Working PaperArticleVersion 1This version is not peer-reviewed
Does Urban Landscape Composition and Configuration Regulate Heat-Related Health Risk? A Spatial Regression-Based Study in World’s Dense City Delhi, India
Version 1
: Received: 1 November 2020 / Approved: 2 November 2020 / Online: 2 November 2020 (13:53:03 CET)
How to cite:
Pramanik, S.; Punia, M.; Chakraborty, S. Does Urban Landscape Composition and Configuration Regulate Heat-Related Health Risk? A Spatial Regression-Based Study in World’s Dense City Delhi, India. Preprints2020, 2020110046
Pramanik, S.; Punia, M.; Chakraborty, S. Does Urban Landscape Composition and Configuration Regulate Heat-Related Health Risk? A Spatial Regression-Based Study in World’s Dense City Delhi, India. Preprints 2020, 2020110046
Pramanik, S.; Punia, M.; Chakraborty, S. Does Urban Landscape Composition and Configuration Regulate Heat-Related Health Risk? A Spatial Regression-Based Study in World’s Dense City Delhi, India. Preprints2020, 2020110046
APA Style
Pramanik, S., Punia, M., & Chakraborty, S. (2020). Does Urban Landscape Composition and Configuration Regulate Heat-Related Health Risk? A Spatial Regression-Based Study in World’s Dense City Delhi, India. Preprints. https://doi.org/
Chicago/Turabian Style
Pramanik, S., Milap Punia and Saurav Chakraborty. 2020 "Does Urban Landscape Composition and Configuration Regulate Heat-Related Health Risk? A Spatial Regression-Based Study in World’s Dense City Delhi, India" Preprints. https://doi.org/
Abstract
Urbanization induced land use land cover (LULC) changes intensify the urban heat island effects. It magnifies the risk of urban dwellers and sometimes causes the loss of human life, defined as heat-related health risk (HRHR). Hence, urban LULC planning plays a crucial role. Present study analyses the impact of composition and configuration of urban LULC defined as urban landscape metric (ULM) on HRHR in Delhi at the ward level. Firstly, the HRHR is measured by using satellite thermal and other digital data. Then, measured HRHR is validated by conducting a rapid field survey. Thirdly, ULM measured at ward level using Fragstat 4 software. Finally, both, HRHR and ULM linked with bi-variate Moran's I and impacts of ULM are assessed using ordinary least square (OLS) and spatial error (SE) regression. The result indicates the high risk is found as clustered in north-east, central and middle of south-west Delhi. Built-up density intensifies HRHR and abundance of vegetation reduce it; however, it is not similar for all vegetation patches. Larger vegetation patches surrounded by dense built-up might not able to reduce the risk as much as a large vegetation patch could in other regions. Findings can be helpful for heat resilient city planning.
Keywords
Urban Heat Island; Heat-Related Health Risk (HRHR); Urban Landscape Metrics (ULM); Local Indicators of Spatial Autocorrelation (LISA); Spatial Error (SE) Regression; NCT-Delhi.
Subject
Public Health and Healthcare, Public, Environmental and Occupational Health
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.