This channel would release Beijing, or the whole China, micro-data and maps (e.g. road networks, parcels, human mobility, historical city maps) for the BCL research fellows and external researchers. There are three levels of data access, free download, email request, and shared among research fellows / student members.
How to cite:
Beijing City Lab, Year, Data ID, Data Name, http://www.beijingcitylab.com
E.g. Beiing City Lab, 2013, Data 8, Housing price in Beijing, http://www.beijingcitylab.com
(For the dataset from external source other than BCL, we would recommend you to cite the original source)
44 Walk score of all main Chinese cities
2022
We are sharing the year-2014 “Walk Score” in GIS Shapefiles for more than 700,000 streets in 287 main cities (at or above prefecture-level) in mainland China. The Walk Scores range from 0 to 100, where 100 indicates the highest walkability. Please unzip the following two files and put them in the same directory and in this way you will be able to open the GIS file.
Eleven attributes are available in the data, including walk score of the street (WS), ID of the street (STREET_ID), ID of the city (CITY_ID), name of the city in Chinese (NAME), name of the city in pinyin (PINYIN), level of the city (CITY_LEVEL), street segment length in meters (LENGTH_M), width of the road in meters (width_m), function density (function_d), function mix (function_m), as well as junction density (junction_d).
Please cite the following paper when you use our data in your study.
龙瀛,赵健婷,李双金,周垠,许留记.中国主要城市街道步行指数的大规模测度[J].新建筑,2018(03):4-8.
The visualization of the data is available at our GeoHey portal.
(https://legacy.geohey.com/portal/dataviz/7ee371d5e8db4ca89d5816306ecebcc5)
43 Urban vacant land of 36 major Chinese cities
2022
The data include two parts: (1) urban vacant land of 36 major Chinese cities (in shapefile format), and (2) codes and data used for automatic vacant land identification.
Urban vacant land is a growing issue worldwide. The study is aimed to realize large-scale automatic identification of urban vacant land. A framework based on deep learning techniques is proposed to extract urban vacant land of 36 major Chinese cities through semantic segmentation of high-resolution remote sensing images. The automatic identification framework is proved to be accurate and efficient, with strong robustness. This method is expected to serve as a practical approach in various countries and regions. The data of urban vacant land of 36 cities can be used in further studies.
42 Functional urban areas of China
2020
We are sharing the Didi car hailing records derived functional urban areas of China in the format of GIS ShapeFiles. Please cite our paper when you use the data.
Ma S, Long Y. 2020. Functional urban area delineations of cities on the Chinese mainland using massive Didi ride-hailing records. Cities, 97: 102532.
41 Urban blocks in 63 Chinese cities
2020
We are sharing 141375 street blocks in 63 Chinese cities in 2017 in the format of GIS ShapeFiles. The data depicts street block scale three-dimensional attributes of these Chinese cities. They were computed using the 3.357 million large-scale three-dimensional building data (footprint with floor number).
The visualization of the data is available at our GeoHey portal.
Eleven attributes are available in the data, including ID of the block (PARCEL_ID), name of cities (CITY_NAME), number of buildings (BLD_Count), average floor number (BLD_FLOORN), average floor area ratio (BLD_FAR), average building density (BDL_bldDen), types of street block form (FORM_TYPE), the blocks in the CBD (In CBD), dominant function (FUNCTION), density of function (DENSITY), and mixing degree of function (MIX).
Please cite the following paper when you use our data in a study.
龙瀛,李派,侯静轩.基于街区三维形态的城市形态类型分析——以中国主要城市为例.上海城市规划,2019(03):10-15.
Ying Long, Pai Li, Jingxuan Hou. “Three-Dimensional urban form at the street block level for major cities in China.” Shanghai Urban Planning Review, 2019(3): 10-15.