Abstract
The urban heat island (UHI) effect can contribute to extreme heat exposure. This can be detrimental to human health. In this paper, we propose a method to estimate air temperature to evaluate the spatial distribution and to monitor the intensity of the air urban heat island (AUHI) from existing GPS infrastructure. The proposed algorithm is based on the relationship between the refractivity of the troposphere and environmental variables, as well as the relationships between the zenith tropospheric delay (ZTD), a by-product of the precise point positioning technique, and the refractivity of the troposphere. The advantage of GPS data is its high temporal resolution and the availability of embedded GPS receivers. In this paper, GPS-derived ZTD data from stations in the Hong Kong Special Administrative Region (HKSAR) of China and Tokyo in Japan are processed to estimate the hourly AUHI intensity. The results derived from this technique are validated using meteorological data in the same cities. Mean absolute error values of 0.79 °C in Hong Kong and 0.22 °C in Tokyo are found from data from the summer. Moreover, an overall accuracy of 0.51 °C is found.
Highlights
The urban heat island (UHI) is a direct consequence of urbanization and industrialization, and is detected when an urban area is warmer than its rural surroundings [1]
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The temperatures estimated with Global Positioning System (GPS) data in Hong Kong and Tokyo were used to compute the spatial distribution of the AUHI intensity (AUHII) at day and night during the summer in both cities
Summary
The urban heat island (UHI) is a direct consequence of urbanization and industrialization, and is detected when an urban area is warmer than its rural surroundings [1]. The UHI based on air temperatures (AUHI) is monitored using a network of ground-based temperature sensors from weather stations in urban and rural areas [7]. Estimated hourly temperatures are used to assess the diurnal cycle of the air urban heat island (AUHI) in Hong Kong (HK) and Tokyo. There were 6055 billion smartphone users in the world as of 2020 [14], and each smartphone has an embedded GPS receiver This GPS-data-based method has great practical potential to be implemented in smartphones and make spatial AUHI data available for big data applications. Other studies have used data from the meteorological networks provided by the Hong Kong Observatory to study the AUHI [20,21] In both cases, the weather station in the Hong Kong Observatory’s headquarters in Tsim Sha Tsui was considered as an urban station. The AUHI in Tokyo has been measured using machine learning techniques and JMA data from 2015–2019 [26]
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