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

作     者：SUN Lu WANG Jia CHANG Shuping SUN Lu;WANG Jia;CHANG Shuping

作者机构：Institute of GISRS&GPSBeijing Forestry UniversityBeijing100083China Beijing Key Laboratory of Precise ForestryBeijing Forestry UniversityBeijing100083China 

出 版 物：《Chinese Geographical Science》 (中国地理科学（英文版）)

年 卷 期：2021年第31卷第6期

页      面：966-978页

核心收录：

学科分类：083002[工学-环境工程] 02[经济学] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 081802[工学-地球探测与信息技术] 0201[经济学-理论经济学] 020106[经济学-人口、资源与环境经济学] 08[工学] 0818[工学-地质资源与地质工程] 081602[工学-摄影测量与遥感] 0816[工学-测绘科学与技术] 

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) 

主　　题：Luojia1-01 nighttime light image principal component analysis points of interest landuse type data population spatial distribution 

摘      要：With the continuous development of urbanization in China,the country’s growing population brings great challenges to urban *** mastering the refined population spatial distribution in administrative units,the quantity and agglomeration of population distribution can be estimated and *** will provide a basis for a more rational urban *** 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 *** comprehensive weight value of population distribution in the study area was then used to calculate the street population distribution of Beijing in *** the population spatial distribution was visualize using GIS *** accuracy assessments by comparing the result with the WorldPop data,the accuracy has reached *** proposed method was validated as a qualified method to generate population spatial *** 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 *** geospatial big data and mathematical models can be combined to create more accurate population maps in the future.