Spatio-Temporal Features of Urban Heat Island and Its Relationship with Land Use/Cover in Mountainous City: A Case Study in Chongqing

The urban heat island (UHI) becomes more and more serious with the acceleration of urbanization. Many researchers have shown interest in studying the UHI by using remote sensing data, but these studies rarely examine the mountainous cities. Studies on UHI in mountainous cities often used empirical p...

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Bibliographic Details
Main Authors: Chunxia Liu, Yuechen Li
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Sustainability
Subjects:
Online Access:http://www.mdpi.com/2071-1050/10/6/1943
Description
Summary:The urban heat island (UHI) becomes more and more serious with the acceleration of urbanization. Many researchers have shown interest in studying the UHI by using remote sensing data, but these studies rarely examine the mountainous cities. Studies on UHI in mountainous cities often used empirical parameters to estimate the land surface temperature (LST), and lacked satellite-ground synchronous experiments to test the accuracy. This paper revised the parameters in the mono-window algorithm used to retrieve the LST according to the characteristics of mountainous cities. This study examined the spatial and temporal patterns of the UHI intensity in Chongqing, a typical mountainous city, and its relationship with land cover from 2007 to 2016 based on the Landsat 5 TM and Landsat 8 TIRS data and the improved method. The accuracy of the LST derivation increased by about 1 °C compared to the traditional method. The high LST areas increased and extended from the downtown to suburban area each year, but the rate of change decreased. The UHI is dramatically impacted by the rivers. There is a good relationship between the urban sprawl and the UHI. The LST was reduced by about 1 °C within a 300 m distance from large urban fringe green spaces. The urban landscape parks had a strong effect relieving the UHI at a 100 m distance. The LST was reduced by about 0.5 °C. This study greatly improves the accuracy of LST derivation, and provides reliable parameters for the UHI researched in mountainous cities.
ISSN:2071-1050