Supply–Demand Analysis of Urban Emergency Shelters Based on Spatiotemporal Population Estimation

Abstract

Supply–demand analysis is an important part of the planning of urban emergency shelters. Using Pudong New Area, Shanghai, China as an example, this study estimated daytime and nighttime population of the study area based on fine-scale land use data, census data, statistical yearbook information, and Tencent user-density big data. An exponential function-based, probability density estimation method was used to analyze the spatial supply of and demand for shelters under an earthquake scenario. The results show that even if all potential available shelters are considered, they still cannot satisfy the demand of the existing population for evacuation and sheltering, especially in the northern region of Pudong, under both the daytime and the nighttime scenarios. The proposed method can reveal the spatiotemporal imbalance between shelter supply and demand. We also conducted a preliminary location selection analysis of shelters based on the supply–demand analysis results. The location selection results demonstrate the advantage of the proposed method. It can be applied to identify the areas where the supply of shelters is seriously inadequate, and provide effective decision support for the planning of urban emergency shelters.

Keywords

Big data / China, population estimation / Probability density estimation / Supply–demand analysis / Urban emergency shelters

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