Regional and urban heat island studies in megacities: A systematic analysis of research methodology

Abstract

The paper provides a systematic review of satellite-based regional and urban heat island (RHI and UHI) studies in cities and their challenges, from 2010 to the present based on visualizing scientific landscapes (VOS) viewer analysis and Scopus and science database search using a set of standard criteria. The review results show that 52.17% of the studies used Landsat images followed by MODIS (36.65%). Based on VOS viewer analysis author keywords, remote sensing was strongly linked to urban heat island, urban greenspace, and improvise surface, respectively. Regarding, Co-authorship network China, Canada and the United kingdom’s authors actively collaborated with different world researchers. The most frequently studied regions and periods of research are China and summer daytime, respectively. A total of 55% of the articles reported the use of a mono-window algorithm for retrieving LST from sensors. On the other hand, remotely sensed UHI studies have been facing a series of challenges, including differences between remote sensing satellite-derived LST and air temperature, impacts of clouds and other factors on LST data, methods to quantify UHI, accuracy assessment and attribution of RHI and UHI. Thus, consideration was given to the understudied cities, the methods to compute RHI and/or UHI intensity, inter-annual variability and modeling in the future.

Are New Residential Areas Cooler than Older Ones?

“…In addition to this prospective nature, the findings in this study bridge pieces of knowledge related to precise house/building/material-scale experiments and regional analyses largely supported by remote sensing. Urban heat islands and suburban green areas have been intensively observed within 100 km 2 areas or greater regions [22]. The heat island phenomenon is elucidated by the current findings, which demonstrate the results of the precise passive cooling mechanisms generalized and systematized in the aforementioned review articles.…”

Dynamics of green spaces- Land surface temperature intensity nexus in cities of Ethiopia

“…Furthermore, the beginning of the years LULC change and LST map generation were linked to political and policy changes in Ethiopia, which were thought to have an impact on various aspects of the country's urban development [ 8 ]. The spatial resolution of the visible and near-infrared bands of Landsat is 30 m, while the spatial resolutions of the thermal infrared bands are 120, 60, and 100 m for TM, ETM+, Landsat 8 Thermal Infrared Sensor (TIRS), respectively ( http://earthexplorer.usgs.gov ) and the fusion temporal enhancement method were used to reconstruct the original LST products at normalized scales in this study [ 11 , 45 ]. Besides, for three decades (1990–2020), LULC dynamics datasets in this study were obtained from Ref.…”

“…This tendency is more frequent in developing countries and especially prevalent in Africa. Thus, characterizing the dynamics of UHI and UGS associations is critical for mitigating the ongoing negative effects of the climate crisis [ 11 , 56 ].…”

“…For example, UHI influence the interspecific phenotypic plasticity and larval survival of butterflies [ 32 ], slow the development of widow spider [ 30 ], and disturbs the health of urban residents [ 44 , 69 ] and persuade nonfatal effects such as dehydration, heat strokes, and heat fatigue [ 46 ]. Thus, understanding characteristics of the spatial distribution of LST and influencing factors of LST pattern and evolution are important for sustainable urban policies development [ 11 , 61 ] and reduce the unabated negative influences of climate crisis [ 8 , 56 , 62 ]. Even though some studies have been conducted, the results focused on the linear relationship between LST and single influencing factors, such as biophysical factors [ 67 ].…”

“…Even though some studies have been conducted, the results focused on the linear relationship between LST and single influencing factors, such as biophysical factors [ 67 ]. Specifically in Ethiopia, there are a few studies that are spatially limited and focused on single-factor analysis [ 9 , 11 , 20 , 63 ] and failed to disclose the comprehensive characterization of the LST-green space nexus [ 9 , 10 ]. In addition, a couple of issues of great importance serve to justify our research: 1) The analyzed cities do not have enough UGS-LST interlinks studies for responses with spatial and temporal variability.…”