Population Spatial Distribution Based on Luojia 1-01 Nighttime Light Image:A Case Study of Beijing  

作　　者：SUN Lu WANG Jia CHANG Shuping 

机构地区：[1]Institute of GIS,RS&GPS,Beijing Forestry University,Beijing,100083,China [2]Beijing Key Laboratory of Precise Forestry,Beijing Forestry University,Beijing,100083,China

出　　处：《Chinese Geographical Science》2021年第6期966-978,共13页中国地理科学（英文版）

基　　金：Under the auspices of Natural Science Foundation of China(No.42071342,31870713);Beijing Natural Science Foundation Program(No.8182038);Fundamental Research Funds for the Central Universities(No.2015ZCQ-LX-01,2018ZY06)。

摘　　要：With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban development.By mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and visualized.It will provide a basis for a more rational urban planning.This paper takes Beijing as the research area and uses a new Luojia1-01 nighttime light image with high resolution,land use type data,Points of Interest(POI)data,and other data to construct the population spatial index system,establishing the index weight based on the principal component analysis.The comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in 2018.Then the population spatial distribution was visualize using GIS technology.After accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached 0.74.The proposed method was validated as a qualified method to generate population spatial maps.By contrast of local areas,Luojia 1-01 data is more suitable for population distribution estimation than the NPP/VIIRS(Net Primary Productivity/Visible infrared Imaging Radiometer)nighttime light data.More geospatial big data and mathematical models can be combined to create more accurate population maps in the future.

关 键 词：Luojia1-01 nighttime light image principal component analysis points of interest landuse type data population spatial distribution 

分 类 号：C922[社会学—人口学] P237[天文地球—摄影测量与遥感]