Reprint

Geographical Analysis and Modeling of Urban Heat Island Formation

Edited by
November 2023
368 pages
  • ISBN978-3-0365-9274-9 (Hardback)
  • ISBN978-3-0365-9275-6 (PDF)

This book is a reprint of the Special Issue Geographical Analysis and Modeling of Urban Heat Island Formation that was published in

Engineering
Environmental & Earth Sciences
Summary

This Special Issue explores the fascinating topic of urban heat islands (UHIs), examining them from temporal and spatial perspectives. We embark on a journey that focuses on the essential impacts of UHI formations, including land use composition, city characteristics, and anthropogenic factors. Our objective is to raise awareness of the many facets of UHIs and their significant effects on urban environments and sustainability. This collective aim is to further strengthen urban sustainability through a deeper understanding of UHI dynamics. This volume includes a wide range of topics related to UHIs, including cutting-edge methods and datasets for capturing UHI phenomena. We investigate the spatial interactions between UHI intensity and land use/cover distribution within metropolitan areas, examine the geographic patterns and processes underlying UHIs in sprawling cities, and analyze the spatial differences in UHI intensity between developing and developed countries. Additionally, we focus on UHI catastrophe mitigation and adaptation measures, which are crucial for setting sail for a sustainable urban future. Finally, we engage in the critical work of prediction and scenario analysis, equipping policymakers and urban planners with the insights necessary for informed decision-making. We express our thanks to the researchers, academics, and contributors who have made this Special Issue possible as we begin this investigation into urban heat islands. We aim to foster a comprehensive understanding of UHIs and contribute to the broader discourse on urban sustainability.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
cooling effect; distance analysis; landscape pattern; urban heat island; urban lake; land surface temperature; spatial analysis; urban agglomeration; driving factors; geo-detector metric; urban heat island (UHI); land use land cover (LULC); land surface temperature (LST); spatiotemporal changes; SUHI-contributing factors; satellite imagery; literature review; Surface Urban Heat Island (SUHI); Land Surface Temperature (LST); Principal Component Analysis (PCA); Multiple Linear Regression (MLR); Machine Learning; Naïve Bayes; land surface temperature; greenspace spatial patterns; landscape metrics; spatial autoregressive model; seasonal variation; functional construction land zones; urban thermal environment; differential surface temperature; environmental indicators; Shenzhen; surface urban heat island; SUHI; land surface temperature; LST; seasonal hysteresis; MODIS; ESA-CCI; Köppen–Geiger climate zones; urbanization; surface urban heat island; land surface temperature; sustainable cities; green space; impervious surface; Kathmandu; temporal and spatial variation; land surface temperature; Zhengzhou city; urban heat island; land surface temperature; neighboring environment; seasonal effect; scale effect; optimal spatial scale; urban heat island; extreme gradient boosting regression; urban vegetation; urban heat island effect; landscape patterns; spatial correlation; Landsat 8; urban thermal security pattern; surface temperature; circuit theory; research framework; Wuhan urban agglomeration; China; thermal environment; heat island intensity; spatio-temporal characteristics; local spatial pattern; land use; regression analysis; LST; mono-window algorithm; land indices; correlation coefficients; directional profiling; SUHI; hotspots (Getis–Ord Gi* statistics); MODIS night-time LST; Prayagraj city; air quality; GeoDetector; habitat quality; thermal environment; urban agglomeration; urban remote sensing; land surface temperature; urbanization; sustainable cities; impervious surface; spatial analysis