Swelter in the city: Urban greenery and its effects on temperature in Guwahati, India

Abstract

Changing urban landscape with multistoried high rises, roads and pavements is continuously reducing urban green space. These structures result in high surface temperature variation within cities. To explore the relationship between surface temperature and normalized difference vegetation index (NDVI), this study estimates two models—geographically weighted regression (GWR) and a fixed effect panel data model in relation to the Guwahati Metropolitan Area (GMA), a secondary city in north east India. The results indicate the superiority of GWR regression in presence of spatial dependence. Panel data analysis shows that the densely populated urban areas in the GMA with less than 10 per cent greenery are 1°C warmer than the sub‐urban areas with 50 per cent greenery.

Beating the Heat

“…Data from Asian megacities suggest that the UHI effect increases by 0.47°C in the day and by 0.30°C at night for every million people (Hung et al 2006). Conversely, protection of green areas and water bodies can create a cool "oasis effect," especially for cities in arid and semiarid climate zones (Rahul, Mukherjee, and Sood 2020;Borthakur, Saikia, and Sharma 2020). In Bangkok, Jakarta, and Manila, the mean land surface temperature of green space is approximately 3 °C c o o l e r t h a n i m p e r v i o u s a r e a s (Estoque, Murayama, and Myint 2017).…”

Study of the Urban Heat Island (UHI) Using Remote Sensing Data/Techniques: A Systematic Review

“…GWR was found to be effective [151], more than OLS [152][153][154][155], and provides an analysis of the multiple spatial data layers with autocorrelated structures [156], predicts the behavior of variables with better accuracy, and can describe spatial non-stationarity [157].…”