and set the 255 value to green to get the following effect:
Supplementary note: The author used the urban boundary (GUB) and GoogleEarth image data to draw the green space data , and the author also provided these two data. In addition, the author also provides a benchmark data set that supports UGS research . For these data, please download them from the data download website above!
At the bottom of the article is our official account business card. We will regularly introduce various urban data and data visualization and analysis technologies. For more details about the green space data of 31 major cities in China, you are welcome to pay more attention to us to learn ~