An Updating System for the Gridded Population Database of China Based on Remote Sensing, GIS and Spatial Database Technologies

Pinliang Dong,Dong Jiang,Yaohuan Huang,Honghui Liu,Xiaohuan Yang

doi:10.3390/s90201128

Abstract

The spatial distribution of population is closely related to land use and land cover (LULC) patterns on both regional and global scales. Population can be redistributed onto geo-referenced square grids according to this relation. In the past decades, various approaches to monitoring LULC using remote sensing and Geographic Information Systems (GIS) have been developed, which makes it possible for efficient updating of geo-referenced population data. A Spatial Population Updating System (SPUS) is developed for updating the gridded population database of China based on remote sensing, GIS and spatial database technologies, with a spatial resolution of 1 km by 1 km. The SPUS can process standard Moderate Resolution Imaging Spectroradiometer (MODIS L1B) data integrated with a Pattern Decomposition Method (PDM) and an LULC-Conversion Model to obtain patterns of land use and land cover, and provide input parameters for a Population Spatialization Model (PSM). The PSM embedded in SPUS is used for generating 1 km by 1 km gridded population data in each population distribution region based on natural and socio-economic variables. Validation results from finer township-level census data of Yishui County suggest that the gridded population database produced by the SPUS is reliable.

Highlights

Demographic data is one of the most direct indexes of the influence of human activities on the planet Earth
Since Tobler et al released the first version of Gridded Population of the World (GPW) in 1995 [8], great progress has been made by many scientists and organizations in creating population databases
This paper focuses on the development of the Spatial Population Updating System (SPUS) for automated updating of annual gridded population databases based on land use and land cover (LULC) data derived from the Moderate Resolution Imaging

Summary

Introduction

Demographic data is one of the most direct indexes of the influence of human activities on the planet Earth. Application areas of demographic information include ecosystem assessment, global environmental changes, public health, and regional sustainable development studies [1,2,3,4,5,6,7]. Census datasets of administrative or statistical reporting units could not meet the needs of these applications because of (1) the low spatial resolution of the datasets, and (2) the long time interval between census years. A new concept of “population spatialization” was presented in a workshop on Global Demography in 1994 for redistributing population onto geo-referenced grids instead of political or administrative units [8,9].

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Results

Conclusion