Examining the Effects of Heat Mitigation on the Physical Properties of Urban Green Space and Urban Blue Space: A Case Study

Abstract

<p>The smart and sustainable city idea gained momentum in recent years in order to cope with population growth in urban areas and to make the city live. Cities are projected to consume 70% of the world's resources and 66% of the world population by 2050. Most of tier-3 and tier-2 cities will convert to tier-1 city, and we need to identify and protect the urban green spaces. Urban green areas have many esthetic advantages, including environmental benefits such as a fall in city temperature in the summer and absorption of rainwater. Social advantages are such as feelings of happiness and peace. Objective quantification of greenery on its neighbourhood spatial distribution may help identify essential and potential areas. Heterogeneous land uses describe urban areas. Urban heat island (UHI), with high Land surface temperatures (LST), is distinguished by its city development pattern, socioeconomic and anthropogenic activities. The LST is rising rapidly not only in cities but also in tier-3 & tier-2 cities.  Urban green areas, including parks, playgrounds, gardens and areas, such as ponds, pools, lakes and rivers, will contribute to the control of land temperatures in and around the city. Such spaces also lead to the formation of the Urban Cooling Island (UCI), where temperatures are comparatively cooler than surrounding temperatures, because of their shade of the trees and their evapotranspiration. This cooling island formation is referred to as the Park Cooling Island (PCI) impact. The present work aims to describe the effect of urban green and urban blue spaces on LST using a range of data sources with geospatial technologies. Udupi town, which comes under Udupi district, Karnataka, India is a tier-3 city, selected for the present research work. The data used in the study include Landsat 8 temporal satellite images and secondary data, such as field data from various government and semi-government organisations. LST has been measured using the emissivity reference channel algorithm from Landsat 8 thermal bands. Different indices such as Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index NDWI, Land Shape Index (LSI) are determined from images from Landsat 8. The results show that LST exists with high spatial variability and urban green, blue spaces have a stronger influence on LST.</p>