Combined Effects of the Surface Urban Heat Island with Landscape Composition and Configuration Based on Remote Sensing: A Case Study of Shanghai, China

Abstract

Rapid urbanization leads to changes in surface coverage and landscape patterns. This results in urban heat island (UHI) effects and a series of negative ecological consequences. Considering this concern and taking Shanghai as an example, this paper concentrates on the effects of surface coverage and landscape patterns on urban land surface temperature (LST). The research is based on quantitative retrieval of remote sensing data with consideration of methods in multiple disciplines, including landscape ecology, geographic information systems, and statistical analysis. It concludes that, over time, the thermal environment of Shanghai is becoming critical. The average LST ranking of different surface coverage is as follows: Construction land (CL) > bare land (BL) > green land (GL) > agricultural land (AL) > water body (WB). LST varies significantly with the type of surface coverage. CL contributes the most to the UHI, while WB and GL have obvious mitigation effects on the UHI. The large area, low degree of landscape fragmentation, and complex outlines lead to low LST rankings for GL, WB, and AL and a high LST ranking for CL. The conclusions indicate that CL should be broken down by GL and WB into discrete pieces to effectively mitigate UHI effects. The research reveals UHI features and changes in Shanghai over the years and provides practical advice that can be used by urban planning authorities to mitigate UHI.

Spatial Configuration and Extent Explains the Urban Heat Mitigation Potential due to Green Spaces: Analysis over Addis Ababa, Ethiopia

“…Urban landscapes are composed of several diverse land cover varieties, while built-up and vegetated cover are two essential features in the UHI formation [48]. Accordingly, it is known that increasing the amount of green space can significantly reduce the ambient air and land surface temperature [16,43,44]. This correlation has been reported consistently and follows the first principle surface radiative flux balance at the surface.…”

“…Many studies have estimated LST from medium-resolution remotely sensed satellite data (e.g., Landsat) for long-term temperature observations from the early 1980s. For instance, the significant cooling effects of urban green space (UGS) spatial patterns on the urban heat have been widely demonstrated by previous researches [22,24,35,[44][45][46][47]. Spatial pattern encompasses composition (the amounts and diversities of land cover types), as well as configuration (their distribution and structure).…”

Analisis Surface Urban Heat Island Menggunakan Teknik Penginderaan Jauh Berbasis Cloud Computing Pada Google Earth Engine Di Kota Samarinda

“…Hal yang hampir sama dilakukan oleh Bahi et al (2016), namun penelitian tersebut belum menunjukkan intensitas UHI yang terjadi, hanya visualisasi suhu permukaan darat (LST) yang dihubungkan dengan fenomena UHI dan dinamika penutup/penggunaan lahan. Penelitian yang lebih spesifik dilakukan oleh Du et al (2019) di Delta Sungai Yangtze dengan menghubungkan kombinasi efek surface urban heat island, komposisi dan konfigurasi bentanglahan. Penelitian tersebut menarik, namun intensitas SUHI yang menjadi fokus utama penelitian belum dijabarkan cara perolehannya, sementara pada visualisasi tabular justru masih menggunakan nilai suhu permukaan darat (LST).…”

Analysis of the Impact of Land Use on Spatiotemporal Patterns of Surface Urban Heat Island in Rapid Urbanization, a Case Study of Shanghai, China

“…The land use data, with a spatial resolution of 30 m, were obtained from RS images by supervised classification [40]. In order to improve the accuracy of the classification results, the land use data of Shanghai (Figure 3 Figure 4 indicates that the total area of the HTZ and SHTZ is expanding, while the LTZ and SLTZ are shrinking with the year.…”