This dataset is the basic supporting data for the Green Carrying Capacity and Sustainable Development Decision Support Platform APP Ecological Master V1.0. The data mainly comes from the 2015-2022 National Provincial and Municipal Statistical Yearbook, and the ecological carrying capacity data is provided by relevant scientific research departments (the dataset includes relevant explanations). The dataset provides data on social economy, agricultural products, resource consumption, pollution emissions, ecological carrying capacity, etc. from 2015 to 2022 at the provincial, municipal, and county levels in China, including 3637 data fields. The data mainly covers the period from 2015 to 2022. As statistical yearbooks may include continuous historical data for certain indicators, some data may include data before 2015, up to 1950 at the earliest. The population and gross domestic product data of some regions include data for 2023.
This dataset is sourced from:
1) 2015-2022 National Statistical Yearbook at the Provincial and Municipal Levels (unless otherwise specified, all sources are from this source);
2) China Western Environmental and Ecological Science Data Center（ http://westdc.westgis.ac.cn ）；
3) National Glacier, Frozen Soil and Desert Science Data Center（ http://www.ncdc.ac.cn )；
4) National Qinghai Tibet Plateau Science Data Center;
5) Institute of Geochemistry, Chinese Academy of Sciences;
6) Institute of Northeast Geography and Agroecology, Chinese Academy of Sciences;
7) Institute of Northwest Plateau Biology, Chinese Academy of Sciences.
1) Collect EXCEL versions of statistical yearbooks provided by third parties for each administrative region from 2015 to 2022, or perform OCR recognition of statistical yearbooks to form a complete sequence of EXCEL files for statistical yearbooks;
2) Process EXCEL files by retaining only relevant tables such as social economy, agricultural products, resource consumption, pollution emissions, ecological carrying capacity, natural disasters, etc., and removing other data to reduce data processing volume;
3) Manually organize various table formats in EXCEL files to form standard tables that comply with certain rules, making them easy to read and process programmatically;
4) Develop a program to extract table data from all files, classify and merge them according to fields, and unify measurement units during the merging process;
5) Program interpretation extracts abnormal data for manual interpretation and correction;
6) Manually inspect abnormal data and make corrections;
7) Other sources of data are programmed and written based on different fields.
Due to differences in statistical content and continuity across different regions, data gaps and discontinuities are more common. In western provinces, this problem is particularly prominent. In addition, there may be many data errors in the dataset due to source data errors, source data measurement unit errors, OCR recognition data errors, data extraction errors, etc. Although various measures have been taken in the production process of the dataset to reduce erroneous data, due to the large amount of data, it is not possible to eliminate all errors. Attention should be paid to discernment during the use of data.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.NCDC.NIEER.DB6550.2024
10.12072/ncdc.nieer.db6550.2024
