气候变化领域集成服务门户(CCPortal): A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations

CCPortal

DOI	10.5194/amt-15-735-2022
	A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations
	Chen, Shihan; Yang, Yuanjian; Deng, Fei; Zhang, Yanhao; Liu, Duanyang; Liu, Chao; Gao, Zhiqiu
发表日期	2022
ISSN	1867-1381
EISSN	1867-8548
起始页码	735
结束页码	756
卷号	15 期号:3
英文摘要	Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high-spatial-resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. Firstly, the observed environmental parameters, e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF), around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 degrees C. Then, the spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the decreasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high spatial and temporal resolution (30 m and 1 h) CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.
语种	英语
WOS研究方向	Meteorology & Atmospheric Sciences
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000758099900001
来源期刊	ATMOSPHERIC MEASUREMENT TECHNIQUES
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280867
作者单位	Wuhan University; Nanjing University of Information Science & Technology; China Meteorological Administration; China Meteorological Administration
推荐引用方式 GB/T 7714	Chen, Shihan,Yang, Yuanjian,Deng, Fei,et al. A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations[J],2022,15(3).
APA	Chen, Shihan.,Yang, Yuanjian.,Deng, Fei.,Zhang, Yanhao.,Liu, Duanyang.,...&Gao, Zhiqiu.(2022).A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations.ATMOSPHERIC MEASUREMENT TECHNIQUES,15(3).
MLA	Chen, Shihan,et al."A high-resolution monitoring approach of canopy urban heat island using a random forest model and multi-platform observations".ATMOSPHERIC MEASUREMENT TECHNIQUES 15.3(2022).