Stochastic Spatial Binary Simulation with Multivariate Normal Distribution for Illustrating Future Evolution of Umbrella-Shape Summer Shelter under Climate Change

Abstract

Surface temperature has increased due to the impact of climate change, and the related weather events, such as heat waves and urban heat island, are occurring more frequently than before. Local governments and planners consider these impacts of climate change and try to avoid them. One of the mainly used structural tools is building summer shelters. A critical issue for urban planners is to test how many shelters should be added and how to distribute the shelters to cope with the impact of climate change. Stochastic simulation models can be a good option to randomize locations of shelters and to see how beneficial for living the shelters can be. Therefore, a novel stochastic simulation model is proposed for distributing summer shelters for coping with the climate change impact. This study proposes a stochastic spatial binary simulation with multivariate normal distribution (SSBM) which contains two major procedures consisting of (1) simulation-based derivation of the empirical function and (2) stochastic simulation of spatial binary data with multivariate normal distribution and the derived empirical function. The proposed model is applied to a case study in Jinju City, South Korea, for the umbrella-shape summer shelters (USS). Results concluded that the proposed SSBM reproduced the statistical characteristics of USS and can be a good alternative to model the locations of USS, including the impact of climate change and investigating the evolution of the USS in the future.