Shrinking Cities Identification Data

Overview / 数据概述

Shrinking Cities Identification Data / 收缩城市识别数据合集 consolidates five locally preserved research packages used to identify and compare shrinking cities in China and worldwide. The collection covers nighttime-light change, population-census comparison, global gridded population change and multi-source validation at the physical-city scale. Historical archive filenames are retained so that earlier references remain traceable; every public download is served locally from the .org website.

本数据合集汇集了五个由BCL本地保存并完成核验的收缩城市识别数据包，覆盖夜间灯光变化、人口普查比较、全球格网人口变化以及实体城市尺度的多源数据检验。公开文件保留历史压缩包名称，便于与既有论文和旧档案对应；所有下载均由.org网站本地提供。

Files & Coverage / 文件与范围

1. JUPD_Data.zip: natural-city boundaries supporting NPP-VIIRS identification of 2,862 Chinese natural cities during 2013-2016, including 798 shrinking cities. / 支持基于NPP-VIIRS夜间灯光识别2013-2016年中国2,862个自然城市，其中798个为收缩城市。
2. EPA_DATA_GLOBE_SCs.zip: global natural-city point data with population attributes for 2000 and 2019, supporting the identification of 5,004 shrinking cities worldwide, including 679 in China. / 包含2000年和2019年人口属性的全球自然城市点数据，支持识别全球5,004个收缩城市，其中中国679个。
3. EPA_DATA_CHINA_SCs.zip: county-level tables comparing China's sixth and seventh population censuses for the 2010-2020 identification of shrinking administrative units and cities. / 用于比较中国第六次和第七次人口普查、识别2010-2020年收缩行政单元与城市的区县人口表。
4. iSciencePaperDataResults.zip: global historical shrinking-city results derived from harmonized nighttime-light and natural-city boundaries, with benchmark layers for 1990, 2000, 2010 and 2015 and the study's 2050 projection context. / 基于统一夜间灯光和自然城市边界形成的全球历史收缩城市结果，包括1990、2000、2010和2015年基准图层，并对应论文中的2050年预测情景。
5. IdentificationResults.zip: population-change results for 2,444 physical cities during 2010-2020, with fields derived from DMSP-VIIRS, LandScan, WorldPop and Baidu data. / 2,444个实体城市2010-2020年人口变化识别结果，包含DMSP-VIIRS、LandScan、WorldPop和百度数据形成的变化率字段。

Method / 方法

The component studies use consistent spatial-city units rather than relying only on administrative boundaries. They identify shrinkage through negative population change or sustained nighttime-light decline, and compare results across remote sensing, census and gridded-population sources. Users should retain each package's original spatial unit, period, field definitions and threshold when conducting comparisons. / 各项研究尽可能采用实体城市或自然城市空间单元，而非仅依赖行政边界；通过人口负增长或持续夜间灯光衰减识别收缩，并在遥感、人口普查和格网人口数据之间进行比较。开展跨数据比较时，应保留各数据包原有的空间单元、时间范围、字段定义和识别阈值。

How to Cite / 标准引用

1. Jiang, Z., Zhai, W., Meng, X., & Long, Y. (2020). Identifying shrinking cities with NPP-VIIRS nightlight data in China. Journal of Urban Planning and Development, 146(4), 04020034. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000598
   Associated data file / 对应数据文件： JUPD_Data.zip
2. Meng, X., Jiang, Z., Wang, X., & Long, Y. (2021). Shrinking cities on the globe: Evidence from LandScan 2000-2019. Environment and Planning A: Economy and Space, 53(6), 1244-1248. https://doi.org/10.1177/0308518X211006118
   Associated data file / 对应数据文件： EPA_DATA_GLOBE_SCs.zip
3. Meng, X., & Long, Y. (2022). Shrinking cities in China: Evidence from the latest two population censuses 2010-2020. Environment and Planning A: Economy and Space, 54(3), 449-453. https://doi.org/10.1177/0308518X221076499
   Associated data file / 对应数据文件： EPA_DATA_CHINA_SCs.zip
4. Zhai, W., Jiang, Z., Meng, X., Zhang, X., Zhao, M., & Long, Y. (2022). Satellite monitoring of shrinking cities on the globe and containment solutions. iScience, 25(6), 104411. https://doi.org/10.1016/j.isci.2022.104411
   Associated data file / 对应数据文件： iSciencePaperDataResults.zip
5. 王新宇, 龙瀛. (2024). “城区常住人口”在收缩城市识别中的特点——基于文献综述和多源数据的检验. 地理研究, 43(7), 1929-1939. https://doi.org/10.11821/dlyj020240054
   Associated data file / 对应数据文件： IdentificationResults.zip

Related Future Projection / 相关未来预测

The 2020-2100 global projection study provides the future context for this collection: Wang, X., & Long, Y. (2023). Future shrinking cities on the globe: A projection map for 2020-2100 based on global gridded population dataset. Environment and Planning B: Urban Analytics and City Science, 50(7), 1994-1997. https://doi.org/10.1177/23998083231186153. See also Data 045: global 1-km population projections.