气候变化领域集成服务门户(CCPortal): Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China

CCPortal

DOI	10.3390/land11010014
	Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China
	Zhang, Maomao; Zhang, Cheng; Kafy, Abdulla-Al; Tan, Shukui
发表日期	2022
EISSN	2073-445X
卷号	11 期号:1
英文摘要	The changes of land use/land cover (LULC) are important factor affecting the intensity of the urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses cellular automata (CA) and artificial neural network (ANN) to predict future changes in LULC and LST. The results show that the built-up area of Wuhan has expanded, reaching 511.51 and 545.28 km(2), while the area of vegetation, water bodies and bare land will decrease to varying degrees in 2030 and 2040. If the built-up area continues to expand rapidly, the proportion of 30~35 degrees C will rise to 52.925% and 55.219%, and the affected area with the temperature >35 degrees C will expand to 15.264 and 33.612 km(2), respectively. The direction of the expansion range of the LST temperature range is obviously similar to the expansion of the built-up area. In order to control and alleviate UHI, the rapid expansion of impervious layers (built-up areas) should be avoided to the greatest extent, and the city's green development strategy should be implemented.
英文关键词	land use; land cover changes; urban thermal environment; machine learning algorithms; artificial neural network; Wuhan
语种	英语
WOS研究方向	Environmental Studies
WOS类目	Social Science Citation Index (SSCI)
WOS记录号	WOS:000746279000001
来源期刊	LAND
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/280650
作者单位	Huazhong University of Science & Technology; Hohai University; Rajshahi University of Engineering & Technology (RUET)
推荐引用方式 GB/T 7714	Zhang, Maomao,Zhang, Cheng,Kafy, Abdulla-Al,et al. Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China[J],2022,11(1).
APA	Zhang, Maomao,Zhang, Cheng,Kafy, Abdulla-Al,&Tan, Shukui.(2022).Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China.LAND,11(1).
MLA	Zhang, Maomao,et al."Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China".LAND 11.1(2022).