Dynamic population surfaces from GPS data show double-disadvantaged zones for services in Hefei cluster in the inner suburban belt, with daytime job centers experiencing sharp rises in demand competition.
Predicting poverty and wealth from mobile phone metadata
2 Pith papers cite this work. Polarity classification is still indexing.
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Multilevel regression and poststratification corrects socioeconomic sampling bias in CDR mobility estimates, lowering average radius of gyration by 17 percent.
citing papers explorer
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The Moving Target of Urban Equity: Spatiotemporal Demand and Double Disadvantage in Hefei, China
Dynamic population surfaces from GPS data show double-disadvantaged zones for services in Hefei cluster in the inner suburban belt, with daytime job centers experiencing sharp rises in demand competition.
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Correcting socioeconomic bias in mobile phone mobility estimates using multilevel regression and poststratification
Multilevel regression and poststratification corrects socioeconomic sampling bias in CDR mobility estimates, lowering average radius of gyration by 17 percent.