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Which Gridded Population Data Product Is Better? Evidences from Mainland Southeast Asia (MSEA)

Datos Bibliográficos

ID22032041
AutoresXu Yin (0000-0003-2498-4115, Chinese Academy of Sciences), Peng Li (0000-0002-7138-430X, Chinese Academy of Sciences), Zhiming Feng (0000-0002-3682-4955, Chinese Academy of Sciences, autor de correspondencia), Yanzhao Yang (0000-0002-1131-7711, Chinese Academy of Sciences), Zhen You (0000-0001-8477-5142, Chinese Academy of Sciences), Chiwei Xiao (0000-0003-3477-9406, Chinese Academy of Sciences)
Año2021
Volumen10
Número10
Páginas681
Fecha de publicación2021-10-09
Open AccessSí
TipoARTICLE
RevistaISPRS International Journal of Geo-Information (JOURNAL)
Identificadores de la revistaISSN: 2220-9964 • E-ISSN: 2220-9964
EditorialMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi10100681
OpenAlexW3207513507
IdiomaEN
Citas recibidas11
Referencias citadas31

The release of global gridded population datasets, including the Gridded Population of the World (GPW), Global Human Settlement Population Grid (GHS-POP), WorldPop, and LandScan, have greatly facilitated cross-comparison for ongoing research related to anthropogenic impacts. However, little attention is paid to the consistency and discrepancy of these gridded products in the regions with rapid changes in local population, e.g., Mainland Southeast Asia (MSEA), where the countries have experienced fast population growth since the 1950s. This awkward situation is unsurprisingly aggravated because of national scarce demographics and incomplete census counts, which further limits their appropriate usage. Thus, comparative analyses of them become the priority of their better application. Here, the consistency and discrepancy of the four common global gridded population datasets were cross-compared by combing the 2015 provincial population statistics (census and yearbooks) via error-comparison based statistical methods. The results showed that: (1) the LandScan performs the best both in spatial accuracy and estimated errors, then followed by the WorldPop, GHS-POP, and GPW in MSEA. (2) Provincial differences in estimated errors indicated that the LandScan better reveals the spatial pattern of population density in Thailand and Vietnam, while the WorldPop performs slightly better in Myanmar and Laos, and both fit well in Cambodia. (3) Substantial errors among the four gridded datasets normally occur in the provincial units with larger population density (over 610 persons/km2) and a rapid population growth rate (greater than 1.54%), respectively. The new findings in MSEA indicated that future usage of these datasets should pay attention to the estimated population in the areas characterized by high population density and rapid population growth

Cartography · Census · Geography · Mainland · Population · Population density · Statistics · Demography · Human Mobility and Location-Based Analysis · Impact of Light on Environment and Health · Land Use and Ecosystem Services · Mathematics

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Citas por año2,75
Intervalo de citas2022 - 2026 (5)
Altamente citadoNo

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