The Urban Heat Island (UHI) effect occurs when an urban area experiences higher temperatures than its rural surrounding because of heat being absorbed by built structures and heat being released by anthropogenic sources. UHIs can cause adverse effects to human health and increase energy consumption used for cooling buildings. Therefore, it is important to monitor accurately the UHI effect. The intensity of UHIs are usually monitored using satellite imagery, airborne sensors, and surface temperature sensors. Satellite imagery can cover a large area but requires a clear sky to obtain good images. Moreover, airborne sensors are expensive and also require a clear sky to obtain good data. A large network of surface temperature sensors is required to monitor the UHI of an entire region, which can also be expensive. In this paper, we present a three-step algorithm to monitor UHI intensity using data from Global Navigation Satellite Systems (GNSS). The advantages of using GNSS data to monitor the UHI effect are the increased availability of observation data, high temporal resolution and high geographical resolution. The first step of the algorithm is the calculation of a priori environmental parameters (i.e., water vapour partial pressure, troposphere height, surface pressure, and the vertical profile of refractivity) from radiosonde data. The second step is the calculation of temperature from GNSS data. The last step is the UHI intensity computation. The algorithm presented in this paper has been tested and validated using publicly available GNSS and meteorological data from Los Angeles, California, USA. The validation of the algorithm is done by comparing the UHI intensity estimated from the algorithm with temperature data obtained from weather stations. In the validation, the proposed algorithm can achieve an accuracy of 1.71 °C at 95 % confidence level.

当城市区域的温度高于其农村周围环境的温度时，就会发生城市热岛效应（UHI），这是因为建筑结构吸收了热量，人为源释放了热量。UHI会对人体健康造成不利影响，并增加用于建筑物散热的能耗。因此，准确监视UHI效果很重要。UHI的强度通常使用卫星图像，机载传感器和表面温度传感器进行监控。卫星图像可以覆盖很大的区域，但需要晴朗的天空才能获得良好的图像。此外，机载传感器价格昂贵，并且还需要晴朗的天空才能获得良好的数据。需要大型的表面温度传感器网络来监视整个区域的UHI，这也可能很昂贵。在本文中，我们提出了一个三步算法，可使用来自全球导航卫星系统（GNSS）的数据监控UHI强度。使用GNSS数据监视UHI效果的优点是增加了观测数据的可用性，高时间分辨率和高地理分辨率。该算法的第一步是计算探空仪数据的先验环境参数（即水蒸气分压，对流层高度，表面压力和折射率的垂直剖面）。第二步是根据GNSS数据计算温度。最后一步是UHI强度计算。本文提供的算法已使用可公开获得的GNSS和来自美国加利福尼亚州洛杉矶的气象数据进行了测试和验证。通过将根据算法估算的UHI强度与从气象站获得的温度数据进行比较，可以完成算法的验证。在验证中，提出的算法在95％的置信度下可以达到1.71°C的精度。