Abstract
Abstract. Direct heat and moisture conditions can lead to discomfort for humans and animals and can decrease health performance. The discomfort index or temperature-humidity index (THI) represents an important indicator that measures the heat sensed by humans for different climate conditions. In extreme situations, heatstroke may occur, which in unfortunate cases will lead to death. Many research studies have been conducted on the urban heat island (UHI) phenomenon, although a majority of such work focuses on regional-scale analyses and emphasizes the thermal trend through larger administrative units. Fewer micro-scale analyses have been performed at the local scale to detect the potential area for increased THI within a city. This work seeks to estimate the THI at the micro-scale level by utilizing the thermal camera on-board of unmanned aerial systems (UASs). Thermal information of the surface and visual images are collected by the UAS, while a thermohygrometer is used to collect the air temperature and the relative humidity at the ground surface for ground truth information. Solar radiation and wind exposure modeled from digital surface model (DSM) and normalized difference vegetation index (NDVI) data are used as explanatory variables, and a random forest machine learning method is implemented to model the spatial distribution of the THI. The results and discussion will provide future possibilities for micro-scale analyses of the UHI.
Highlights
In recent years, as an urban environmental problem, the urban heat island (UHI) phenomenon that accompanies urbanization has become prominent in Japan and in other countries around the world
We focus on developing a new method for observing and estimating temperature-humidity index (THI) mapping at an extreme micro-scale unit by utilizing the unmanned aerial systems (UASs) and satellite remote sensing data
This work has focused on modeling the temperature-humidity index (THI) at a micro-scale unit by utilizing various remote sensing data obtained from both unmanned aerial system (UAS) and satellite data
Summary
As an urban environmental problem, the urban heat island (UHI) phenomenon that accompanies urbanization has become prominent in Japan and in other countries around the world. UHI is a cause of increased tropical nights and associated health hazards, such as heatstroke in urban areas, changes in ecosystems due to the overwintering of mosquitoes that carry infectious diseases, and extreme torrential rains (Deilami et al, 2018). It is a serious problem that greatly affects urban space environments and leads to associated health issues (Royé, 2017). To understand the human sensations associated with different climatic conditions, various indices are prepared that consider both temperature and humidity. With the increasing development of urban areas leading to the expansion of hotter areas in combination with a changing climate, more threats to health will occur. Determining the heat hotspots or the distribution of THI in urban areas (i.e., where is the area exposed to higher discomfort) has become an issue. The results are tabulated to determine the trend for the whole city or district
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