Abstract
Aggregating crowd density in grids from big mobile datasets is a basic but critical work in urban computing and mobile computing. The error of position estimation in raw mobile data, including spatial deviation and temporal deviation, is inevitable and directly impacts the accuracy of aggregated crowd density results. In this case, a key modifiable areal unit problem is raised to understand the relationship among the crowd density accuracy, raw mobile data error, grid shape, and size, but few studies focused on it. In this chapter, we analyze this modifiable areal unit problem of the error in crowd density estimation from big mobility data. A real application for grided population distribution map construction and restoration from Call Detail Record was conducted to prove the reliability of the whole analysis.
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