气候变化领域集成服务门户(CCPortal): WBGT prediction with high spatial resolution using actual measurement data and data acquired using infrared sensors mounted on UAVs

CCPortal

DOI	10.1016/j.scs.2024.105470
	WBGT prediction with high spatial resolution using actual measurement data and data acquired using infrared sensors mounted on UAVs
	Niwa, Hideyuki; Manabe, Ryoko
发表日期	2024
ISSN	2210-6707
EISSN	2210-6715
起始页码	107
卷号	107
英文摘要	Spatial understanding of heat stress indices is important to prevent the worsening of heat-related health problems. The objective of this study is to understand heat stress indices with high spatial and temporal resolution using actual measurement data and data acquired using infrared sensors mounted on unmanned aerial vehicles (UAVs). Two study sites were established to examine the relationship between green space and heat stress indices and the versatility of the developed method. The wet bulb globe temperature (WBGT), a heat stress index, was measured on extremely hot days. Thermal infrared, the normalized difference vegetation index, and the normalized difference water index were obtained from UAV images. Extreme gradient boosting, a supervised machine learning method for gradient boosting decision trees, was used to predict the WBGT for the study area using data from actual measurement points as training data. The maximum and average root mean square errors of the predicted WBGT were 2.8 and 1.4, respectively. The second measurement session, which was closest to noon, showed a greater WBGT reduction effect because of vegetation and moisture. This study successfully predicted the WBGT with high spatial and temporal resolution. This achievement is expected to contribute to the prevention of heat stress.
英文关键词	Heat stress index; WBGT; Infrared sensor; UAV; XGBoost
语种	英语
WOS研究方向	Construction & Building Technology ; Science & Technology - Other Topics ; Energy & Fuels
WOS类目	Construction & Building Technology ; Green & Sustainable Science & Technology ; Energy & Fuels
WOS记录号	WOS:001235553900001
来源期刊	SUSTAINABLE CITIES AND SOCIETY
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/295820
推荐引用方式 GB/T 7714	Niwa, Hideyuki,Manabe, Ryoko. WBGT prediction with high spatial resolution using actual measurement data and data acquired using infrared sensors mounted on UAVs[J],2024,107.
APA	Niwa, Hideyuki,&Manabe, Ryoko.(2024).WBGT prediction with high spatial resolution using actual measurement data and data acquired using infrared sensors mounted on UAVs.SUSTAINABLE CITIES AND SOCIETY,107.
MLA	Niwa, Hideyuki,et al."WBGT prediction with high spatial resolution using actual measurement data and data acquired using infrared sensors mounted on UAVs".SUSTAINABLE CITIES AND SOCIETY 107(2024).