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Population Spatialization in Beijing City Based on Machine Learning and Multisource Remote Sensing Data
2020
Remote Sensing
Remote sensing data have been widely used in research on population spatialization. Previous studies have generally divided study areas into several sub-areas with similar features by artificial or clustering algorithms and then developed models for these sub-areas separately using statistical methods. These approaches have drawbacks due to their subjectivity and uncertainty. In this paper, we present a study of population spatialization in Beijing City, China based on multisource remote
doi:10.3390/rs12121910
fatcat:mbh4bjxtdrbaljaqyphweqhvm4