A gridded dataset comprising value-added of primary, secondary and tertiary industries in China under shared socioeconomic pathways from 2020-2100

doi: 10.4121/14113706.v2
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/14113706
Datacite citation style:
jing, cheng; su, buda; tao, hui; zhai, jianqing; wang, yanjun et. al. (2022): A gridded dataset comprising value-added of primary, secondary and tertiary industries in China under shared socioeconomic pathways from 2020-2100. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/14113706.v2
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 2 - 2022-03-21 (latest)
version 1 - 2021-03-09
usage stats
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citations
6339
downloads
geolocation
China
lat (N): 18.25N-53.58N
lon (E): 73.50E-135.00E
time coverage
2020-2100
licence
cc-0.png logo CC0

The Cobb-Douglas production function is applied to project the output values of primary, secondary and tertiary industries in China at the provincial scale from 2020-2100 within the framework of shared socioeconomic pathways (SSPs). The provincial output value is re-allocated to grids at a 0.1 degree resolution based on the gridded land use and population. There are 15 files in total, which are saved in the form of. CSV. Each file is a combination of an industry sector and an SSP. In each file, the first and second columns are the longitude and latitude of the grids, respectively, and the first row is the year. Starting from the third column and the second row, the output value is given as a two-dimensional matrix in units of yuan.

history
  • 2021-03-09 first online
  • 2022-03-21 published, posted
publisher
4TU.ResearchData
format
ASCII
funding
  • National Key Research and Development Program of China MOST (2018FY100501)
organizations
School of Geographical Science, Nanjing University of Information Science & Technology

DATA

files (18)