The estimation of population on multi-spatial scale using Tencent location big data

doi:10.13474/j.cnki.11-2246.2022.0178.

Abstract

Abstract: The diversity of social perception data brings new data and perspectives to the study of population estimation methods. In this paper, the multi-scale population spatial estimation is studied by Tencent location big data. With the volume data of construction land and residential area as the relevant factors, the 5 km grid is refined to 1 km and residential area level scale. By analyzing the correlation between Tencent location big data and demographic data at three different scales of Guangxi, Guilin and Lingui district, the spatial model of population at three scales is obtained by polynomial regression model analysis, and the correctness of the model is verified. The accuracy of the population estimation model is 0.984 5 on the scale of provincial level and 0.977 0 on the scale of city level, the verification accuracy is 0.979 9 in terms of community scale. The estimation results have high reliability.

Key words: Tencent location big data, population estimation, multi-scale, grid transformation

CLC Number:

P208

LI Huimin, LUO Dawei, DOU Shiqing. The estimation of population on multi-spatial scale using Tencent location big data[J]. Bulletin of Surveying and Mapping, 2022, 0(6): 93-97.

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