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Corrected population grid data using multisource high precision data.

Shuang Wang1,2, Chun Dong3, Rong Zhao1

  • 1Chinese Academy of Surveying and Mapping, Beijing, China.

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Summary
This summary is machine-generated.

This study enhances population grid data accuracy using multisource high-precision data. The improved data offers a more reliable foundation for ecological planning and environmental monitoring.

Keywords:
Corrected populationHigh precision geographicMultisource dataPopulation gridPublic population gridWorldPop

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Area of Science:

  • Geographic Information Systems (GIS)
  • Environmental Science
  • Demography

Background:

  • Population grid data is crucial for ecological planning, environmental monitoring, and emergency response.
  • Existing methods using administrative units have cross-scale errors, and current datasets lack fine-grained regional detail.
  • There is a need for enhanced population distribution data with improved accuracy and regional specificity.

Purpose of the Study:

  • To develop and present a methodology for correcting public population grid data.
  • To enhance the accuracy and regional specificity of population distribution datasets.
  • To improve the scientific basis for ecological and environmental applications.

Main Methods:

  • Utilized WorldPop as baseline population grid data.
  • Developed a new model to incorporate multisource high-precision auxiliary data for correction.
  • Applied the methodology at the grid scale for enhanced population allocation.

Main Results:

  • The corrected population grid data showed a significant decrease in Root Mean Square Error (RMSE), exceeding sevenfold.
  • Achieved a high coefficient of determination (R² ) of 0.997, indicating substantial data quality improvement.
  • Demonstrated enhanced regional fine-grained characteristics and population distribution accuracy.

Conclusions:

  • The proposed methodology effectively corrects public population grid data.
  • The enhanced population grid data offers superior quality for ecological and environmental applications.
  • This advancement provides a more reliable foundation for scientific research and decision-making.