Quantifying Connections Between Urban LCLUC and Emerging Extreme Heat in Rapidly Growing Indian Cities

SIGNIFICANCE: The rapid growth of urban settlements, combined with climate change and the urban heat island effect, has increased the risk of extreme heat exposure. In the Indian subcontinent, fast-developing cities have experienced a significant rise in the frequency, intensity, and duration of heatwaves, posing a threat to nearly a billion people who regularly experience temperatures exceeding 100F during summers.

PROBLEM STATEMENT: Current global estimates of heat exposure underestimate the risk to urban residents due to high thermal variability within cities. Therefore, there is an urgent need of characterizing where urban growth and extreme heat emergence intersects at scales of <50m.

KEY SCIENCE  QUESTIONS: Here, we have identified six archetype Indian cities that collectively represent the diverse Indian climate types as well as urban form and growth trajectories. These cities will help answer the following scientific questions: 1. What is the impact of heatwaves (large-scale advective driven) versus the urban heat island (local-scale convective driven) on the intra-urban thermal footprint of each city? 2. From city growth over the past decade (from 2013-2023), where does rapid urban growth and extreme heat emergence intersect in each of the cities? 3. What are the dominant thermal properties of different urban LCLU classes that contribute to the day and nighttime surface urban heat island effect?

OBJECTIVES AND METHODOLOGY: We will achieve this through the following three objectives: 1. Use VIIRS 375-m LST data to create annual composite day/night maps of urban summertime heat and extreme heat (heatwaves) for the selected Indian cities from 2013 to 2023. We will analyze the probability distribution functions of the size and intensity of intra-urban extreme heat islets, which are clusters of high temperatures within the city, to quantify the trend of intra-urban warming over the study period. 2. For characterizing the urban LCLU growth, we will use the Local Climate Zone (LCZ) classification scheme, which is a globally consistent and climatologically relevant approach for describing and categorizing the physical characteristics of urban form and function. LCZ maps for three-time steps (2013, 2018, 2023) will be created for each of the six cities using Landsat optical imagery. The time series of VIIRS LST climatology and LCZ maps will then be used to identify regions of rapid urban changes that have significantly impacted the local thermal environment. 3. Within the identified regions of rapid change, we will examine the relationships between the thermal properties of land cover changes and the diurnal variations in Land Surface Temperature (LST). For this analysis, we will utilize sharpened ECOSTRESS and Landsat LST data (30m) which will provide crucial detailed spatial information for resolving fine-scale structures in urban environments. Additionally, the day and night coverage of ECOSTRESS will enable us to estimate the Diurnal Thermal Range (DTR) and Apparent Thermal Inertia (ATI), allowing us to characterize the thermal properties of urban materials and understand how they relate to changes in land cover.

EARTH OBSERVATION DATA USED: This study will rely on using TIR data from VIIRS, Landsat and ECOSTRESS to map the summertime as well as heatwave scenario LSTs of the selected Indian cities. These data will be used in combination with VSWIR data from Landsat for urban LCLUC mapping and quantify connections between emerging heat and urban growth over the last decade (2013-2023 and onward). The proposed work advances the Multi-Source Land Imaging (MuSLI) of the LCLUC program by combining TIR and optical data described above.

CONCLUSION: Better understanding the total urban warming trajectories will help cities to identify regions where locally tailored adaptation measures are most needed to mitigate heat risk.