Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China

Maomao Zhang, Cheng Zhang, Abdulla-Al Kafy and Shukui Tan
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Maomao Zhang: College of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, China
Cheng Zhang: College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213022, China
Abdulla-Al Kafy: Department of Urban & Regional Planning, Rajshahi University of Engineering & Technology, Rajshahi 6203, Bangladesh
Shukui Tan: College of Public Administration, Huazhong University of Science and Technology, Wuhan 430079, China

Land, 2021, vol. 11, issue 1, 1-17

Abstract: 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 °C will rise to 52.925% and 55.219%, and the affected area with the temperature >35 °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.

Keywords: land use/land cover changes; urban thermal environment; machine learning algorithms; artificial neural network; Wuhan (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (3)

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