Is dense or sprawl growth more prone to heat-related health risks? Spatial regression-based study in Delhi, India. (June 2022)

• Record Type: Journal Article
• Authors: Pramanik, Suvamoy; Punia, Milap; Yu, Hanchen; Chakraborty, Saurav
• Is Part Of: Sustainable cities and society. Volume 81(2022)
• Publication Date: 2022-06
• Subjects: Heat related health risk -- LISA -- Spatial regressions modeling -- Urban densification -- Spill-over effects; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2022.103808
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: Comprehensively assessed the heat-related health risk (HRHR) at ward level in Delhi for 2001 and 2017. The direct linkages between urban morphologies/ landscape metrics and HRHR were established by adopting spatial auto-correlation and spatial regression modeling. High built-up density positively correlated with elevated HRHR. Larger vegetation patches surrounded by dense built-up have less cooling efficiency during the night, hence not able to reduce HRHR. Spill-over effects found as most prominent than direct effects. SDM found most fitted among the adopted spatial regression models. Abstract: Rapid urban growth and land-use transformation has intensified urban heat island effects and exacerbated the heat-related health risk (HRHR). However, it remains debatable what are the interconnections between densification or sprawling and HRHR. Thus, the present study aimed at two crucial issues: 'whether the denser or sprawling growth is more prone to heat-related risk?' as well as 'what are the spatial interconnections or dependences of heat-risk on urban morphologies (ULM)' while taking Delhi as a case for the year 2001 & 2017. Four successive steps were followed (1) developing a comprehensive HRHR index adopting Crichton's risk triangle, (2) calculation of ULM and building a composite density index (DI), (3) testing correlation between HRHR and DI, (4) spatial autocorrelation and spatial regression modeling for exploring spatial dependence and interaction between ULM and HRHR. The result showed a strong positive correlation between DI and HRHR (R2 = 0.36 & 0.64 for 2001 and 2017, respectively). The models revealed ULM and HRHR as both spatially interconnected although spill-over, direct and total effect varies. The findings may contribute to the long-standing academic debate on 'dense growth' vs. 'sprawling growth' and help to effective heat-resilient LULC planning. Graphical abstract: Image, graphical abstract