{"title":"A study on residential population estimation based on HJ-1 CCD image","authors":"Siqi Jia, Qi Li, Shuai Liu, Lei Xue","doi":"10.1109/EORSA.2012.6261184","DOIUrl":null,"url":null,"abstract":"This study firstly built a linear spectral unmixing model based on image data of HJ-1 satellites (Environment and Disaster monitoring and forecasting Satellite constellation) to derive impervious surface coverage data in Beijing. Then combined with street population census data in Beijing, we can build Beijing population density estimation model for population distribution estimation. The corresponding abundance information of the street impervious surface is derived by geographic information system (GIS) overlay of street data and impervious surface data, to build the population density estimation model based on the information of the impervious surface by the regression analysis. The result shows that the population density estimation model built based on the information of the impervious surface is a reliable method for estimating the population density in Beijing and the feasibility of this method is demonstrated.","PeriodicalId":132133,"journal":{"name":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Second International Workshop on Earth Observation and Remote Sensing Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EORSA.2012.6261184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study firstly built a linear spectral unmixing model based on image data of HJ-1 satellites (Environment and Disaster monitoring and forecasting Satellite constellation) to derive impervious surface coverage data in Beijing. Then combined with street population census data in Beijing, we can build Beijing population density estimation model for population distribution estimation. The corresponding abundance information of the street impervious surface is derived by geographic information system (GIS) overlay of street data and impervious surface data, to build the population density estimation model based on the information of the impervious surface by the regression analysis. The result shows that the population density estimation model built based on the information of the impervious surface is a reliable method for estimating the population density in Beijing and the feasibility of this method is demonstrated.