Population Distribution Dataset in Provincial Level of Mainland Southeast Asia (2000-2020)
YIN Xu1,3,4WEI Hui*2
1 School of Geographic Science，Hebei Normal University，Shijiazhuang 050024，China2 School of Public Administration of Hebei University of Economics and Business，Shijiazhuang 050061，China3 GeoComputation and Planning Center of Hebei Normal University，Shijiazhuang 050024，China4 Hebei Key Laboratory of Environmental Change and Ecological Construction，Shijiazhuang 050024，China
DOI:10.3974/geodb.2023.03.07.V1
Published:Mar. 2023
Visitors：1421 Data Files Downloaded：94
Data Downloaded：812.12 MB Citations：
Key Words：
Population,Mainland Southeast Asia,provincial,spatio-temporal distribution
Abstract：
The population distribution dataset in provincial level of Mainland Southeast Asia (2000-2020) was developed based on the census data in 2000, 2005, 2010, 2015 and 2020 released by the governments of Mainland Southeast Asia (Cambodia, Laos, Myanmar, Thailand and Vietnam) and the administrative boundary data in provincial level of each of the five countries. The LandScan was used for the data pre-processing. The dataset consists of the total population of 198 provinces from Cambodia, Laos, Myanmar, Thailand and Vietnam in 2000, 2005, 2010, 2015 and 2020. The dataset was archived in .shp and .xlsx data formats, consisting of 7 data files with data size of 16 MB (Compressed to one file with 8.63 MB).
Foundation Item：
Hebei Normal University (L2023B36); Hebei Education Department (BJK2023081)
Data Citation：
YIN Xu, WEI Hui*.Population Distribution Dataset in Provincial Level of Mainland Southeast Asia (2000-2020)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2023. https://doi.org/10.3974/geodb.2023.03.07.V1.
References：
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[3] Liu, Y., Li, P., Yin, X., et al. Dynamic characteristics of correlation between agricultural and forest active fires and population density in Mainland Southeast Asia [J/OL]. Tropical Geography, 2023: 1-13. [2023-03-03]. DOI: 10.13284/j.cnki.rddl.003565.
[4] Feng, Z. M., Li, P. Review of population geography in the past century [J]. Progress in Geography, 2011, 30(2): 131-140.
[5] Yin, X., Li, P., Feng, Z. M., et al. Which gridded population data product is better? evidences from Mainland Southeast Asia (MSEA) [J]. ISPRS International Journal of Geo-Information, 2021, 10(10): 681.
[6] Burke, M., Driscoll, A., Lobell, D. B., et al. Using satellite imagery to understand and promote sustainable development [J]. Science, 2021, 371: 6535.
[7] Wan, Z. H. Research on the evolution and driving factors of the population spatial pattern in Myanmar [D]. Yunnan University of Finance and Economics, 2021.
[8] Yin, X., Wang, J., Li, Y. R., et al. Spatio-temporal evolution and driving factors of Chinese population at town level [J]. Geographical Research, 2022, 41(5): 1245-1261.
[9] Oak Ridge National Laboratory. LandScan datasets [DB/OL]. https://landscan.ornl.gov/.
Data Product:
| ID |
Data Name |
Data Size |
Operation |
| 1 |
ProvPopMainlandSEAsia2000-2020.rar |
8846.97KB |
|