气候变化领域集成服务门户(CCPortal): Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China

CCPortal

DOI	10.1016/j.uclim.2022.101347
	Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China
	Zhang, Maomao; Abdulla-Al Kafy; Xiao, Pengnan; Han, Siyu; Zou, Shangjun; Saha, Milan; Zhang, Cheng; Tan, Shukui
发表日期	2023
ISSN	2212-0955
卷号	47
英文摘要	The impact of the rapid expansion of urban land on the urban thermal environment and carbon chain has attracted widespread attention. This paper uses artificial neural network-cellular automata (ANN-CA) and long short-term memory model of the improved whale optimization algorithm (IWOA-LSTM) models to predict the changes of LULC and LST, and explores the cor-relation between LST and carbon emissions in Wuhan.The results show that urban land will occupy >70.05% of the central urban area, while green land and water areas will continue to decrease to varying degrees in 2030 and 2040. The area of the high temperature area (LST > 30 degrees C) is expanding in the urban land, while the green land and the low temperature area of the water body are gradually shrinking. The area of high temperature is expanding, and the area with LST > 30 degrees C accounts for 67.84% in summer, and the area with LST at 10 degrees C similar to 15 degrees C accounts for 96.32% in winter. The fitting results of correlation regression show that there is a significant correlation between carbon emissions and LST. The R-2 of linear fitting between LST and carbon emissions in summer and winter of 2000 are 0.6227 and 0.6143, respectively. The R-2 of linear fitting in summer and winter is higher, both of which are >0.85 in 2010 and 2020. This research may provide new clues for future urban development and thermal environment governance and carbon emission mitigation.
英文关键词	Urban expansion; Thermal environment; Carbon emission; ANN -CA; IWOA-LSTM; China
语种	英语
WOS研究方向	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS类目	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000953119500001
来源期刊	URBAN CLIMATE
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280863
作者单位	Huazhong University of Science & Technology; University of Texas System; University of Texas Austin; Central China Normal University; Bangladesh University of Engineering & Technology (BUET); Independent University Bangladesh (IUB); Huazhong University of Science & Technology
推荐引用方式 GB/T 7714	Zhang, Maomao,Abdulla-Al Kafy,Xiao, Pengnan,et al. Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China[J],2023,47.
APA	Zhang, Maomao.,Abdulla-Al Kafy.,Xiao, Pengnan.,Han, Siyu.,Zou, Shangjun.,...&Tan, Shukui.(2023).Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China.URBAN CLIMATE,47.
MLA	Zhang, Maomao,et al."Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China".URBAN CLIMATE 47(2023).