Identifying design shortcomings and heat-island effects in schools located in warm climates: An outdoor environmental assessment procedure based on remote sensing tools

2021 ◽  
pp. 103209
Author(s):  
Antonio Serrano-Jiménez ◽  
Julia Hiruelo-Pérez ◽  
Emilio Ramírez-Juidias ◽  
Ángela Barrios-Padura
Author(s):  
Qijiao Xie ◽  
Jing Li

As a nature-based solution, development of urban blue-green spaces is widely accepted for mitigating the urban heat island (UHI) effect. It is of great significance to determine the main driving factors of the park cool island (PCI) effect for optimizing park layout and achieving a maximum cooling benefit of urban parks. However, there have been obviously controversial conclusions in previous studies due to varied case contexts. This study was conducted in Wuhan, a city with high water coverage, which has significant differences in context with the previous case cities. The PCI intensity and its correlation with park characteristics were investigated based on remote sensing data. The results indicated that 36 out of 40 urban parks expressed a PCI effect, with a PCI intensity of 0.08~7.29 °C. As expected, larger parks with enough width had stronger PCI intensity. An increased density of hardened elements in a park could significantly weaken PCI effect. Noticeably, in this study, water bodies in a park contributed the most to the PCI effect of urban parks, while the vegetated areas showed a negative impact on the PCI intensity. It implied that in a context with higher water coverage, the cooling effect of vegetation was weakened or even masked by water bodies, due to the interaction effect of different variables on PCI intensity.


Author(s):  
Valentino Sangiorgio ◽  
Alessandra Capolupo ◽  
Eufemia Tarantino ◽  
Francesco Fiorito ◽  
Mattheos Santamouris

2019 ◽  
Vol 45 ◽  
pp. 686-692 ◽  
Author(s):  
Niloufar Shirani-bidabadi ◽  
Touraj Nasrabadi ◽  
Shahrzad Faryadi ◽  
Adnan Larijani ◽  
Majid Shadman Roodposhti

2018 ◽  
Vol 11 (1) ◽  
pp. 48 ◽  
Author(s):  
Decheng Zhou ◽  
Jingfeng Xiao ◽  
Stefania Bonafoni ◽  
Christian Berger ◽  
Kaveh Deilami ◽  
...  

The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms/sensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI/LST variability at a local scale. The Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+)/Thermal Infrared Sensor (TIRS) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite/sensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions/cities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.


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